mirror of
https://github.com/CNugteren/CLBlast.git
synced 2024-08-22 21:12:26 +02:00
Merge pull request #99 from CNugteren/development
Update to version 0.9.0
This commit is contained in:
commit
f07ac22f5b
|
@ -1,8 +1,8 @@
|
||||||
environment:
|
environment:
|
||||||
global:
|
global:
|
||||||
CLBLAST_ROOT: "%APPVEYOR_BUILD_FOLDER%\\bin\\clblast"
|
CLBLAST_ROOT: "%APPVEYOR_BUILD_FOLDER%\\..\\bin\\clblast"
|
||||||
OPENCL_REGISTRY: "https://www.khronos.org/registry/cl"
|
OPENCL_REGISTRY: "https://www.khronos.org/registry/cl"
|
||||||
OPENCL_ROOT: "%APPVEYOR_BUILD_FOLDER%\\bin\\opencl"
|
OPENCL_ROOT: "%APPVEYOR_BUILD_FOLDER%\\..\\bin\\opencl"
|
||||||
|
|
||||||
platform:
|
platform:
|
||||||
- x64
|
- x64
|
||||||
|
|
3
.gitignore
vendored
3
.gitignore
vendored
|
@ -2,5 +2,6 @@ build
|
||||||
stash
|
stash
|
||||||
.*
|
.*
|
||||||
*.pyc
|
*.pyc
|
||||||
*.db
|
database.json
|
||||||
|
database_best.json
|
||||||
cl.hpp
|
cl.hpp
|
32
.travis.yml
32
.travis.yml
|
@ -17,49 +17,21 @@ addons:
|
||||||
- kubuntu-backports
|
- kubuntu-backports
|
||||||
packages:
|
packages:
|
||||||
- cmake
|
- cmake
|
||||||
|
- ocl-icd-opencl-dev
|
||||||
|
|
||||||
env:
|
env:
|
||||||
global:
|
global:
|
||||||
- CLBLAST_ROOT=${TRAVIS_BUILD_DIR}/bin/clblast
|
- CLBLAST_ROOT=${TRAVIS_BUILD_DIR}/bin/clblast
|
||||||
- OPENCL_REGISTRY=https://www.khronos.org/registry/cl
|
|
||||||
- OPENCL_ROOT=${TRAVIS_BUILD_DIR}/bin/opencl
|
|
||||||
|
|
||||||
before_install:
|
before_install:
|
||||||
- cmake --version;
|
- cmake --version;
|
||||||
- ${CC} --version;
|
- ${CC} --version;
|
||||||
- ${CXX} --version;
|
- ${CXX} --version;
|
||||||
|
|
||||||
install:
|
|
||||||
# The following linux logic is necessary because of Travis's move to the GCE platform, which does not
|
|
||||||
# currently contain packages for fglrx: https://github.com/travis-ci/travis-ci/issues/5221
|
|
||||||
# We build our own linkable .so file
|
|
||||||
- if [ ${TRAVIS_OS_NAME} == "linux" ]; then
|
|
||||||
mkdir -p ${OPENCL_ROOT};
|
|
||||||
pushd ${OPENCL_ROOT};
|
|
||||||
travis_retry git clone --depth 1 https://github.com/KhronosGroup/OpenCL-ICD-Loader.git;
|
|
||||||
mv ./OpenCL-ICD-Loader/* .;
|
|
||||||
travis_retry git clone --depth 1 https://github.com/KhronosGroup/OpenCL-Headers.git inc/CL;
|
|
||||||
pushd inc/CL;
|
|
||||||
travis_retry wget -w 1 -np -nd -nv -A h,hpp ${OPENCL_REGISTRY}/api/2.1/cl.hpp;
|
|
||||||
popd;
|
|
||||||
mkdir -p lib;
|
|
||||||
pushd lib;
|
|
||||||
cmake -G "Unix Makefiles" ..;
|
|
||||||
make;
|
|
||||||
cp ./bin/libOpenCL.so .;
|
|
||||||
popd;
|
|
||||||
pushd inc/CL;
|
|
||||||
travis_retry git fetch origin opencl12:opencl12;
|
|
||||||
git checkout opencl12;
|
|
||||||
popd;
|
|
||||||
mv inc/ include/;
|
|
||||||
popd;
|
|
||||||
fi
|
|
||||||
|
|
||||||
before_script:
|
before_script:
|
||||||
- mkdir -p ${CLBLAST_ROOT}
|
- mkdir -p ${CLBLAST_ROOT}
|
||||||
- pushd ${CLBLAST_ROOT}
|
- pushd ${CLBLAST_ROOT}
|
||||||
- cmake -DOPENCL_ROOT=${OPENCL_ROOT} -DTESTS=ON -DCLIENTS=ON ${TRAVIS_BUILD_DIR}
|
- cmake -DTESTS=ON -DCLIENTS=ON ${TRAVIS_BUILD_DIR}
|
||||||
|
|
||||||
script:
|
script:
|
||||||
- make
|
- make
|
||||||
|
|
15
CHANGELOG
15
CHANGELOG
|
@ -1,4 +1,19 @@
|
||||||
|
|
||||||
|
Version 0.9.0
|
||||||
|
- Updated to version 6.0 of the CLCudaAPI C++11 OpenCL header
|
||||||
|
- Improved performance significantly of rotated GEMV computations
|
||||||
|
- Improved performance of unseen/un-tuned devices by a better default tuning parameter selection
|
||||||
|
- Fixed proper MSVC dllimport and dllexport declarations
|
||||||
|
- Fixed memory leaks related to events not being released
|
||||||
|
- Fixed a bug with a size_t and cl_ulong mismatch on 32-bit systems
|
||||||
|
- Fixed a bug related to the cache and retrieval of programs based on the OpenCL context
|
||||||
|
- Fixed a performance issue (caused by fp16 support) by optimizing alpha/beta parameter passing to kernels
|
||||||
|
- Fixed a bug in the OpenCL kernels: now placing __kernel before __attribute__
|
||||||
|
- Fixed a bug in level-3 routines when beta is zero and matrix C contains NaNs
|
||||||
|
- Added an option (-warm_up) to do a warm-up run before timing in the performance clients
|
||||||
|
- Various minor fixes and enhancements
|
||||||
|
- Added tuned parameters for various devices (see README)
|
||||||
|
|
||||||
Version 0.8.0
|
Version 0.8.0
|
||||||
- Added support for half-precision floating-point (fp16) in the library
|
- Added support for half-precision floating-point (fp16) in the library
|
||||||
- Made it possible to compile the performance tests (clients) separately from the correctness tests
|
- Made it possible to compile the performance tests (clients) separately from the correctness tests
|
||||||
|
|
|
@ -9,7 +9,7 @@
|
||||||
#
|
#
|
||||||
# ==================================================================================================
|
# ==================================================================================================
|
||||||
|
|
||||||
cmake_minimum_required(VERSION 2.8.10)
|
cmake_minimum_required(VERSION 2.8.11)
|
||||||
|
|
||||||
# Overrides for MSVC static runtime
|
# Overrides for MSVC static runtime
|
||||||
set(CMAKE_USER_MAKE_RULES_OVERRIDE ${CMAKE_CURRENT_SOURCE_DIR}/cmake/c_flag_overrides.cmake)
|
set(CMAKE_USER_MAKE_RULES_OVERRIDE ${CMAKE_CURRENT_SOURCE_DIR}/cmake/c_flag_overrides.cmake)
|
||||||
|
@ -18,7 +18,7 @@ set(CMAKE_USER_MAKE_RULES_OVERRIDE_CXX ${CMAKE_CURRENT_SOURCE_DIR}/cmake/cxx_fla
|
||||||
# CMake project details
|
# CMake project details
|
||||||
project("clblast" C CXX)
|
project("clblast" C CXX)
|
||||||
set(clblast_VERSION_MAJOR 0)
|
set(clblast_VERSION_MAJOR 0)
|
||||||
set(clblast_VERSION_MINOR 8)
|
set(clblast_VERSION_MINOR 9)
|
||||||
set(clblast_VERSION_PATCH 0)
|
set(clblast_VERSION_PATCH 0)
|
||||||
|
|
||||||
# Options and their default values
|
# Options and their default values
|
||||||
|
@ -27,6 +27,13 @@ option(TUNERS "Enable compilation of the tuners" OFF)
|
||||||
option(CLIENTS "Enable compilation of the clients to test and compare performance" OFF)
|
option(CLIENTS "Enable compilation of the clients to test and compare performance" OFF)
|
||||||
option(TESTS "Enable compilation of the correctness tests" OFF)
|
option(TESTS "Enable compilation of the correctness tests" OFF)
|
||||||
|
|
||||||
|
# Compile in verbose mode with additional diagnostic messages
|
||||||
|
option(VERBOSE "Compile in verbose mode for additional diagnostic messages" OFF)
|
||||||
|
if(VERBOSE)
|
||||||
|
message("-- Building in verbose mode")
|
||||||
|
add_definitions(-DVERBOSE)
|
||||||
|
endif()
|
||||||
|
|
||||||
# ==================================================================================================
|
# ==================================================================================================
|
||||||
|
|
||||||
# RPATH settings
|
# RPATH settings
|
||||||
|
@ -68,6 +75,12 @@ else()
|
||||||
if(CMAKE_CXX_COMPILER_VERSION VERSION_LESS 4.9.0)
|
if(CMAKE_CXX_COMPILER_VERSION VERSION_LESS 4.9.0)
|
||||||
set(FLAGS "${FLAGS} -Wno-attributes -Wno-unused-variable")
|
set(FLAGS "${FLAGS} -Wno-attributes -Wno-unused-variable")
|
||||||
endif()
|
endif()
|
||||||
|
if(CMAKE_CXX_COMPILER_VERSION VERSION_GREATER 6.0.0)
|
||||||
|
# GCC does not support attributes on template arguments
|
||||||
|
# in particular we hit this with the alignment attributes on cl_XXX types
|
||||||
|
# which are then used to instantiate various templates in CLBlast
|
||||||
|
set(FLAGS "${FLAGS} -Wno-ignored-attributes")
|
||||||
|
endif()
|
||||||
elseif(CMAKE_CXX_COMPILER_ID MATCHES Clang)
|
elseif(CMAKE_CXX_COMPILER_ID MATCHES Clang)
|
||||||
set(FLAGS "${FLAGS} -Wextra -Wno-c++98-compat -Wno-c++98-compat-pedantic -Wno-padded")
|
set(FLAGS "${FLAGS} -Wextra -Wno-c++98-compat -Wno-c++98-compat-pedantic -Wno-padded")
|
||||||
set(FLAGS "${FLAGS} -Wno-missing-prototypes -Wno-float-equal -Wno-switch-enum -Wno-switch")
|
set(FLAGS "${FLAGS} -Wno-missing-prototypes -Wno-float-equal -Wno-switch-enum -Wno-switch")
|
||||||
|
@ -88,7 +101,7 @@ set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} ${CFLAGS}")
|
||||||
# ==================================================================================================
|
# ==================================================================================================
|
||||||
|
|
||||||
# Package scripts location
|
# Package scripts location
|
||||||
set(CMAKE_MODULE_PATH ${CMAKE_MODULE_PATH} "${CMAKE_SOURCE_DIR}/cmake/Modules/")
|
set(CMAKE_MODULE_PATH ${CMAKE_MODULE_PATH} "${clblast_SOURCE_DIR}/cmake/Modules/")
|
||||||
|
|
||||||
# Requires OpenCL. It is found through the included "FindOpenCL.cmake" in CMAKE_MODULE_PATH.
|
# Requires OpenCL. It is found through the included "FindOpenCL.cmake" in CMAKE_MODULE_PATH.
|
||||||
find_package(OpenCL REQUIRED)
|
find_package(OpenCL REQUIRED)
|
||||||
|
@ -120,11 +133,6 @@ endif()
|
||||||
|
|
||||||
# ==================================================================================================
|
# ==================================================================================================
|
||||||
|
|
||||||
# Includes directories: CLBlast and OpenCL
|
|
||||||
include_directories(${clblast_SOURCE_DIR}/include ${clblast_SOURCE_DIR}/src ${OPENCL_INCLUDE_DIRS})
|
|
||||||
|
|
||||||
# ==================================================================================================
|
|
||||||
|
|
||||||
# Sets the supported routines and the used kernels. New routines and kernels should be added here.
|
# Sets the supported routines and the used kernels. New routines and kernels should be added here.
|
||||||
set(KERNELS copy_fast copy_pad transpose_fast transpose_pad xaxpy xdot xger xgemm xgemv)
|
set(KERNELS copy_fast copy_pad transpose_fast transpose_pad xaxpy xdot xger xgemm xgemv)
|
||||||
set(SAMPLE_PROGRAMS_CPP sgemm)
|
set(SAMPLE_PROGRAMS_CPP sgemm)
|
||||||
|
@ -166,21 +174,36 @@ endforeach()
|
||||||
add_library(clblast SHARED ${SOURCES})
|
add_library(clblast SHARED ${SOURCES})
|
||||||
target_link_libraries(clblast ${OPENCL_LIBRARIES})
|
target_link_libraries(clblast ${OPENCL_LIBRARIES})
|
||||||
|
|
||||||
|
# Includes directories: CLBlast and OpenCL
|
||||||
|
target_include_directories(clblast PUBLIC
|
||||||
|
$<BUILD_INTERFACE:${clblast_SOURCE_DIR}/include>
|
||||||
|
$<BUILD_INTERFACE:${clblast_SOURCE_DIR}/src>
|
||||||
|
$<INSTALL_INTERFACE:include>
|
||||||
|
${OPENCL_INCLUDE_DIRS})
|
||||||
|
|
||||||
|
# Sets the proper __declspec(dllexport) keyword for Visual Studio when the library is built
|
||||||
|
if(MSVC)
|
||||||
|
target_compile_definitions(clblast PRIVATE COMPILING_DLL=1) # requires at least CMake 2.8.11
|
||||||
|
endif()
|
||||||
|
|
||||||
# Installs the library
|
# Installs the library
|
||||||
install(TARGETS clblast DESTINATION lib)
|
install(TARGETS clblast EXPORT CLBlast DESTINATION lib)
|
||||||
install(FILES include/clblast.h DESTINATION include)
|
install(FILES include/clblast.h DESTINATION include)
|
||||||
install(FILES include/clblast_c.h DESTINATION include)
|
install(FILES include/clblast_c.h DESTINATION include)
|
||||||
install(FILES include/clblast_half.h DESTINATION include)
|
install(FILES include/clblast_half.h DESTINATION include)
|
||||||
|
|
||||||
|
# Installs the config for find_package in dependent projects
|
||||||
|
install(EXPORT CLBlast DESTINATION lib/cmake/CLBLast FILE CLBlastConfig.cmake)
|
||||||
|
|
||||||
# ==================================================================================================
|
# ==================================================================================================
|
||||||
|
|
||||||
# Sets a default platform ($DEVICEPLATFORM) and device ($DEFAULT_DEVICE) to run tuners and tests on
|
# Sets a default platform ($DEVICEPLATFORM) and device ($CLBLAST_DEVICE) to run tuners and tests on
|
||||||
set(DEVICEPLATFORM )
|
set(DEVICEPLATFORM )
|
||||||
if(DEFINED ENV{DEFAULT_DEVICE})
|
if(DEFINED ENV{CLBLAST_DEVICE})
|
||||||
set(DEVICEPLATFORM ${DEVICEPLATFORM} -device $ENV{DEFAULT_DEVICE})
|
set(DEVICEPLATFORM ${DEVICEPLATFORM} -device $ENV{CLBLAST_DEVICE})
|
||||||
endif()
|
endif()
|
||||||
if(DEFINED ENV{DEFAULT_PLATFORM})
|
if(DEFINED ENV{CLBLAST_PLATFORM})
|
||||||
set(DEVICEPLATFORM ${DEVICEPLATFORM} -platform $ENV{DEFAULT_PLATFORM})
|
set(DEVICEPLATFORM ${DEVICEPLATFORM} -platform $ENV{CLBLAST_PLATFORM})
|
||||||
endif()
|
endif()
|
||||||
|
|
||||||
# ==================================================================================================
|
# ==================================================================================================
|
||||||
|
@ -213,13 +236,17 @@ endif()
|
||||||
# the CLTune library (not included as part of the source).
|
# the CLTune library (not included as part of the source).
|
||||||
if(TUNERS)
|
if(TUNERS)
|
||||||
|
|
||||||
# Includes CLTune
|
# Visual Studio requires the sources of non-exported objects/libraries
|
||||||
include_directories(${CLTUNE_INCLUDE_DIRS})
|
set(TUNERS_COMMON )
|
||||||
|
if(MSVC)
|
||||||
|
set(TUNERS_COMMON ${TUNERS_COMMON} src/utilities.cpp)
|
||||||
|
endif()
|
||||||
|
|
||||||
# Adds tuning executables
|
# Adds tuning executables
|
||||||
foreach(KERNEL ${KERNELS})
|
foreach(KERNEL ${KERNELS})
|
||||||
add_executable(clblast_tuner_${KERNEL} src/tuning/kernels/${KERNEL}.cpp)
|
add_executable(clblast_tuner_${KERNEL} ${TUNERS_COMMON} src/tuning/kernels/${KERNEL}.cpp)
|
||||||
target_link_libraries(clblast_tuner_${KERNEL} clblast ${CLTUNE_LIBRARIES} ${OPENCL_LIBRARIES})
|
target_link_libraries(clblast_tuner_${KERNEL} clblast ${CLTUNE_LIBRARIES} ${OPENCL_LIBRARIES})
|
||||||
|
target_include_directories(clblast_tuner_${KERNEL} PUBLIC ${CLTUNE_INCLUDE_DIRS})
|
||||||
install(TARGETS clblast_tuner_${KERNEL} DESTINATION bin)
|
install(TARGETS clblast_tuner_${KERNEL} DESTINATION bin)
|
||||||
endforeach()
|
endforeach()
|
||||||
|
|
||||||
|
@ -263,9 +290,6 @@ if(CLIENTS OR TESTS)
|
||||||
endif()
|
endif()
|
||||||
endif()
|
endif()
|
||||||
|
|
||||||
# Sets the include directories
|
|
||||||
include_directories(${clblast_SOURCE_DIR} ${REF_INCLUDES})
|
|
||||||
|
|
||||||
endif()
|
endif()
|
||||||
|
|
||||||
# ==================================================================================================
|
# ==================================================================================================
|
||||||
|
@ -281,6 +305,11 @@ if(CLIENTS)
|
||||||
else()
|
else()
|
||||||
# Creates the common performance-tests objects (requires CMake 2.8.8)
|
# Creates the common performance-tests objects (requires CMake 2.8.8)
|
||||||
add_library(test_performance_common OBJECT test/performance/client.cpp)
|
add_library(test_performance_common OBJECT test/performance/client.cpp)
|
||||||
|
|
||||||
|
# Adds CLBlast's interface include paths because we can't link to CLBlast here
|
||||||
|
target_include_directories(test_performance_common PRIVATE
|
||||||
|
$<TARGET_PROPERTY:clblast,INTERFACE_INCLUDE_DIRECTORIES>
|
||||||
|
${clblast_SOURCE_DIR})
|
||||||
set(CLIENTS_COMMON ${CLIENTS_COMMON} $<TARGET_OBJECTS:test_performance_common>)
|
set(CLIENTS_COMMON ${CLIENTS_COMMON} $<TARGET_OBJECTS:test_performance_common>)
|
||||||
endif()
|
endif()
|
||||||
|
|
||||||
|
@ -303,6 +332,7 @@ if(CLIENTS)
|
||||||
endforeach()
|
endforeach()
|
||||||
foreach(ROUTINE ${ROUTINES})
|
foreach(ROUTINE ${ROUTINES})
|
||||||
target_link_libraries(clblast_client_${ROUTINE} clblast ${REF_LIBRARIES} ${OPENCL_LIBRARIES})
|
target_link_libraries(clblast_client_${ROUTINE} clblast ${REF_LIBRARIES} ${OPENCL_LIBRARIES})
|
||||||
|
target_include_directories(clblast_client_${ROUTINE} PUBLIC ${clblast_SOURCE_DIR} ${REF_INCLUDES})
|
||||||
install(TARGETS clblast_client_${ROUTINE} DESTINATION bin)
|
install(TARGETS clblast_client_${ROUTINE} DESTINATION bin)
|
||||||
endforeach()
|
endforeach()
|
||||||
|
|
||||||
|
@ -324,6 +354,9 @@ if(TESTS)
|
||||||
# Creates the common correctness-tests objects (requires CMake 2.8.8)
|
# Creates the common correctness-tests objects (requires CMake 2.8.8)
|
||||||
add_library(test_correctness_common OBJECT
|
add_library(test_correctness_common OBJECT
|
||||||
test/correctness/tester.cpp test/correctness/testblas.cpp)
|
test/correctness/tester.cpp test/correctness/testblas.cpp)
|
||||||
|
target_include_directories(test_correctness_common PUBLIC
|
||||||
|
$<TARGET_PROPERTY:clblast,INTERFACE_INCLUDE_DIRECTORIES>
|
||||||
|
${clblast_SOURCE_DIR})
|
||||||
set(TESTS_COMMON ${TESTS_COMMON} $<TARGET_OBJECTS:test_correctness_common>)
|
set(TESTS_COMMON ${TESTS_COMMON} $<TARGET_OBJECTS:test_correctness_common>)
|
||||||
endif()
|
endif()
|
||||||
|
|
||||||
|
@ -347,6 +380,7 @@ if(TESTS)
|
||||||
foreach(ROUTINE ${ROUTINES})
|
foreach(ROUTINE ${ROUTINES})
|
||||||
target_link_libraries(clblast_test_${ROUTINE} clblast ${REF_LIBRARIES} ${OPENCL_LIBRARIES})
|
target_link_libraries(clblast_test_${ROUTINE} clblast ${REF_LIBRARIES} ${OPENCL_LIBRARIES})
|
||||||
install(TARGETS clblast_test_${ROUTINE} DESTINATION bin)
|
install(TARGETS clblast_test_${ROUTINE} DESTINATION bin)
|
||||||
|
target_include_directories(clblast_test_${ROUTINE} PUBLIC ${clblast_SOURCE_DIR} ${REF_INCLUDES})
|
||||||
add_test(clblast_test_${ROUTINE} clblast_test_${ROUTINE} ${DEVICEPLATFORM})
|
add_test(clblast_test_${ROUTINE} clblast_test_${ROUTINE} ${DEVICEPLATFORM})
|
||||||
endforeach()
|
endforeach()
|
||||||
|
|
||||||
|
|
19
README.md
19
README.md
|
@ -99,20 +99,26 @@ The CLBlast library will be tuned in the future for the most commonly used OpenC
|
||||||
* NVIDIA GPUs:
|
* NVIDIA GPUs:
|
||||||
- GRID K520
|
- GRID K520
|
||||||
- GeForce GTX 480
|
- GeForce GTX 480
|
||||||
|
- GeForce GTX 670
|
||||||
- GeForce GTX 680
|
- GeForce GTX 680
|
||||||
|
- GeForce GTX 750
|
||||||
- GeForce GTX 750 Ti
|
- GeForce GTX 750 Ti
|
||||||
- GeForce GTX 980
|
- GeForce GTX 980
|
||||||
|
- GeForce GTX 1070
|
||||||
- GeForce GTX Titan
|
- GeForce GTX Titan
|
||||||
- GeForce GTX Titan X
|
- GeForce GTX Titan X
|
||||||
- Tesla K20m
|
- Tesla K20m
|
||||||
- Tesla K40m
|
- Tesla K40m
|
||||||
* AMD GPUs:
|
* AMD GPUs:
|
||||||
- Tahiti
|
- AMD Radeon R9 M370X Compute Engine
|
||||||
- Hawaii
|
- Hawaii
|
||||||
|
- Oland
|
||||||
- Pitcairn
|
- Pitcairn
|
||||||
- Radeon R9 M370X Compute Engine
|
- Tahiti
|
||||||
* Intel GPUs:
|
* Intel GPUs:
|
||||||
|
- HD Graphics 530
|
||||||
- HD Graphics Haswell Ultrabook GT2 Mobile
|
- HD Graphics Haswell Ultrabook GT2 Mobile
|
||||||
|
- HD Graphics 5500 BroadWell U-Processor GT2
|
||||||
- HD Graphics Skylake ULT GT2
|
- HD Graphics Skylake ULT GT2
|
||||||
- Iris
|
- Iris
|
||||||
- Iris Pro
|
- Iris Pro
|
||||||
|
@ -130,7 +136,7 @@ If your device is not (yet) among this list or if you want to tune CLBlast for s
|
||||||
|
|
||||||
Note that CLBlast's tuners are based on the [CLTune auto-tuning library](https://github.com/CNugteren/CLTune), which has to be installed separately (requires version 2.3.1 or higher).
|
Note that CLBlast's tuners are based on the [CLTune auto-tuning library](https://github.com/CNugteren/CLTune), which has to be installed separately (requires version 2.3.1 or higher).
|
||||||
|
|
||||||
Compiling with `-DTUNERS=ON` will generate a number of tuners, each named `clblast_tuner_xxxxx`, in which `xxxxx` corresponds to a `.opencl` kernel file as found in `src/kernels`. These kernels corresponds to routines (e.g. `xgemm`) or to common pre-processing or post-processing kernels (`copy` and `transpose`). Running such a tuner will test a number of parameter-value combinations on your device and report which one gave the best performance. Running `make alltuners` runs all tuners for all precisions in one go. You can set the default device and platform for `alltuners` by setting the `DEFAULT_DEVICE` and `DEFAULT_PLATFORM` environmental variables before running CMake.
|
Compiling with `-DTUNERS=ON` will generate a number of tuners, each named `clblast_tuner_xxxxx`, in which `xxxxx` corresponds to a `.opencl` kernel file as found in `src/kernels`. These kernels corresponds to routines (e.g. `xgemm`) or to common pre-processing or post-processing kernels (`copy` and `transpose`). Running such a tuner will test a number of parameter-value combinations on your device and report which one gave the best performance. Running `make alltuners` runs all tuners for all precisions in one go. You can set the default device and platform for `alltuners` by setting the `CLBLAST_DEVICE` and `CLBLAST_PLATFORM` environmental variables before running CMake.
|
||||||
|
|
||||||
The tuners output a JSON-file with the results. The best results need to be added to `src/database/kernels/xxxxx.hpp` in the appropriate section. However, this can be done automatically based on the JSON-data using a Python script in `scripts/database/database.py`. If you want the found parameters to be included in future releases of CLBlast, please attach the JSON files to the corresponding issue on GitHub or [email the main author](http://www.cedricnugteren.nl).
|
The tuners output a JSON-file with the results. The best results need to be added to `src/database/kernels/xxxxx.hpp` in the appropriate section. However, this can be done automatically based on the JSON-data using a Python script in `scripts/database/database.py`. If you want the found parameters to be included in future releases of CLBlast, please attach the JSON files to the corresponding issue on GitHub or [email the main author](http://www.cedricnugteren.nl).
|
||||||
|
|
||||||
|
@ -162,7 +168,7 @@ To build these tests, another BLAS library is needed to serve as a reference. Th
|
||||||
|
|
||||||
Afterwards, executables in the form of `clblast_test_xxxxx` are available, in which `xxxxx` is the name of a routine (e.g. `xgemm`). Note that CLBlast is tested for correctness against [clBLAS](http://github.com/clMathLibraries/clBLAS) and/or a regular CPU BLAS library. If both are installed on your system, setting the command-line option `-clblas 1` or `-cblas 1` will select the library to test against for the `clblast_test_xxxxx` executables. All tests have a `-verbose` option to enable additional diagnostic output. They also have a `-full_test` option to increase coverage further.
|
Afterwards, executables in the form of `clblast_test_xxxxx` are available, in which `xxxxx` is the name of a routine (e.g. `xgemm`). Note that CLBlast is tested for correctness against [clBLAS](http://github.com/clMathLibraries/clBLAS) and/or a regular CPU BLAS library. If both are installed on your system, setting the command-line option `-clblas 1` or `-cblas 1` will select the library to test against for the `clblast_test_xxxxx` executables. All tests have a `-verbose` option to enable additional diagnostic output. They also have a `-full_test` option to increase coverage further.
|
||||||
|
|
||||||
All tests can be run directly together in one go through the `make alltests` target or using CTest (`make test` or `ctest`). In the latter case the output is less verbose. Both cases allow you to set the default device and platform to non-zero by setting the `DEFAULT_DEVICE` and `DEFAULT_PLATFORM` environmental variables before running CMake.
|
All tests can be run directly together in one go through the `make alltests` target or using CTest (`make test` or `ctest`). In the latter case the output is less verbose. Both cases allow you to set the default device and platform to non-zero by setting the `CLBLAST_DEVICE` and `CLBLAST_PLATFORM` environmental variables before running CMake.
|
||||||
|
|
||||||
|
|
||||||
Compiling the performance tests/clients (optional)
|
Compiling the performance tests/clients (optional)
|
||||||
|
@ -180,6 +186,8 @@ The folder `doc/performance` contains some PDF files with performance results on
|
||||||
|
|
||||||
Note that the CLBlast library provides pre-tuned parameter-values for some devices only: if your device is not among these, then out-of-the-box performance might be poor. See above under `Using the tuners` to find out how to tune for your device.
|
Note that the CLBlast library provides pre-tuned parameter-values for some devices only: if your device is not among these, then out-of-the-box performance might be poor. See above under `Using the tuners` to find out how to tune for your device.
|
||||||
|
|
||||||
|
In case performance is still sub-optimal or something else is wrong, CLBlast can be build in verbose mode for (performance) debugging by specifying `-DVERBOSE=ON` to CMake.
|
||||||
|
|
||||||
|
|
||||||
Supported routines
|
Supported routines
|
||||||
-------------
|
-------------
|
||||||
|
@ -278,6 +286,9 @@ The contributing authors (code, pull requests, testing) so far are:
|
||||||
* [Dragan Djuric](https://github.com/blueberry)
|
* [Dragan Djuric](https://github.com/blueberry)
|
||||||
* [Marco Hutter](https://github.com/gpus)
|
* [Marco Hutter](https://github.com/gpus)
|
||||||
* [Hugh Perkins](https://github.com/hughperkins)
|
* [Hugh Perkins](https://github.com/hughperkins)
|
||||||
|
* [Gian-Carlo Pascutto](https://github.com/gcp)
|
||||||
|
* [Ivan Shapovalov](https://github.com/intelfx)
|
||||||
|
* [Dimitri Van Assche](https://github.com/dvasschemacq)
|
||||||
|
|
||||||
Tuning and testing on a variety of OpenCL devices was made possible by:
|
Tuning and testing on a variety of OpenCL devices was made possible by:
|
||||||
|
|
||||||
|
|
|
@ -25,6 +25,18 @@
|
||||||
#include <CL/opencl.h>
|
#include <CL/opencl.h>
|
||||||
#endif
|
#endif
|
||||||
|
|
||||||
|
// Exports library functions under Windows when building a DLL. See also:
|
||||||
|
// https://msdn.microsoft.com/en-us/library/a90k134d.aspx
|
||||||
|
#ifdef _WIN32
|
||||||
|
#ifdef COMPILING_DLL
|
||||||
|
#define PUBLIC_API __declspec(dllexport)
|
||||||
|
#else
|
||||||
|
#define PUBLIC_API __declspec(dllimport)
|
||||||
|
#endif
|
||||||
|
#else
|
||||||
|
#define PUBLIC_API
|
||||||
|
#endif
|
||||||
|
|
||||||
namespace clblast {
|
namespace clblast {
|
||||||
// =================================================================================================
|
// =================================================================================================
|
||||||
|
|
||||||
|
@ -576,11 +588,11 @@ StatusCode Omatcopy(const Layout layout, const Transpose a_transpose,
|
||||||
|
|
||||||
// CLBlast stores binaries of compiled kernels into a cache in case the same kernel is used later on
|
// CLBlast stores binaries of compiled kernels into a cache in case the same kernel is used later on
|
||||||
// for the same device. This cache can be cleared to free up system memory or in case of debugging.
|
// for the same device. This cache can be cleared to free up system memory or in case of debugging.
|
||||||
StatusCode ClearCache();
|
StatusCode PUBLIC_API ClearCache();
|
||||||
|
|
||||||
// The cache can also be pre-initialized for a specific device with all possible CLBLast kernels.
|
// The cache can also be pre-initialized for a specific device with all possible CLBLast kernels.
|
||||||
// Further CLBlast routine calls will then run at maximum speed.
|
// Further CLBlast routine calls will then run at maximum speed.
|
||||||
StatusCode FillCache(const cl_device_id device);
|
StatusCode PUBLIC_API FillCache(const cl_device_id device);
|
||||||
|
|
||||||
// =================================================================================================
|
// =================================================================================================
|
||||||
|
|
||||||
|
|
|
@ -25,7 +25,11 @@
|
||||||
// Exports library functions under Windows when building a DLL. See also:
|
// Exports library functions under Windows when building a DLL. See also:
|
||||||
// https://msdn.microsoft.com/en-us/library/a90k134d.aspx
|
// https://msdn.microsoft.com/en-us/library/a90k134d.aspx
|
||||||
#ifdef _WIN32
|
#ifdef _WIN32
|
||||||
|
#ifdef COMPILING_DLL
|
||||||
#define PUBLIC_API __declspec(dllexport)
|
#define PUBLIC_API __declspec(dllexport)
|
||||||
|
#else
|
||||||
|
#define PUBLIC_API __declspec(dllimport)
|
||||||
|
#endif
|
||||||
#else
|
#else
|
||||||
#define PUBLIC_API
|
#define PUBLIC_API
|
||||||
#endif
|
#endif
|
||||||
|
|
|
@ -113,6 +113,7 @@ void run_example_routine(const cl_device_id device) {
|
||||||
|
|
||||||
// Wait for completion
|
// Wait for completion
|
||||||
clWaitForEvents(1, &event);
|
clWaitForEvents(1, &event);
|
||||||
|
clReleaseEvent(event);
|
||||||
|
|
||||||
// Retrieves the execution time
|
// Retrieves the execution time
|
||||||
clock_t diff = clock() - start;
|
clock_t diff = clock() - start;
|
||||||
|
|
|
@ -85,6 +85,7 @@ int main(void) {
|
||||||
|
|
||||||
// Wait for completion
|
// Wait for completion
|
||||||
clWaitForEvents(1, &event);
|
clWaitForEvents(1, &event);
|
||||||
|
clReleaseEvent(event);
|
||||||
|
|
||||||
// Example completed. See "clblast_c.h" for status codes (0 -> success).
|
// Example completed. See "clblast_c.h" for status codes (0 -> success).
|
||||||
printf("Completed DGEMV with status %d\n", status);
|
printf("Completed DGEMV with status %d\n", status);
|
||||||
|
|
|
@ -78,6 +78,7 @@ int main(void) {
|
||||||
|
|
||||||
// Wait for completion
|
// Wait for completion
|
||||||
clWaitForEvents(1, &event);
|
clWaitForEvents(1, &event);
|
||||||
|
clReleaseEvent(event);
|
||||||
|
|
||||||
// Copies the result back to the host
|
// Copies the result back to the host
|
||||||
clEnqueueReadBuffer(queue, device_b, CL_TRUE, 0, n*sizeof(cl_half), host_b, 0, NULL, NULL);
|
clEnqueueReadBuffer(queue, device_b, CL_TRUE, 0, n*sizeof(cl_half), host_b, 0, NULL, NULL);
|
||||||
|
|
|
@ -74,6 +74,7 @@ int main(void) {
|
||||||
|
|
||||||
// Wait for completion
|
// Wait for completion
|
||||||
clWaitForEvents(1, &event);
|
clWaitForEvents(1, &event);
|
||||||
|
clReleaseEvent(event);
|
||||||
|
|
||||||
// Copies the result back to the host
|
// Copies the result back to the host
|
||||||
clEnqueueReadBuffer(queue, device_output, CL_TRUE, 0, 1*sizeof(float), host_output, 0, NULL, NULL);
|
clEnqueueReadBuffer(queue, device_output, CL_TRUE, 0, 1*sizeof(float), host_output, 0, NULL, NULL);
|
||||||
|
|
|
@ -88,6 +88,7 @@ int main(void) {
|
||||||
|
|
||||||
// Wait for completion
|
// Wait for completion
|
||||||
clWaitForEvents(1, &event);
|
clWaitForEvents(1, &event);
|
||||||
|
clReleaseEvent(event);
|
||||||
|
|
||||||
// Example completed. See "clblast_c.h" for status codes (0 -> success).
|
// Example completed. See "clblast_c.h" for status codes (0 -> success).
|
||||||
printf("Completed SGEMM with status %d\n", status);
|
printf("Completed SGEMM with status %d\n", status);
|
||||||
|
|
|
@ -96,6 +96,7 @@ int main() {
|
||||||
|
|
||||||
// Record the execution time
|
// Record the execution time
|
||||||
clWaitForEvents(1, &event);
|
clWaitForEvents(1, &event);
|
||||||
|
clReleaseEvent(event);
|
||||||
auto elapsed_time = std::chrono::steady_clock::now() - start_time;
|
auto elapsed_time = std::chrono::steady_clock::now() - start_time;
|
||||||
auto time_ms = std::chrono::duration<double,std::milli>(elapsed_time).count();
|
auto time_ms = std::chrono::duration<double,std::milli>(elapsed_time).count();
|
||||||
|
|
||||||
|
|
343
scripts/database/database.py
Normal file → Executable file
343
scripts/database/database.py
Normal file → Executable file
|
@ -1,325 +1,104 @@
|
||||||
#!/usr/bin/env python
|
#!/usr/bin/env python
|
||||||
|
|
||||||
# ==================================================================================================
|
# This file is part of the CLBlast project. The project is licensed under Apache Version 2.0. This file follows the
|
||||||
# This file is part of the CLBlast project. The project is licensed under Apache Version 2.0. This
|
# PEP8 Python style guide and uses a max-width of 120 characters per line.
|
||||||
# project loosely follows the Google C++ styleguide and uses a max-width of 100 characters per line.
|
|
||||||
#
|
#
|
||||||
# Author(s):
|
# Author(s):
|
||||||
# Cedric Nugteren <www.cedricnugteren.nl>
|
# Cedric Nugteren <www.cedricnugteren.nl>
|
||||||
#
|
|
||||||
# ==================================================================================================
|
|
||||||
|
|
||||||
# System modules
|
|
||||||
import sys
|
import sys
|
||||||
import os.path
|
import os.path
|
||||||
import glob
|
import glob
|
||||||
import re
|
import argparse
|
||||||
import json
|
|
||||||
try:
|
|
||||||
from urllib.request import urlopen # Python 3
|
|
||||||
except ImportError:
|
|
||||||
from urllib2 import urlopen # Python 2
|
|
||||||
|
|
||||||
# Additional modules
|
import database.io as io
|
||||||
import pandas as pd
|
import database.db as db
|
||||||
|
import database.clblast as clblast
|
||||||
|
import database.bests as bests
|
||||||
|
import database.defaults as defaults
|
||||||
|
|
||||||
# Server storing a copy of the database
|
# Server storing a copy of the database
|
||||||
DATABASE_SERVER_URL = "http://www.cedricnugteren.nl/tuning/clblast.db"
|
DATABASE_SERVER_URL = "http://www.cedricnugteren.nl/tuning/clblast.json"
|
||||||
|
|
||||||
# Constants
|
|
||||||
VENDOR_DEFAULT = "default"
|
|
||||||
DEVICETYPE_DEFAULT = "All"
|
|
||||||
DEVICENAME_DEFAULT = "default"
|
|
||||||
|
|
||||||
# Attributes
|
|
||||||
DEVICETYPE_ATTRIBUTES = ["device_vendor", "device_type"]
|
|
||||||
DEVICE_ATTRIBUTES = ["device", "device_core_clock", "device_compute_units"]
|
|
||||||
KERNEL_ATTRIBUTES = ["precision", "kernel_family"]
|
|
||||||
ARGUMENT_ATTRIBUTES = ["arg_m", "arg_n", "arg_k", "arg_alpha", "arg_beta"]
|
|
||||||
ATTRIBUTES = DEVICE_ATTRIBUTES + DEVICETYPE_ATTRIBUTES + KERNEL_ATTRIBUTES + ARGUMENT_ATTRIBUTES
|
|
||||||
|
|
||||||
# OpenCL vendor names and their short name
|
# OpenCL vendor names and their short name
|
||||||
VENDOR_NAMES = { "device_vendor": {
|
VENDOR_TRANSLATION_TABLE = {
|
||||||
"GenuineIntel": "Intel",
|
"GenuineIntel": "Intel",
|
||||||
"Intel(R) Corporation": "Intel",
|
"Intel(R) Corporation": "Intel",
|
||||||
"Advanced Micro Devices, Inc.": "AMD",
|
"Advanced Micro Devices, Inc.": "AMD",
|
||||||
"NVIDIA Corporation": "NVIDIA",
|
"NVIDIA Corporation": "NVIDIA",
|
||||||
}}
|
}
|
||||||
|
|
||||||
# Pandas options
|
|
||||||
pd.set_option('display.width', 1000)
|
|
||||||
|
|
||||||
# ==================================================================================================
|
def main(argv):
|
||||||
# Database operations
|
|
||||||
# ==================================================================================================
|
|
||||||
|
|
||||||
# Downloads the database and save it to disk
|
|
||||||
def DownloadDatabase(filename):
|
|
||||||
print("## Downloading database from '"+DATABASE_SERVER_URL+"'...")
|
|
||||||
df = urlopen(DATABASE_SERVER_URL)
|
|
||||||
output = open(file_db,'wb')
|
|
||||||
output.write(df.read())
|
|
||||||
output.close()
|
|
||||||
|
|
||||||
# Loads the database from disk
|
|
||||||
def LoadDatabase(filename):
|
|
||||||
return pd.read_pickle(filename)
|
|
||||||
|
|
||||||
# Saves the database to disk
|
|
||||||
def SaveDatabase(df, filename):
|
|
||||||
df.to_pickle(filename)
|
|
||||||
|
|
||||||
# Loads JSON data from file
|
|
||||||
def ImportDataFromFile(filename):
|
|
||||||
with open(filename) as f:
|
|
||||||
data = json.load(f)
|
|
||||||
json_data = pd.DataFrame(data)
|
|
||||||
df = pd.io.json.json_normalize(json_data["results"])
|
|
||||||
for attribute in ATTRIBUTES:
|
|
||||||
if attribute == "kernel_family":
|
|
||||||
df[attribute] = re.sub(r'_\d+', '', data[attribute])
|
|
||||||
elif attribute in data:
|
|
||||||
df[attribute] = data[attribute]
|
|
||||||
else:
|
|
||||||
df[attribute] = 0
|
|
||||||
return df
|
|
||||||
|
|
||||||
# Returns the row-wise concatenation of two dataframes
|
|
||||||
def ConcatenateData(df1, df2):
|
|
||||||
return pd.concat([df1, df2])
|
|
||||||
|
|
||||||
# Removes duplicates from a dataframe
|
|
||||||
def RemoveDuplicates(df):
|
|
||||||
return df.drop_duplicates()
|
|
||||||
|
|
||||||
# database = database[(database["device"] != "AMD Radeon R9 M370X Compute Engine") | (database["kernel_family"] != "xgemm") | (database["precision"] != "32")]
|
|
||||||
def RemoveEntriesByDevice(df, devicename):
|
|
||||||
return df[df["device"] != devicename]
|
|
||||||
|
|
||||||
def RemoveEntriesByKernelFamily(df, familyname):
|
|
||||||
return df[df["kernel_family"] != familyname]
|
|
||||||
|
|
||||||
def GetEntriesByField(df, field, value):
|
|
||||||
return df[df[field] == value]
|
|
||||||
|
|
||||||
# Example usage:
|
|
||||||
# df = UpdateDatabase(df, (df["kernel_family"] == "xdot") & (df["arg_n"] == "67108864"), "arg_n", "2097152")
|
|
||||||
def UpdateDatabase(df, condition, field, value):
|
|
||||||
df.loc[condition, field] = value
|
|
||||||
return df
|
|
||||||
|
|
||||||
# Fixes the problem that some vendors use multiple different names
|
|
||||||
def SanitizeVendorNames(df):
|
|
||||||
df = df.replace(VENDOR_NAMES)
|
|
||||||
return df
|
|
||||||
|
|
||||||
# Retrieves the results with the lowest execution times
|
|
||||||
def GetBestResults(df):
|
|
||||||
dfbest = pd.DataFrame()
|
|
||||||
grouped = df.groupby(ATTRIBUTES+["kernel"])
|
|
||||||
for name, dfgroup in grouped:
|
|
||||||
besttime = dfgroup["time"].min()
|
|
||||||
bestcase = dfgroup[dfgroup["time"] == besttime].iloc[0]
|
|
||||||
dfbest = dfbest.append(bestcase, ignore_index=True)
|
|
||||||
return dfbest
|
|
||||||
|
|
||||||
# Sets defaults for devices of the same type/vendor based on the smallest values of all know
|
|
||||||
# entries. The average might be better for performance but some parameters might not be supported
|
|
||||||
# on other devices.
|
|
||||||
def CalculateDefaults(df):
|
|
||||||
dfdefault = pd.DataFrame()
|
|
||||||
|
|
||||||
# Defaults per type/vendor
|
|
||||||
groups = df.groupby(DEVICETYPE_ATTRIBUTES+KERNEL_ATTRIBUTES+ARGUMENT_ATTRIBUTES+["kernel"])
|
|
||||||
for name, dfgroup in groups:
|
|
||||||
default_values = dfgroup.min(axis=0)
|
|
||||||
default_values["device"] = DEVICENAME_DEFAULT
|
|
||||||
default_values["device_compute_units"] = 0
|
|
||||||
default_values["device_core_clock"] = 0
|
|
||||||
default_values["time"] = 0.0
|
|
||||||
dfdefault = dfdefault.append(default_values, ignore_index=True)
|
|
||||||
|
|
||||||
# Checks for mis-matched arguments
|
|
||||||
groups = dfdefault.groupby(DEVICETYPE_ATTRIBUTES+KERNEL_ATTRIBUTES+["kernel"])
|
|
||||||
for name, dfgroup in groups:
|
|
||||||
if len(dfgroup) != 1:
|
|
||||||
description = dfgroup["kernel"].min() + " " + dfgroup["device_vendor"].min()
|
|
||||||
print("[WARNING] Entries for a single kernel with multiple argument values: " + description)
|
|
||||||
|
|
||||||
# Defaults in general
|
|
||||||
groups = df.groupby(KERNEL_ATTRIBUTES+ARGUMENT_ATTRIBUTES+["kernel"])
|
|
||||||
for name, dfgroup in groups:
|
|
||||||
default_values = dfgroup.min(axis=0)
|
|
||||||
default_values["device_vendor"] = VENDOR_DEFAULT
|
|
||||||
default_values["device_type"] = DEVICETYPE_DEFAULT
|
|
||||||
default_values["device"] = DEVICENAME_DEFAULT
|
|
||||||
default_values["device_compute_units"] = 0
|
|
||||||
default_values["device_core_clock"] = 0
|
|
||||||
default_values["time"] = 0.0
|
|
||||||
dfdefault = dfdefault.append(default_values, ignore_index=True)
|
|
||||||
|
|
||||||
# Database with both types of defaults only
|
|
||||||
return dfdefault
|
|
||||||
|
|
||||||
# ==================================================================================================
|
|
||||||
# C++ header generation
|
|
||||||
# ==================================================================================================
|
|
||||||
|
|
||||||
# The C++ header
|
|
||||||
def GetHeader(family):
|
|
||||||
return("""
|
|
||||||
// =================================================================================================
|
|
||||||
// This file is part of the CLBlast project. The project is licensed under Apache Version 2.0. This
|
|
||||||
// project loosely follows the Google C++ styleguide and uses a tab-size of two spaces and a max-
|
|
||||||
// width of 100 characters per line.
|
|
||||||
//
|
|
||||||
// Author(s):
|
|
||||||
// Database generator <database.py>
|
|
||||||
//
|
|
||||||
// This file populates the database with best-found tuning parameters for the '%s' kernels.
|
|
||||||
//
|
|
||||||
// =================================================================================================
|
|
||||||
|
|
||||||
namespace clblast {
|
|
||||||
// ================================================================================================="""
|
|
||||||
% family.title())
|
|
||||||
|
|
||||||
# The C++ footer
|
|
||||||
def GetFooter():
|
|
||||||
return("\n} // namespace clblast\n")
|
|
||||||
|
|
||||||
# The start of a new C++ precision entry
|
|
||||||
def GetPrecision(family, precision):
|
|
||||||
precisionstring = ""
|
|
||||||
if precision == "16":
|
|
||||||
precisionstring = "Half"
|
|
||||||
elif precision == "32":
|
|
||||||
precisionstring = "Single"
|
|
||||||
elif precision == "64":
|
|
||||||
precisionstring = "Double"
|
|
||||||
elif precision == "3232":
|
|
||||||
precisionstring = "ComplexSingle"
|
|
||||||
elif precision == "6464":
|
|
||||||
precisionstring = "ComplexDouble"
|
|
||||||
else:
|
|
||||||
print("[ERROR] Unknown precision")
|
|
||||||
sys.exit()
|
|
||||||
return("\n\nconst Database::DatabaseEntry Database::%s%s = {\n \"%s\", Precision::k%s, {\n"
|
|
||||||
% (family.title(), precisionstring, family.title(), precisionstring))
|
|
||||||
|
|
||||||
# The C++ device type and vendor
|
|
||||||
def GetDeviceVendor(vendor, devtype):
|
|
||||||
if vendor == VENDOR_DEFAULT and devtype == DEVICETYPE_DEFAULT:
|
|
||||||
return(" { // Default\n kDeviceType%s, \"%s\", {\n" % (devtype, vendor))
|
|
||||||
return(" { // %s %ss\n kDeviceType%s, \"%s\", {\n" % (vendor, devtype, devtype[0].upper() + devtype[1:], vendor))
|
|
||||||
|
|
||||||
# Prints the data to a C++ database
|
|
||||||
def PrintData(df, outputdir):
|
|
||||||
|
|
||||||
# Iterates over the kernel families: creates a new file per family
|
|
||||||
for family, dffamily in df.groupby(["kernel_family"]):
|
|
||||||
dffamily = dffamily.dropna(axis=1, how='all')
|
|
||||||
f = open(os.path.join(outputdir, family+'.hpp'), 'w+')
|
|
||||||
f.write(GetHeader(family))
|
|
||||||
|
|
||||||
# Loops over the different entries for this family and prints their headers
|
|
||||||
for precision, dfprecision in dffamily.groupby(["precision"]):
|
|
||||||
f.write(GetPrecision(family, precision))
|
|
||||||
for vendor, dfvendor in dfprecision.groupby(["device_vendor"]):
|
|
||||||
for devtype, dfdevtype in dfvendor.groupby(["device_type"]):
|
|
||||||
f.write(GetDeviceVendor(vendor, devtype))
|
|
||||||
for device, dfdevice in dfdevtype.groupby(["device"]):
|
|
||||||
devicename = "\"%s\"," % device
|
|
||||||
f.write(" { %-50s { " % devicename)
|
|
||||||
|
|
||||||
# Collects the paramaters for this case and prints them
|
|
||||||
parameters = []
|
|
||||||
for kernel, dfkernel in dfdevice.groupby(["kernel"]):
|
|
||||||
dfkernel = dfkernel.dropna(axis=1)
|
|
||||||
col_names = [col for col in list(dfkernel) if col.startswith('parameters.') and col != "parameters.PRECISION"]
|
|
||||||
parameters += ["{\"%s\",%d}" % (p.replace("parameters.",""), dfkernel[p].iloc[0]) for p in col_names]
|
|
||||||
f.write(", ".join(parameters))
|
|
||||||
f.write(" } },\n")
|
|
||||||
|
|
||||||
# Prints the footers
|
|
||||||
f.write(" }\n },\n")
|
|
||||||
f.write(" }\n};\n\n// =================================================================================================")
|
|
||||||
f.write(GetFooter())
|
|
||||||
|
|
||||||
# ==================================================================================================
|
|
||||||
# Command-line arguments parsing and verification
|
|
||||||
# ==================================================================================================
|
|
||||||
|
|
||||||
# Checks for the number of command-line arguments
|
|
||||||
if len(sys.argv) != 3:
|
|
||||||
print("[ERROR] Usage: database.py <folder_with_json_files> <root_of_clblast>")
|
|
||||||
sys.exit()
|
|
||||||
|
|
||||||
# Parses the command-line arguments
|
# Parses the command-line arguments
|
||||||
path_json = sys.argv[1]
|
parser = argparse.ArgumentParser()
|
||||||
path_clblast = sys.argv[2]
|
parser.add_argument("source_folder", help="The folder with JSON files to parse to add to the database")
|
||||||
file_db = os.path.join(path_clblast, "scripts", "database", "database.db")
|
parser.add_argument("clblast_root", help="Root of the CLBlast sources")
|
||||||
glob_json = os.path.join(path_json, "*.json")
|
parser.add_argument("-v", "--verbose", action="store_true", help="Increase verbosity of the script")
|
||||||
|
cl_args = parser.parse_args(argv)
|
||||||
|
|
||||||
# Checks whether the command-line arguments are valid; exists otherwise
|
# Parses the path arguments
|
||||||
clblast_h = os.path.join(path_clblast, "include", "clblast.h") # Not used but just for validation
|
database_filename = os.path.join(cl_args.clblast_root, "scripts", "database", "database.json")
|
||||||
if not os.path.isfile(clblast_h):
|
database_best_filename = os.path.join(cl_args.clblast_root, "scripts", "database", "database_best.json")
|
||||||
print("[ERROR] The path '"+path_clblast+"' does not point to the root of the CLBlast library")
|
json_files = os.path.join(cl_args.source_folder, "*.json")
|
||||||
sys.exit()
|
cpp_database_path = os.path.join(cl_args.clblast_root, "src", "database", "kernels")
|
||||||
if len(glob.glob(glob_json)) < 1:
|
|
||||||
print("## The path '"+path_json+"' does not contain any JSON files")
|
|
||||||
|
|
||||||
# ==================================================================================================
|
# Checks whether the command-line arguments are valid
|
||||||
# The main body of the script
|
clblast_header = os.path.join(cl_args.clblast_root, "include", "clblast.h") # Not used but just for validation
|
||||||
# ==================================================================================================
|
if not os.path.isfile(clblast_header):
|
||||||
|
raise RuntimeError("The path '" + cl_args.clblast_root + "' does not point to the root of the CLBlast library")
|
||||||
|
if len(glob.glob(json_files)) < 1:
|
||||||
|
print("[database] The path '" + cl_args.source_folder + "' does not contain any JSON files")
|
||||||
|
|
||||||
# Downloads the database if a local copy is not present
|
# Downloads the database if a local copy is not present
|
||||||
db_exists = os.path.isfile(file_db)
|
if not os.path.isfile(database_filename):
|
||||||
if not db_exists:
|
io.download_database(database_filename, DATABASE_SERVER_URL)
|
||||||
DownloadDatabase(file_db)
|
|
||||||
|
|
||||||
# Loads the database from disk
|
# Loads the database from disk
|
||||||
print("## Loading the database from disk...")
|
database = io.load_database(database_filename)
|
||||||
database = LoadDatabase(file_db)
|
|
||||||
|
|
||||||
# Loops over all JSON files in the supplied folder
|
# Loops over all JSON files in the supplied folder
|
||||||
for file_json in glob.glob(glob_json):
|
for file_json in glob.glob(json_files):
|
||||||
|
|
||||||
# Loads the newly imported data
|
# Loads the newly imported data
|
||||||
sys.stdout.write("## Processing '"+file_json+"' ")
|
sys.stdout.write("[database] Processing '" + file_json + "' ") # No newline printed
|
||||||
imported_data = ImportDataFromFile(file_json)
|
imported_data = io.load_tuning_results(file_json)
|
||||||
imported_data = SanitizeVendorNames(imported_data)
|
|
||||||
|
# Fixes the problem that some vendors use multiple different names
|
||||||
|
for target in VENDOR_TRANSLATION_TABLE:
|
||||||
|
if imported_data["device_vendor"] == target:
|
||||||
|
imported_data["device_vendor"] = VENDOR_TRANSLATION_TABLE[target]
|
||||||
|
|
||||||
# Adds the new data to the database
|
# Adds the new data to the database
|
||||||
old_size = len(database.index)
|
old_size = db.length(database)
|
||||||
database = ConcatenateData(database, imported_data)
|
database = db.add_section(database, imported_data)
|
||||||
database = RemoveDuplicates(database)
|
new_size = db.length(database)
|
||||||
new_size = len(database.index)
|
print("with " + str(new_size - old_size) + " new items") # Newline printed here
|
||||||
print("with "+str(new_size-old_size)+" new items")
|
|
||||||
|
|
||||||
# Stores the modified database back to disk
|
# Stores the modified database back to disk
|
||||||
if len(glob.glob(glob_json)) >= 1:
|
if len(glob.glob(json_files)) >= 1:
|
||||||
print("## Storing the database to disk...")
|
io.save_database(database, database_filename)
|
||||||
SaveDatabase(database, file_db)
|
|
||||||
|
|
||||||
# Optional: update the database here. Default is disabled, code below is just an example
|
|
||||||
if False:
|
|
||||||
database = UpdateDatabase(database, ((database["kernel"] == "CopyMatrixFast") & (database["precision"] == "3232")), "arg_alpha", "2+0.5i")
|
|
||||||
SaveDatabase(database, file_db)
|
|
||||||
|
|
||||||
# Retrieves the best performing results
|
# Retrieves the best performing results
|
||||||
print("## Calculating the best results per device/kernel...")
|
print("[database] Calculating the best results per device/kernel...")
|
||||||
bests = GetBestResults(database)
|
database_best_results = bests.get_best_results(database)
|
||||||
|
|
||||||
# Determines the defaults for other vendors and per vendor
|
# Determines the defaults for other vendors and per vendor
|
||||||
defaults = CalculateDefaults(bests)
|
print("[database] Calculating the default values...")
|
||||||
bests = ConcatenateData(bests, defaults)
|
database_defaults = defaults.calculate_defaults(database, cl_args.verbose)
|
||||||
|
database_best_results["sections"].extend(database_defaults["sections"])
|
||||||
|
|
||||||
# Outputs the data as a C++ database
|
# Optionally outputs the database to disk
|
||||||
path_cpp_database = os.path.join(path_clblast, "src", "database", "kernels")
|
if cl_args.verbose:
|
||||||
print("## Producing a C++ database in '"+path_cpp_database+"'...")
|
io.save_database(database_best_results, database_best_filename)
|
||||||
PrintData(bests, path_cpp_database)
|
|
||||||
|
|
||||||
print("## All done")
|
# Outputs the database as a C++ database
|
||||||
|
print("[database] Producing a C++ database in '" + cpp_database_path + "'...")
|
||||||
|
clblast.print_cpp_database(database_best_results, cpp_database_path)
|
||||||
|
|
||||||
# ==================================================================================================
|
print("[database] All done")
|
||||||
|
|
||||||
|
|
||||||
|
if __name__ == '__main__':
|
||||||
|
main(sys.argv[1:])
|
||||||
|
|
0
scripts/database/database/__init__.py
Normal file
0
scripts/database/database/__init__.py
Normal file
58
scripts/database/database/bests.py
Normal file
58
scripts/database/database/bests.py
Normal file
|
@ -0,0 +1,58 @@
|
||||||
|
|
||||||
|
# This file is part of the CLBlast project. The project is licensed under Apache Version 2.0. This file follows the
|
||||||
|
# PEP8 Python style guide and uses a max-width of 120 characters per line.
|
||||||
|
#
|
||||||
|
# Author(s):
|
||||||
|
# Cedric Nugteren <www.cedricnugteren.nl>
|
||||||
|
|
||||||
|
import sys
|
||||||
|
|
||||||
|
|
||||||
|
def get_best_results(database):
|
||||||
|
"""Retrieves the results with the lowest execution times"""
|
||||||
|
sections_best = []
|
||||||
|
for section in database["sections"]:
|
||||||
|
section_best = {}
|
||||||
|
|
||||||
|
# Stores all the section's meta data
|
||||||
|
for attribute in section.keys():
|
||||||
|
if attribute != "results":
|
||||||
|
section_best[attribute] = section[attribute]
|
||||||
|
|
||||||
|
# Find the best result
|
||||||
|
parameters_best = None
|
||||||
|
time_best = sys.float_info.max
|
||||||
|
for result in section["results"]:
|
||||||
|
if result["time"] < time_best:
|
||||||
|
time_best = result["time"]
|
||||||
|
parameters_best = result["parameters"]
|
||||||
|
|
||||||
|
# Stores the best result
|
||||||
|
section_best["results"] = [{"time": time_best, "parameters": parameters_best}]
|
||||||
|
sections_best.append(section_best)
|
||||||
|
|
||||||
|
return {"sections": sections_best}
|
||||||
|
|
||||||
|
|
||||||
|
def get_relative_bests(name, common_results, common_parameters, verbose=False):
|
||||||
|
"""Retrieves the parameters with the relative best execution time over different devices"""
|
||||||
|
|
||||||
|
# Helper function
|
||||||
|
def argmax(iterable):
|
||||||
|
return max(enumerate(iterable), key=lambda x: x[1])[0]
|
||||||
|
|
||||||
|
# Computes the sum of the execution times over the different devices
|
||||||
|
performance_sums = []
|
||||||
|
for parameters in common_parameters:
|
||||||
|
performance_sum = sum([r["relative_performance"] for r in common_results if r["parameters"] == parameters])
|
||||||
|
performance_sums.append(performance_sum)
|
||||||
|
|
||||||
|
# Retrieves the entry with the highest performance
|
||||||
|
best_index = argmax(performance_sums)
|
||||||
|
best_performance = performance_sums[best_index]
|
||||||
|
best_parameters = common_parameters[best_index]
|
||||||
|
|
||||||
|
# Completed, report and return the results
|
||||||
|
if verbose:
|
||||||
|
print("[database] " + str(name) + " with performance " + str(best_performance))
|
||||||
|
return best_parameters
|
155
scripts/database/database/clblast.py
Normal file
155
scripts/database/database/clblast.py
Normal file
|
@ -0,0 +1,155 @@
|
||||||
|
|
||||||
|
# This file is part of the CLBlast project. The project is licensed under Apache Version 2.0. This file follows the
|
||||||
|
# PEP8 Python style guide and uses a max-width of 120 characters per line.
|
||||||
|
#
|
||||||
|
# Author(s):
|
||||||
|
# Cedric Nugteren <www.cedricnugteren.nl>
|
||||||
|
|
||||||
|
import os
|
||||||
|
|
||||||
|
# Constants from the C++ code
|
||||||
|
VENDOR_DEFAULT = "default"
|
||||||
|
DEVICE_TYPE_DEFAULT = "All"
|
||||||
|
DEVICE_NAME_DEFAULT = "default"
|
||||||
|
|
||||||
|
# List of attributes
|
||||||
|
DEVICE_TYPE_ATTRIBUTES = ["device_vendor", "device_type"]
|
||||||
|
DEVICE_ATTRIBUTES = ["device", "device_core_clock", "device_compute_units"]
|
||||||
|
KERNEL_ATTRIBUTES = ["precision", "kernel_family"]
|
||||||
|
ARGUMENT_ATTRIBUTES = ["arg_m", "arg_n", "arg_k", "arg_alpha", "arg_beta"]
|
||||||
|
ATTRIBUTES = DEVICE_ATTRIBUTES + DEVICE_TYPE_ATTRIBUTES + KERNEL_ATTRIBUTES + ARGUMENT_ATTRIBUTES
|
||||||
|
GROUP_ATTRIBUTES = DEVICE_TYPE_ATTRIBUTES + KERNEL_ATTRIBUTES + ["kernel"] + ARGUMENT_ATTRIBUTES
|
||||||
|
|
||||||
|
|
||||||
|
def precision_to_string(precision):
|
||||||
|
"""Translates a precision number (represented as Python string) into a descriptive string"""
|
||||||
|
if precision == "16":
|
||||||
|
return "Half"
|
||||||
|
elif precision == "32":
|
||||||
|
return "Single"
|
||||||
|
elif precision == "64":
|
||||||
|
return "Double"
|
||||||
|
elif precision == "3232":
|
||||||
|
return "ComplexSingle"
|
||||||
|
elif precision == "6464":
|
||||||
|
return "ComplexDouble"
|
||||||
|
else:
|
||||||
|
raise("Unknown precision: " + precision)
|
||||||
|
|
||||||
|
|
||||||
|
def get_cpp_separator():
|
||||||
|
"""Retrieves a C++ comment separator"""
|
||||||
|
return "// ================================================================================================="
|
||||||
|
|
||||||
|
|
||||||
|
def get_cpp_header(family):
|
||||||
|
"""Retrieves the C++ header"""
|
||||||
|
return ("\n" + get_cpp_separator() + """
|
||||||
|
// This file is part of the CLBlast project. The project is licensed under Apache Version 2.0. This
|
||||||
|
// project loosely follows the Google C++ styleguide and uses a tab-size of two spaces and a max-
|
||||||
|
// width of 100 characters per line.
|
||||||
|
//
|
||||||
|
// Author(s):
|
||||||
|
// Database generator <database.py>
|
||||||
|
//
|
||||||
|
// This file populates the database with best-found tuning parameters for the '%s' kernels.
|
||||||
|
//\n"""
|
||||||
|
% family.title() + get_cpp_separator() + "\n\nnamespace clblast {\n" + get_cpp_separator())
|
||||||
|
|
||||||
|
|
||||||
|
def get_cpp_footer():
|
||||||
|
"""Retrieves the C++ footer"""
|
||||||
|
return "\n} // namespace clblast\n"
|
||||||
|
|
||||||
|
|
||||||
|
def get_cpp_precision(family, precision):
|
||||||
|
"""Retrieves the C++ code for the start of a new precision"""
|
||||||
|
precision_string = precision_to_string(precision)
|
||||||
|
camelcase_name = family.title().replace("_", "")
|
||||||
|
return("\n\nconst Database::DatabaseEntry Database::%s%s = {\n \"%s\", Precision::k%s, {\n"
|
||||||
|
% (camelcase_name, precision_string, camelcase_name, precision_string))
|
||||||
|
|
||||||
|
|
||||||
|
def get_cpp_device_vendor(vendor, device_type):
|
||||||
|
"""Retrieves the C++ code for the (default) vendor and device type"""
|
||||||
|
if vendor == VENDOR_DEFAULT and device_type == DEVICE_TYPE_DEFAULT:
|
||||||
|
return " { // Default\n kDeviceType%s, \"%s\", {\n" % (device_type, vendor)
|
||||||
|
device_type_caps = device_type[0].upper() + device_type[1:]
|
||||||
|
return " { // %s %ss\n kDeviceType%s, \"%s\", {\n" % (vendor, device_type, device_type_caps, vendor)
|
||||||
|
|
||||||
|
|
||||||
|
def print_cpp_database(database, output_dir):
|
||||||
|
"""Outputs the database as C++ code"""
|
||||||
|
|
||||||
|
# Iterates over the kernel families
|
||||||
|
kernel_families = sorted(set([s["kernel_family"] for s in database["sections"]]))
|
||||||
|
for family_name in kernel_families:
|
||||||
|
family_database = [s for s in database["sections"] if s["kernel_family"] == family_name]
|
||||||
|
|
||||||
|
# Opens a new file for each kernel family
|
||||||
|
full_path = os.path.join(output_dir, family_name + ".hpp")
|
||||||
|
with open(full_path, 'w+') as f:
|
||||||
|
f.write(get_cpp_header(family_name))
|
||||||
|
|
||||||
|
# Loops over the different precision (e.g. 16, 32, 3232, 64, 6464)
|
||||||
|
precisions = sorted(set([s["precision"] for s in database["sections"]])) # Based on full database
|
||||||
|
for precision in precisions:
|
||||||
|
precision_database = [s for s in family_database if s["precision"] == precision]
|
||||||
|
f.write(get_cpp_precision(family_name, precision))
|
||||||
|
|
||||||
|
# In case there is nothing found at all (e.g. 16-bit): continue as if this was a precision of 32 but
|
||||||
|
# with the defaults only
|
||||||
|
if len(precision_database) == 0:
|
||||||
|
print("[database] No results found for %s:%s, retrieving defaults from %s:32" %
|
||||||
|
(family_name, precision, family_name))
|
||||||
|
precision_database = [s for s in family_database if s["precision"] == "32"
|
||||||
|
and s["device_vendor"] == VENDOR_DEFAULT
|
||||||
|
and s["device_type"] == DEVICE_TYPE_DEFAULT
|
||||||
|
and s["device"] == DEVICE_NAME_DEFAULT]
|
||||||
|
|
||||||
|
# Loops over device vendors (e.g. AMD)
|
||||||
|
device_vendors = sorted(set([s["device_vendor"] for s in precision_database]))
|
||||||
|
for vendor in device_vendors:
|
||||||
|
vendor_database = [s for s in precision_database if s["device_vendor"] == vendor]
|
||||||
|
|
||||||
|
# Loops over device types (e.g. GPU)
|
||||||
|
device_types = sorted(set([s["device_type"] for s in vendor_database]))
|
||||||
|
for device_type in device_types:
|
||||||
|
type_database = [s for s in vendor_database if s["device_type"] == device_type]
|
||||||
|
f.write(get_cpp_device_vendor(vendor, device_type))
|
||||||
|
|
||||||
|
# Loops over every device of this vendor-type combination
|
||||||
|
devices = sorted(set([s["device"] for s in type_database]))
|
||||||
|
for device_name in devices:
|
||||||
|
device_database = [s for s in type_database if s["device"] == device_name]
|
||||||
|
device_name_quoted = "\"%s\"," % device_name
|
||||||
|
device_name_cpp = " { %-50s { " % device_name_quoted
|
||||||
|
f.write(device_name_cpp)
|
||||||
|
|
||||||
|
# Collects the parameters for this entry
|
||||||
|
parameters = []
|
||||||
|
kernels = sorted(set([s["kernel"] for s in device_database]))
|
||||||
|
for kernel in kernels:
|
||||||
|
kernel_database = [s for s in device_database if s["kernel"] == kernel]
|
||||||
|
|
||||||
|
assert len(kernel_database) == 1
|
||||||
|
results = kernel_database[0]["results"]
|
||||||
|
|
||||||
|
assert len(results) == 1
|
||||||
|
new_parameters = results[0]["parameters"]
|
||||||
|
for parameter_name in sorted(new_parameters):
|
||||||
|
parameter_value = new_parameters[parameter_name]
|
||||||
|
parameters.append("{\"" + parameter_name + "\"," + str(parameter_value) + "}")
|
||||||
|
|
||||||
|
# Prints the entry
|
||||||
|
f.write(", ".join(parameters))
|
||||||
|
f.write(" } },\n")
|
||||||
|
|
||||||
|
# Prints the vendor-type combination footer
|
||||||
|
f.write(" }\n },\n")
|
||||||
|
|
||||||
|
# Prints the precision footer
|
||||||
|
f.write(" }\n};\n\n" + get_cpp_separator())
|
||||||
|
|
||||||
|
# Prints the file footer
|
||||||
|
f.write(get_cpp_footer())
|
64
scripts/database/database/db.py
Normal file
64
scripts/database/database/db.py
Normal file
|
@ -0,0 +1,64 @@
|
||||||
|
|
||||||
|
# This file is part of the CLBlast project. The project is licensed under Apache Version 2.0. This file follows the
|
||||||
|
# PEP8 Python style guide and uses a max-width of 120 characters per line.
|
||||||
|
#
|
||||||
|
# Author(s):
|
||||||
|
# Cedric Nugteren <www.cedricnugteren.nl>
|
||||||
|
|
||||||
|
import clblast
|
||||||
|
|
||||||
|
|
||||||
|
def length(database):
|
||||||
|
"""Computes the total number of tuning entries"""
|
||||||
|
num_tuning_entries = 0
|
||||||
|
for section in database["sections"]:
|
||||||
|
num_tuning_entries += len(section["results"])
|
||||||
|
return num_tuning_entries
|
||||||
|
|
||||||
|
|
||||||
|
def add_section(database, new_section):
|
||||||
|
"""Adds a new section to the database"""
|
||||||
|
for old_section in database["sections"]:
|
||||||
|
|
||||||
|
# Verify whether the sections match
|
||||||
|
equal = True
|
||||||
|
for attribute in new_section.keys():
|
||||||
|
if attribute != "results":
|
||||||
|
if attribute not in old_section or new_section[attribute] != old_section[attribute]:
|
||||||
|
equal = False
|
||||||
|
break
|
||||||
|
|
||||||
|
# They match: append the new section's results to the corresponding entry in the database and return
|
||||||
|
if equal:
|
||||||
|
old_section["results"] = combine_results(old_section["results"], new_section["results"])
|
||||||
|
return database
|
||||||
|
|
||||||
|
# No match found: append the whole new section to the database
|
||||||
|
database["sections"].append(new_section)
|
||||||
|
return database
|
||||||
|
|
||||||
|
|
||||||
|
def combine_results(old_results, new_results):
|
||||||
|
"""Adds new results to the results JSON list"""
|
||||||
|
for new_result in new_results:
|
||||||
|
old_results = combine_result(old_results, new_result)
|
||||||
|
return old_results
|
||||||
|
|
||||||
|
|
||||||
|
def combine_result(old_results, new_result):
|
||||||
|
"""Adds a new result to the results JSON list; filters for duplicate entries and saves the best performing one"""
|
||||||
|
|
||||||
|
# Loops over all existing results to test for already existing entries with these parameters
|
||||||
|
for old_result in old_results:
|
||||||
|
|
||||||
|
# Verify whether the results match
|
||||||
|
equal = new_result["parameters"] == old_result["parameters"]
|
||||||
|
|
||||||
|
# They match: keep only the one with the minimum execution time
|
||||||
|
if equal:
|
||||||
|
old_result["time"] = min(old_result["time"], new_result["time"])
|
||||||
|
return old_results
|
||||||
|
|
||||||
|
# No match found: append a new result
|
||||||
|
old_results.append(new_result)
|
||||||
|
return old_results
|
180
scripts/database/database/defaults.py
Normal file
180
scripts/database/database/defaults.py
Normal file
|
@ -0,0 +1,180 @@
|
||||||
|
|
||||||
|
# This file is part of the CLBlast project. The project is licensed under Apache Version 2.0. This file follows the
|
||||||
|
# PEP8 Python style guide and uses a max-width of 120 characters per line.
|
||||||
|
#
|
||||||
|
# Author(s):
|
||||||
|
# Cedric Nugteren <www.cedricnugteren.nl>
|
||||||
|
|
||||||
|
|
||||||
|
import clblast
|
||||||
|
import bests
|
||||||
|
|
||||||
|
|
||||||
|
def set_default_device(section):
|
||||||
|
"""Sets the device name and parameters to some default values"""
|
||||||
|
section["device"] = clblast.DEVICE_NAME_DEFAULT
|
||||||
|
section["device_compute_units"] = 0
|
||||||
|
section["device_core_clock"] = 0
|
||||||
|
return section
|
||||||
|
|
||||||
|
|
||||||
|
def set_identifiers(database, group_by_attributes, identifier_name):
|
||||||
|
"""Sets a group-identifier based on a given set of attributes. Modifies the database but also returns a list of
|
||||||
|
unique identifiers."""
|
||||||
|
identifiers = []
|
||||||
|
for section in database["sections"]:
|
||||||
|
identifier = []
|
||||||
|
for attribute in group_by_attributes:
|
||||||
|
if attribute in section:
|
||||||
|
identifier.append(section[attribute])
|
||||||
|
section[identifier_name] = ";".join(identifier)
|
||||||
|
identifiers.append(section[identifier_name])
|
||||||
|
return sorted(set(identifiers))
|
||||||
|
|
||||||
|
|
||||||
|
def remove_identifiers(database, identifier_name):
|
||||||
|
"""Removes an identifier from all sections in the database"""
|
||||||
|
for section in database["sections"]:
|
||||||
|
section.pop(identifier_name, None)
|
||||||
|
|
||||||
|
|
||||||
|
def get_groups_by_identifier(database, group_identifiers, identifier_name):
|
||||||
|
"""Returns a list of (group, group_identifier) tuples based a previously made grouping"""
|
||||||
|
groups = []
|
||||||
|
for group_identifier in group_identifiers:
|
||||||
|
|
||||||
|
# Get all sections in this group
|
||||||
|
group = []
|
||||||
|
for section in database["sections"]:
|
||||||
|
if section[identifier_name] == group_identifier:
|
||||||
|
group.append(section)
|
||||||
|
|
||||||
|
groups.append((group, group_identifier))
|
||||||
|
return groups
|
||||||
|
|
||||||
|
|
||||||
|
def calculate_defaults(database, verbose):
|
||||||
|
"""Sets defaults for devices of the same type/vendor"""
|
||||||
|
|
||||||
|
# Groups the database by kernel, vendor and device type (e.g. AMD GPU)
|
||||||
|
group_identifiers = set_identifiers(database, clblast.GROUP_ATTRIBUTES, "group_identifier")
|
||||||
|
groups = get_groups_by_identifier(database, group_identifiers, "group_identifier")
|
||||||
|
|
||||||
|
# Loops over all groups
|
||||||
|
default_sections = {"sections": []}
|
||||||
|
for group, group_identifier in groups:
|
||||||
|
|
||||||
|
# Computes the best parameters
|
||||||
|
default_parameters = get_common_best_parameters(group, group_identifier, verbose)
|
||||||
|
|
||||||
|
# Stores all the section's data
|
||||||
|
assert len(group) > 0
|
||||||
|
default_section = {}
|
||||||
|
for attribute in group[0].keys():
|
||||||
|
if attribute != "results" and attribute != "group_identifier":
|
||||||
|
default_section[attribute] = group[0][attribute]
|
||||||
|
default_section = set_default_device(default_section)
|
||||||
|
default_section["results"] = [{"time": 0.0, "parameters": default_parameters}]
|
||||||
|
default_sections["sections"].append(default_section)
|
||||||
|
|
||||||
|
# Groups the database by kernel, vendor and device type (e.g. AMD GPU) - but not by arguments! This is to check for
|
||||||
|
# mis-matched arguments.
|
||||||
|
attributes = clblast.DEVICE_TYPE_ATTRIBUTES + clblast.KERNEL_ATTRIBUTES + ["kernel"]
|
||||||
|
group_identifiers = set_identifiers(default_sections, attributes, "temp_identifier")
|
||||||
|
groups = get_groups_by_identifier(default_sections, group_identifiers, "temp_identifier")
|
||||||
|
for group, group_identifier in groups:
|
||||||
|
if len(group) != 1:
|
||||||
|
print("[ERROR] Entries for a single kernel with multiple argument values: " + str(group_identifier))
|
||||||
|
assert len(group) == 1
|
||||||
|
remove_identifiers(default_sections, "temp_identifier")
|
||||||
|
|
||||||
|
# Groups the database by kernel only
|
||||||
|
group_identifiers = set_identifiers(database, clblast.KERNEL_ATTRIBUTES + ["kernel"], "group_identifier")
|
||||||
|
groups = get_groups_by_identifier(database, group_identifiers, "group_identifier")
|
||||||
|
|
||||||
|
# Loops over all groups
|
||||||
|
for group, group_identifier in groups:
|
||||||
|
|
||||||
|
# Computes the best parameters
|
||||||
|
default_parameters = get_common_best_parameters(group, group_identifier, verbose)
|
||||||
|
|
||||||
|
# Stores all the section's data
|
||||||
|
assert len(group) > 0
|
||||||
|
default_section = {}
|
||||||
|
for attribute in group[0].keys():
|
||||||
|
if attribute != "results" and attribute != "group_identifier":
|
||||||
|
default_section[attribute] = group[0][attribute]
|
||||||
|
default_section = set_default_device(default_section)
|
||||||
|
default_section["device_vendor"] = clblast.VENDOR_DEFAULT
|
||||||
|
default_section["device_type"] = clblast.DEVICE_TYPE_DEFAULT
|
||||||
|
default_section["results"] = [{"time": 0.0, "parameters": default_parameters}]
|
||||||
|
default_sections["sections"].append(default_section)
|
||||||
|
|
||||||
|
# Database with both types of defaults only
|
||||||
|
return default_sections
|
||||||
|
|
||||||
|
|
||||||
|
def get_smallest_best_parameters(group):
|
||||||
|
"""Sets defaults based on the smallest values of all known entries. The average might be better for performance but
|
||||||
|
some parameters might not be supported on other devices."""
|
||||||
|
|
||||||
|
# Counts the number of devices in this group
|
||||||
|
assert len(group) > 0
|
||||||
|
|
||||||
|
# Find the smallest values of the parameters
|
||||||
|
min_parameters = {}
|
||||||
|
for section in group:
|
||||||
|
assert len(section["results"]) > 0
|
||||||
|
minimum_time = min([result["time"] for result in section["results"]])
|
||||||
|
for result in section["results"]:
|
||||||
|
if result["time"] == minimum_time:
|
||||||
|
for parameter in result["parameters"]:
|
||||||
|
if parameter in min_parameters:
|
||||||
|
min_parameters[parameter] = min(min_parameters[parameter], result["parameters"][parameter])
|
||||||
|
else:
|
||||||
|
min_parameters[parameter] = result["parameters"][parameter]
|
||||||
|
|
||||||
|
return min_parameters
|
||||||
|
|
||||||
|
|
||||||
|
def get_common_best_parameters(group, group_identifier, verbose):
|
||||||
|
"""Sets defaults based on the best values of entries supported by all devices. This might cause a problem in case
|
||||||
|
not every device was tuned with the same parameters. In that case it falls back to the above method to retrieve
|
||||||
|
the smallest best execution time"""
|
||||||
|
|
||||||
|
# Counts the number of devices in this group
|
||||||
|
num_devices = len(group)
|
||||||
|
assert num_devices > 0
|
||||||
|
|
||||||
|
# Inserts the relative execution times into the database
|
||||||
|
for section in group:
|
||||||
|
assert len(section["results"]) > 0
|
||||||
|
minimum_time = min([result["time"] for result in section["results"]])
|
||||||
|
for result in section["results"]:
|
||||||
|
result["relative_performance"] = minimum_time / result["time"]
|
||||||
|
|
||||||
|
# Determine which parameters are available for all devices
|
||||||
|
common_parameters = [result["parameters"] for result in group[0]["results"]] # Parameters of the first section
|
||||||
|
for i in range(1, num_devices):
|
||||||
|
section_parameters = [result["parameters"] for result in group[i]["results"]]
|
||||||
|
common_parameters = [p for p in section_parameters if p in common_parameters] # Intersection of the parameters
|
||||||
|
|
||||||
|
# Fall back to another method in case there are no shared entries at all across devices
|
||||||
|
if len(common_parameters) == 0:
|
||||||
|
if verbose:
|
||||||
|
print("[database] No common kernels for: " + str(group_identifier) + " with devices: %d " % num_devices)
|
||||||
|
smallest_best_parameters = get_smallest_best_parameters(group)
|
||||||
|
if verbose:
|
||||||
|
print("[database] " + str(group_identifier))
|
||||||
|
return smallest_best_parameters
|
||||||
|
|
||||||
|
# Removes entries with parameters which are not common
|
||||||
|
common_results = []
|
||||||
|
for section in group:
|
||||||
|
for result in section["results"]:
|
||||||
|
if result["parameters"] in common_parameters:
|
||||||
|
common_results.append(result)
|
||||||
|
|
||||||
|
# Retrieves the entries with the highest relative performance
|
||||||
|
relative_best_parameters = bests.get_relative_bests(group_identifier, common_results, common_parameters, verbose)
|
||||||
|
return relative_best_parameters
|
60
scripts/database/database/io.py
Normal file
60
scripts/database/database/io.py
Normal file
|
@ -0,0 +1,60 @@
|
||||||
|
|
||||||
|
# This file is part of the CLBlast project. The project is licensed under Apache Version 2.0. This file follows the
|
||||||
|
# PEP8 Python style guide and uses a max-width of 120 characters per line.
|
||||||
|
#
|
||||||
|
# Author(s):
|
||||||
|
# Cedric Nugteren <www.cedricnugteren.nl>
|
||||||
|
|
||||||
|
import re
|
||||||
|
import json
|
||||||
|
|
||||||
|
try:
|
||||||
|
from urllib.request import urlopen # Python 3
|
||||||
|
except ImportError:
|
||||||
|
from urllib2 import urlopen # Python 2
|
||||||
|
|
||||||
|
|
||||||
|
def download_database(filename, database_url):
|
||||||
|
"""Downloads a database and saves it to disk"""
|
||||||
|
print("[database] Downloading database from '" + database_url + "'...")
|
||||||
|
database = urlopen(database_url)
|
||||||
|
with open(filename, "wb") as f:
|
||||||
|
f.write(database.read())
|
||||||
|
|
||||||
|
|
||||||
|
def load_database(filename):
|
||||||
|
"""Loads a database from disk"""
|
||||||
|
print("[database] Loading database from '" + filename + "'")
|
||||||
|
with open(filename) as f:
|
||||||
|
return json.load(f)
|
||||||
|
|
||||||
|
|
||||||
|
def save_database(database, filename):
|
||||||
|
"""Saves a database to disk"""
|
||||||
|
print("[database] Saving database to '" + filename + "'")
|
||||||
|
with open(filename, "wb") as f:
|
||||||
|
json.dump(database, f, sort_keys=True, indent=4)
|
||||||
|
|
||||||
|
|
||||||
|
def load_tuning_results(filename):
|
||||||
|
"""Loads JSON data from file and pre-processes it"""
|
||||||
|
with open(filename) as f:
|
||||||
|
json_data = json.load(f)
|
||||||
|
|
||||||
|
# Removes the numbering following the kernel family name
|
||||||
|
json_data["kernel_family"] = re.sub(r'_\d+', '', json_data["kernel_family"])
|
||||||
|
|
||||||
|
# Adds the kernel name to the section instead of to the individual results
|
||||||
|
assert len(json_data["results"]) > 0
|
||||||
|
json_data["kernel"] = json_data["results"][0]["kernel"]
|
||||||
|
for result in json_data["results"]:
|
||||||
|
assert json_data["kernel"] == result["kernel"]
|
||||||
|
result.pop("kernel", None)
|
||||||
|
|
||||||
|
# Removes the 'PRECISION' parameter from the individual results: it is redundant
|
||||||
|
for result in json_data["results"]:
|
||||||
|
assert json_data["precision"] == str(result["parameters"]["PRECISION"])
|
||||||
|
result["parameters"].pop("PRECISION", None)
|
||||||
|
|
||||||
|
# All done
|
||||||
|
return json_data
|
|
@ -1,70 +0,0 @@
|
||||||
#!/usr/bin/env python
|
|
||||||
|
|
||||||
# ==================================================================================================
|
|
||||||
# This file is part of the CLBlast project. The project is licensed under Apache Version 2.0. This
|
|
||||||
# project loosely follows the Google C++ styleguide and uses a max-width of 100 characters per line.
|
|
||||||
#
|
|
||||||
# Author(s):
|
|
||||||
# Cedric Nugteren <www.cedricnugteren.nl>
|
|
||||||
#
|
|
||||||
# This file contains the 'DataType' class, used in the generator script to generate the CLBlast API
|
|
||||||
# interface and implementation.
|
|
||||||
#
|
|
||||||
# ==================================================================================================
|
|
||||||
|
|
||||||
# Short-hands for data-types
|
|
||||||
HLF = "half"
|
|
||||||
FLT = "float"
|
|
||||||
DBL = "double"
|
|
||||||
FLT2 = "float2"
|
|
||||||
DBL2 = "double2"
|
|
||||||
|
|
||||||
HCL = "cl_half"
|
|
||||||
F2CL = "cl_float2"
|
|
||||||
D2CL = "cl_double2"
|
|
||||||
|
|
||||||
# Structure holding data-type and precision information
|
|
||||||
class DataType():
|
|
||||||
def __init__(self, precision_name, name, template, scalars, buffertype):
|
|
||||||
self.precision_name = precision_name
|
|
||||||
self.name = name
|
|
||||||
self.template = template
|
|
||||||
self.alpha_cpp = scalars[0]
|
|
||||||
self.beta_cpp = scalars[1]
|
|
||||||
self.alpha_cl = scalars[2]
|
|
||||||
self.beta_cl = scalars[3]
|
|
||||||
self.buffertype = buffertype
|
|
||||||
|
|
||||||
# Outputs the name of the data-type (alpha/beta), possibly transforming into the right type
|
|
||||||
def UseAlpha(self):
|
|
||||||
if self.alpha_cpp in [FLT2, DBL2]:
|
|
||||||
return self.alpha_cpp+"{alpha.s[0], alpha.s[1]}"
|
|
||||||
return "alpha"
|
|
||||||
def UseBeta(self):
|
|
||||||
if self.beta_cpp in [FLT2, DBL2]:
|
|
||||||
return self.beta_cpp+"{beta.s[0], beta.s[1]}"
|
|
||||||
return "beta"
|
|
||||||
|
|
||||||
# As above, but the transformation is in the opposite direction
|
|
||||||
def UseAlphaCL(self):
|
|
||||||
if self.alpha_cpp in [FLT2, DBL2]:
|
|
||||||
return self.alpha_cl+"{{alpha.real(), alpha.imag()}}"
|
|
||||||
return "alpha"
|
|
||||||
def UseBetaCL(self):
|
|
||||||
if self.beta_cpp in [FLT2, DBL2]:
|
|
||||||
return self.beta_cl+"{{beta.real(), beta.imag()}}"
|
|
||||||
return "beta"
|
|
||||||
|
|
||||||
# Returns the template as used in the correctness/performance tests
|
|
||||||
def TestTemplate(self):
|
|
||||||
if self.buffertype != self.beta_cpp:
|
|
||||||
return "<"+self.buffertype+","+self.beta_cpp+">, "+self.buffertype+", "+self.beta_cpp
|
|
||||||
return "<"+self.buffertype+">, "+self.buffertype+", "+self.beta_cpp
|
|
||||||
|
|
||||||
# Current scalar is complex
|
|
||||||
def IsComplex(self, scalar):
|
|
||||||
return ((scalar == "alpha" and self.alpha_cpp in [FLT2, DBL2]) or
|
|
||||||
(scalar == "beta" and self.beta_cpp in [FLT2, DBL2]))
|
|
||||||
|
|
||||||
|
|
||||||
# ==================================================================================================
|
|
|
@ -1,14 +1,13 @@
|
||||||
#!/usr/bin/env python
|
#!/usr/bin/env python
|
||||||
|
|
||||||
# ==================================================================================================
|
# This file is part of the CLBlast project. The project is licensed under Apache Version 2.0. This file follows the
|
||||||
# This file is part of the CLBlast project. The project is licensed under Apache Version 2.0. This
|
# PEP8 Python style guide and uses a max-width of 120 characters per line.
|
||||||
# project loosely follows the Google C++ styleguide and uses a max-width of 100 characters per line.
|
|
||||||
#
|
#
|
||||||
# Author(s):
|
# Author(s):
|
||||||
# Cedric Nugteren <www.cedricnugteren.nl>
|
# Cedric Nugteren <www.cedricnugteren.nl>
|
||||||
#
|
#
|
||||||
# This script automatically generates the bodies of the following files, creating the full CLBlast
|
# This script automatically generates the bodies of the following files, creating the full CLBlast API interface and
|
||||||
# API interface and implementation (C, C++, and reference BLAS wrappers):
|
# implementation (C, C++, and reference BLAS wrappers):
|
||||||
# clblast.h
|
# clblast.h
|
||||||
# clblast.cpp
|
# clblast.cpp
|
||||||
# clblast_c.h
|
# clblast_c.h
|
||||||
|
@ -19,45 +18,20 @@
|
||||||
# test/correctness/routines/levelX/xYYYY.cpp
|
# test/correctness/routines/levelX/xYYYY.cpp
|
||||||
# test/performance/routines/levelX/xYYYY.cpp
|
# test/performance/routines/levelX/xYYYY.cpp
|
||||||
# It also produces the API documentation found in doc/clblast.md
|
# It also produces the API documentation found in doc/clblast.md
|
||||||
#
|
|
||||||
# ==================================================================================================
|
|
||||||
|
|
||||||
# System modules
|
|
||||||
import sys
|
import sys
|
||||||
import os.path
|
import os.path
|
||||||
|
import argparse
|
||||||
|
|
||||||
# Local files
|
import generator.cpp as cpp
|
||||||
from routine import Routine
|
import generator.doc as doc
|
||||||
from datatype import DataType, HLF, FLT, DBL, FLT2, DBL2, HCL, F2CL, D2CL
|
from generator.routine import Routine
|
||||||
|
from generator.datatype import H, S, D, C, Z, Sc, Dz, iH, iS, iD, iC, iZ, Css, Zdd, Ccs, Zzd, T, Tc, TU
|
||||||
|
|
||||||
# ==================================================================================================
|
|
||||||
|
|
||||||
# Regular data-types
|
HEADER_LINES = [96, 73, 97, 22, 29, 41]
|
||||||
H = DataType("H", "H", HLF, [HLF, HLF, HCL, HCL], HLF ) # half (16)
|
FOOTER_LINES = [17, 75, 19, 14, 6, 6]
|
||||||
S = DataType("S", "S", FLT, [FLT, FLT, FLT, FLT], FLT ) # single (32)
|
|
||||||
D = DataType("D", "D", DBL, [DBL, DBL, DBL, DBL], DBL ) # double (64)
|
|
||||||
C = DataType("C", "C", FLT2, [FLT2, FLT2, F2CL, F2CL], FLT2) # single-complex (3232)
|
|
||||||
Z = DataType("Z", "Z", DBL2, [DBL2, DBL2, D2CL, D2CL], DBL2) # double-complex (6464)
|
|
||||||
|
|
||||||
# Special cases
|
|
||||||
Sc = DataType("C", "Sc", FLT2, [FLT2, FLT2, FLT2, FLT2], FLT2) # As C, but with real output
|
|
||||||
Dz = DataType("Z", "Dz", DBL2, [DBL2, DBL2, DBL2, DBL2], DBL2) # As Z, but with real output
|
|
||||||
iH = DataType("H", "iH", HLF, [HLF, HLF, HLF, HLF], HLF ) # As H, but with integer output
|
|
||||||
iS = DataType("S", "iS", FLT, [FLT, FLT, FLT, FLT], FLT ) # As S, but with integer output
|
|
||||||
iD = DataType("D", "iD", DBL, [DBL, DBL, DBL, DBL], DBL ) # As D, but with integer output
|
|
||||||
iC = DataType("C", "iC", FLT2, [FLT2, FLT2, F2CL, F2CL], FLT2) # As C, but with integer output
|
|
||||||
iZ = DataType("Z", "iZ", DBL2, [DBL2, DBL2, D2CL, D2CL], DBL2) # As Z, but with integer output
|
|
||||||
Css = DataType("C", "C", FLT, [FLT, FLT, FLT, FLT], FLT2) # As C, but with constants from S
|
|
||||||
Zdd = DataType("Z", "Z", DBL, [DBL, DBL, DBL, DBL], DBL2) # As Z, but with constants from D
|
|
||||||
Ccs = DataType("C", "C", FLT2+","+FLT, [FLT2, FLT, F2CL, FLT], FLT2) # As C, but with one constant from S
|
|
||||||
Zzd = DataType("Z", "Z", DBL2+","+DBL, [DBL2, DBL, D2CL, DBL], DBL2) # As Z, but with one constant from D
|
|
||||||
|
|
||||||
# C++ template data-types
|
|
||||||
T = DataType("T", "typename T", "T", ["T", "T", "T", "T"], "T") # regular routine
|
|
||||||
Tc = DataType("Tc", "typename T", "std::complex<T>,T", ["T", "T", "T", "T"], "std::complex<T>") # for herk
|
|
||||||
TU = DataType("TU", "typename T, typename U", "T,U", ["T", "U", "T", "U"], "T") # for her2k
|
|
||||||
|
|
||||||
# ==================================================================================================
|
|
||||||
|
|
||||||
# Different possibilities for requirements
|
# Different possibilities for requirements
|
||||||
ald_m = "The value of `a_ld` must be at least `m`."
|
ald_m = "The value of `a_ld` must be at least `m`."
|
||||||
|
@ -77,7 +51,7 @@ cld_n = "The value of `c_ld` must be at least `n`."
|
||||||
# ==================================================================================================
|
# ==================================================================================================
|
||||||
|
|
||||||
# Populates a list of routines
|
# Populates a list of routines
|
||||||
routines = [
|
ROUTINES = [
|
||||||
[ # Level 1: vector-vector
|
[ # Level 1: vector-vector
|
||||||
Routine(False, True, "1", "rotg", T, [S,D], [], [], [], ["sa","sb","sc","ss"], [], "", "Generate givens plane rotation", "", []),
|
Routine(False, True, "1", "rotg", T, [S,D], [], [], [], ["sa","sb","sc","ss"], [], "", "Generate givens plane rotation", "", []),
|
||||||
Routine(False, True, "1", "rotmg", T, [S,D], [], [], ["sy1"], ["sd1","sd2","sx1","sparam"], [], "", "Generate modified givens plane rotation", "", []),
|
Routine(False, True, "1", "rotmg", T, [S,D], [], [], ["sy1"], ["sd1","sd2","sx1","sparam"], [], "", "Generate modified givens plane rotation", "", []),
|
||||||
|
@ -140,409 +114,99 @@ routines = [
|
||||||
Routine(True, True, "x", "omatcopy", T, [S,D,C,Z,H], ["m","n"], ["layout","a_transpose"], ["a"], ["b"], ["alpha"], "", "Scaling and out-place transpose/copy (non-BLAS function)", "Performs scaling and out-of-place transposition/copying of matrices according to _B = alpha*op(A)_, in which _A_ is an input matrix (_m_ rows by _n_ columns), _B_ an output matrix, and _alpha_ a scalar value. The operation _op_ can be a normal matrix copy, a transposition or a conjugate transposition.", [ald_m, bld_n]),
|
Routine(True, True, "x", "omatcopy", T, [S,D,C,Z,H], ["m","n"], ["layout","a_transpose"], ["a"], ["b"], ["alpha"], "", "Scaling and out-place transpose/copy (non-BLAS function)", "Performs scaling and out-of-place transposition/copying of matrices according to _B = alpha*op(A)_, in which _A_ is an input matrix (_m_ rows by _n_ columns), _B_ an output matrix, and _alpha_ a scalar value. The operation _op_ can be a normal matrix copy, a transposition or a conjugate transposition.", [ald_m, bld_n]),
|
||||||
]]
|
]]
|
||||||
|
|
||||||
# ==================================================================================================
|
|
||||||
# Translates an option name to a CLBlast data-type
|
|
||||||
def PrecisionToFullName(x):
|
|
||||||
return {
|
|
||||||
'H': "Half",
|
|
||||||
'S': "Single",
|
|
||||||
'D': "Double",
|
|
||||||
'C': "ComplexSingle",
|
|
||||||
'Z': "ComplexDouble",
|
|
||||||
}[x]
|
|
||||||
|
|
||||||
# ==================================================================================================
|
def main(argv):
|
||||||
|
|
||||||
# Separators for the BLAS levels
|
|
||||||
separators = ["""
|
|
||||||
// =================================================================================================
|
|
||||||
// BLAS level-1 (vector-vector) routines
|
|
||||||
// =================================================================================================""",
|
|
||||||
"""
|
|
||||||
// =================================================================================================
|
|
||||||
// BLAS level-2 (matrix-vector) routines
|
|
||||||
// =================================================================================================""",
|
|
||||||
"""
|
|
||||||
// =================================================================================================
|
|
||||||
// BLAS level-3 (matrix-matrix) routines
|
|
||||||
// =================================================================================================""",
|
|
||||||
"""
|
|
||||||
// =================================================================================================
|
|
||||||
// Extra non-BLAS routines (level-X)
|
|
||||||
// ================================================================================================="""]
|
|
||||||
|
|
||||||
# Names of the level sub-folders
|
|
||||||
levelnames = ["1", "2", "3", "x"]
|
|
||||||
|
|
||||||
# Main header/footer for source files
|
|
||||||
header = """
|
|
||||||
// =================================================================================================
|
|
||||||
// This file is part of the CLBlast project. The project is licensed under Apache Version 2.0. This
|
|
||||||
// project loosely follows the Google C++ styleguide and uses a tab-size of two spaces and a max-
|
|
||||||
// width of 100 characters per line.
|
|
||||||
//
|
|
||||||
// Author(s):
|
|
||||||
// Cedric Nugteren <www.cedricnugteren.nl>
|
|
||||||
//
|
|
||||||
// =================================================================================================
|
|
||||||
"""
|
|
||||||
footer = """
|
|
||||||
// =================================================================================================
|
|
||||||
"""
|
|
||||||
|
|
||||||
# ==================================================================================================
|
|
||||||
|
|
||||||
# The C++ API header (.h)
|
|
||||||
def clblast_h(routines):
|
|
||||||
result = ""
|
|
||||||
for routine in routines:
|
|
||||||
result += "\n// "+routine.description+": "+routine.ShortNames()+"\n"
|
|
||||||
result += routine.RoutineHeaderCPP(12, " = nullptr")+";\n"
|
|
||||||
return result
|
|
||||||
|
|
||||||
# The C++ API implementation (.cpp)
|
|
||||||
def clblast_cc(routines):
|
|
||||||
result = ""
|
|
||||||
for routine in routines:
|
|
||||||
indent1 = " "*(20 + routine.Length())
|
|
||||||
result += "\n// "+routine.description+": "+routine.ShortNames()+"\n"
|
|
||||||
if routine.implemented:
|
|
||||||
result += routine.RoutineHeaderCPP(12, "")+" {\n"
|
|
||||||
result += " auto queue_cpp = Queue(*queue);\n"
|
|
||||||
result += " auto routine = X"+routine.name+"<"+routine.template.template+">(queue_cpp, event);\n"
|
|
||||||
result += " auto status = routine.SetUp();\n"
|
|
||||||
result += " if (status != StatusCode::kSuccess) { return status; }\n"
|
|
||||||
result += " return routine.Do"+routine.name.capitalize()+"("
|
|
||||||
result += (",\n"+indent1).join([a for a in routine.ArgumentsCladuc(routine.template, indent1)])
|
|
||||||
result += ");\n"
|
|
||||||
else:
|
|
||||||
result += routine.RoutineHeaderTypeCPP(12)+" {\n"
|
|
||||||
result += " return StatusCode::kNotImplemented;\n"
|
|
||||||
result += "}\n"
|
|
||||||
for flavour in routine.flavours:
|
|
||||||
indent2 = " "*(34 + routine.Length() + len(flavour.template))
|
|
||||||
result += "template StatusCode PUBLIC_API "+routine.name.capitalize()+"<"+flavour.template+">("
|
|
||||||
result += (",\n"+indent2).join([a for a in routine.ArgumentsType(flavour)])
|
|
||||||
result += ",\n"+indent2+"cl_command_queue*, cl_event*);\n"
|
|
||||||
return result
|
|
||||||
|
|
||||||
# ==================================================================================================
|
|
||||||
|
|
||||||
# The C API header (.h)
|
|
||||||
def clblast_c_h(routines):
|
|
||||||
result = ""
|
|
||||||
for routine in routines:
|
|
||||||
result += "\n// "+routine.description+": "+routine.ShortNames()+"\n"
|
|
||||||
for flavour in routine.flavours:
|
|
||||||
result += routine.RoutineHeaderC(flavour, 31, " PUBLIC_API")+";\n"
|
|
||||||
return result
|
|
||||||
|
|
||||||
# The C API implementation (.cpp)
|
|
||||||
def clblast_c_cc(routines):
|
|
||||||
result = ""
|
|
||||||
for routine in routines:
|
|
||||||
result += "\n// "+routine.name.upper()+"\n"
|
|
||||||
for flavour in routine.flavours:
|
|
||||||
template = "<"+flavour.template+">" if routine.NoScalars() else ""
|
|
||||||
indent = " "*(26 + routine.Length() + len(template))
|
|
||||||
result += routine.RoutineHeaderC(flavour, 20, "")+" {\n"
|
|
||||||
result += " auto status = clblast::"+routine.name.capitalize()+template+"("
|
|
||||||
result += (",\n"+indent).join([a for a in routine.ArgumentsCast(flavour, indent)])
|
|
||||||
result += ",\n"+indent+"queue, event);"
|
|
||||||
result += "\n return static_cast<StatusCode>(status);\n}\n"
|
|
||||||
return result
|
|
||||||
|
|
||||||
# ==================================================================================================
|
|
||||||
|
|
||||||
# The wrapper to the reference clBLAS routines (for performance/correctness testing)
|
|
||||||
def wrapper_clblas(routines):
|
|
||||||
result = ""
|
|
||||||
for routine in routines:
|
|
||||||
if routine.has_tests:
|
|
||||||
result += "\n// Forwards the clBLAS calls for %s\n" % (routine.ShortNamesTested())
|
|
||||||
if routine.NoScalars():
|
|
||||||
result += routine.RoutineHeaderWrapperCL(routine.template, True, 21)+";\n"
|
|
||||||
for flavour in routine.flavours:
|
|
||||||
result += routine.RoutineHeaderWrapperCL(flavour, False, 21)+" {\n"
|
|
||||||
|
|
||||||
# There is a version available in clBLAS
|
|
||||||
if flavour.precision_name in ["S","D","C","Z"]:
|
|
||||||
indent = " "*(17 + routine.Length())
|
|
||||||
arguments = routine.ArgumentsWrapperCL(flavour)
|
|
||||||
if routine.scratch:
|
|
||||||
result += " auto queue = Queue(queues[0]);\n"
|
|
||||||
result += " auto context = queue.GetContext();\n"
|
|
||||||
result += " auto scratch_buffer = Buffer<"+flavour.template+">(context, "+routine.scratch+");\n"
|
|
||||||
arguments += ["scratch_buffer()"]
|
|
||||||
result += " return clblas"+flavour.name+routine.name+"("
|
|
||||||
result += (",\n"+indent).join([a for a in arguments])
|
|
||||||
result += ",\n"+indent+"num_queues, queues, num_wait_events, wait_events, events);"
|
|
||||||
|
|
||||||
# There is no clBLAS available, forward the call to one of the available functions
|
|
||||||
else: # Half-precision
|
|
||||||
indent = " "*(24 + routine.Length())
|
|
||||||
|
|
||||||
# Convert to float (note: also integer buffers are stored as half/float)
|
|
||||||
for buf in routine.inputs + routine.outputs:
|
|
||||||
result += " auto "+buf+"_buffer_bis = HalfToFloatBuffer("+buf+"_buffer, queues[0]);\n"
|
|
||||||
|
|
||||||
# Call the float routine
|
|
||||||
result += " auto status = clblasX"+routine.name+"("
|
|
||||||
result += (",\n"+indent).join([a for a in routine.ArgumentsHalf()])
|
|
||||||
result += ",\n"+indent+"num_queues, queues, num_wait_events, wait_events, events);"
|
|
||||||
result += "\n"
|
|
||||||
|
|
||||||
# Convert back to half
|
|
||||||
for buf in routine.outputs:
|
|
||||||
result += " FloatToHalfBuffer("+buf+"_buffer, "+buf+"_buffer_bis, queues[0]);\n"
|
|
||||||
result += " return status;"
|
|
||||||
|
|
||||||
# Complete
|
|
||||||
result += "\n}\n"
|
|
||||||
return result
|
|
||||||
|
|
||||||
# The wrapper to the reference CBLAS routines (for performance/correctness testing)
|
|
||||||
def wrapper_cblas(routines):
|
|
||||||
result = ""
|
|
||||||
for routine in routines:
|
|
||||||
if routine.has_tests:
|
|
||||||
result += "\n// Forwards the Netlib BLAS calls for %s\n" % (routine.ShortNamesTested())
|
|
||||||
for flavour in routine.flavours:
|
|
||||||
result += routine.RoutineHeaderWrapperC(flavour, False, 12)+" {\n"
|
|
||||||
|
|
||||||
# There is a version available in CBLAS
|
|
||||||
if flavour.precision_name in ["S","D","C","Z"]:
|
|
||||||
indent = " "*(10 + routine.Length())
|
|
||||||
arguments = routine.ArgumentsWrapperC(flavour)
|
|
||||||
|
|
||||||
# Complex scalars
|
|
||||||
for scalar in routine.scalars:
|
|
||||||
if flavour.IsComplex(scalar):
|
|
||||||
result += " const auto "+scalar+"_array = std::vector<"+flavour.buffertype[:-1]+">{"+scalar+".real(), "+scalar+".imag()};\n"
|
|
||||||
|
|
||||||
# Special case for scalar outputs
|
|
||||||
assignment = ""
|
|
||||||
postfix = ""
|
|
||||||
endofline = ""
|
|
||||||
extra_argument = ""
|
|
||||||
for output_buffer in routine.outputs:
|
|
||||||
if output_buffer in routine.ScalarBuffersFirst():
|
|
||||||
if flavour in [C,Z]:
|
|
||||||
postfix += "_sub"
|
|
||||||
indent += " "
|
|
||||||
extra_argument += ",\n"+indent+"reinterpret_cast<return_pointer_"+flavour.buffertype[:-1]+">(&"+output_buffer+"_buffer["+output_buffer+"_offset])"
|
|
||||||
elif output_buffer in routine.IndexBuffers():
|
|
||||||
assignment = "((int*)&"+output_buffer+"_buffer[0])["+output_buffer+"_offset] = "
|
|
||||||
indent += " "*len(assignment)
|
|
||||||
else:
|
|
||||||
assignment = output_buffer+"_buffer["+output_buffer+"_offset]"
|
|
||||||
if (flavour.name in ["Sc","Dz"]):
|
|
||||||
assignment = assignment+".real("
|
|
||||||
endofline += ")"
|
|
||||||
else:
|
|
||||||
assignment = assignment+" = "
|
|
||||||
indent += " "*len(assignment)
|
|
||||||
|
|
||||||
result += " "+assignment+"cblas_"+flavour.name.lower()+routine.name+postfix+"("
|
|
||||||
result += (",\n"+indent).join([a for a in arguments])
|
|
||||||
result += extra_argument+endofline+");\n"
|
|
||||||
|
|
||||||
# There is no CBLAS available, forward the call to one of the available functions
|
|
||||||
else: # Half-precision
|
|
||||||
indent = " "*(9 + routine.Length())
|
|
||||||
|
|
||||||
# Convert to float (note: also integer buffers are stored as half/float)
|
|
||||||
for buf in routine.inputs + routine.outputs:
|
|
||||||
result += " auto "+buf+"_buffer_bis = HalfToFloatBuffer("+buf+"_buffer);\n"
|
|
||||||
|
|
||||||
# Call the float routine
|
|
||||||
result += " cblasX"+routine.name+"("
|
|
||||||
result += (",\n"+indent).join([a for a in routine.ArgumentsHalf()])
|
|
||||||
result += ");\n"
|
|
||||||
|
|
||||||
# Convert back to half
|
|
||||||
for buf in routine.outputs:
|
|
||||||
result += " FloatToHalfBuffer("+buf+"_buffer, "+buf+"_buffer_bis);\n"
|
|
||||||
|
|
||||||
# Complete
|
|
||||||
result += "}\n"
|
|
||||||
return result
|
|
||||||
|
|
||||||
# ==================================================================================================
|
|
||||||
|
|
||||||
# Checks for the number of command-line arguments
|
|
||||||
if len(sys.argv) != 2:
|
|
||||||
print "[ERROR] Usage: generator.py <root_of_clblast>"
|
|
||||||
sys.exit()
|
|
||||||
|
|
||||||
# Parses the command-line arguments
|
# Parses the command-line arguments
|
||||||
path_clblast = sys.argv[1]
|
parser = argparse.ArgumentParser()
|
||||||
|
parser.add_argument("clblast_root", help="Root of the CLBlast sources")
|
||||||
|
parser.add_argument("-v", "--verbose", action="store_true", help="Increase verbosity of the script")
|
||||||
|
cl_args = parser.parse_args(argv)
|
||||||
|
library_root = cl_args.clblast_root
|
||||||
|
|
||||||
|
# Sets all the files the output
|
||||||
files = [
|
files = [
|
||||||
path_clblast+"/include/clblast.h",
|
library_root + "/include/clblast.h",
|
||||||
path_clblast+"/src/clblast.cpp",
|
library_root + "/src/clblast.cpp",
|
||||||
path_clblast+"/include/clblast_c.h",
|
library_root + "/include/clblast_c.h",
|
||||||
path_clblast+"/src/clblast_c.cpp",
|
library_root + "/src/clblast_c.cpp",
|
||||||
path_clblast+"/test/wrapper_clblas.hpp",
|
library_root + "/test/wrapper_clblas.hpp",
|
||||||
path_clblast+"/test/wrapper_cblas.hpp",
|
library_root + "/test/wrapper_cblas.hpp",
|
||||||
]
|
]
|
||||||
header_lines = [84, 74, 93, 22, 29, 41]
|
|
||||||
footer_lines = [17, 75, 19, 14, 6, 6]
|
|
||||||
|
|
||||||
# Checks whether the command-line arguments are valid; exists otherwise
|
# Checks whether the command-line arguments are valid; exists otherwise
|
||||||
for f in files:
|
for f in files:
|
||||||
if not os.path.isfile(f):
|
if not os.path.isfile(f):
|
||||||
print "[ERROR] The path '"+path_clblast+"' does not point to the root of the CLBlast library"
|
print("[ERROR] The path '" + library_root + "' does not point to the root of the CLBlast library")
|
||||||
sys.exit()
|
sys.exit()
|
||||||
|
|
||||||
# ==================================================================================================
|
# Iterates over all regular files to output
|
||||||
|
for i in range(0, len(files)):
|
||||||
# Iterates over all files to output
|
|
||||||
for i in xrange(0,len(files)):
|
|
||||||
|
|
||||||
# Stores the header and the footer of the original file
|
# Stores the header and the footer of the original file
|
||||||
with open(files[i]) as f:
|
with open(files[i]) as f:
|
||||||
original = f.readlines()
|
original = f.readlines()
|
||||||
file_header = original[:header_lines[i]]
|
file_header = original[:HEADER_LINES[i]]
|
||||||
file_footer = original[-footer_lines[i]:]
|
file_footer = original[-FOOTER_LINES[i]:]
|
||||||
|
|
||||||
# Re-writes the body of the file
|
# Re-writes the body of the file
|
||||||
with open(files[i], "w") as f:
|
with open(files[i], "w") as f:
|
||||||
body = ""
|
body = ""
|
||||||
levels = [1, 2, 3] if (i == 4 or i == 5) else [1, 2, 3, 4]
|
levels = [1, 2, 3] if (i == 4 or i == 5) else [1, 2, 3, 4]
|
||||||
for level in levels:
|
for level in levels:
|
||||||
body += separators[level-1]+"\n"
|
body += cpp.LEVEL_SEPARATORS[level - 1] + "\n"
|
||||||
|
for routine in ROUTINES[level - 1]:
|
||||||
if i == 0:
|
if i == 0:
|
||||||
body += clblast_h(routines[level-1])
|
body += cpp.clblast_h(routine)
|
||||||
if i == 1:
|
if i == 1:
|
||||||
body += clblast_cc(routines[level-1])
|
body += cpp.clblast_cc(routine)
|
||||||
if i == 2:
|
if i == 2:
|
||||||
body += clblast_c_h(routines[level-1])
|
body += cpp.clblast_c_h(routine)
|
||||||
if i == 3:
|
if i == 3:
|
||||||
body += clblast_c_cc(routines[level-1])
|
body += cpp.clblast_c_cc(routine)
|
||||||
if i == 4:
|
if i == 4:
|
||||||
body += wrapper_clblas(routines[level-1])
|
body += cpp.wrapper_clblas(routine)
|
||||||
if i == 5:
|
if i == 5:
|
||||||
body += wrapper_cblas(routines[level-1])
|
body += cpp.wrapper_cblas(routine)
|
||||||
f.write("".join(file_header))
|
f.write("".join(file_header))
|
||||||
f.write(body)
|
f.write(body)
|
||||||
f.write("".join(file_footer))
|
f.write("".join(file_footer))
|
||||||
|
|
||||||
# ==================================================================================================
|
# Outputs all the test implementations
|
||||||
|
|
||||||
# Outputs all the correctness-test implementations
|
|
||||||
for level in [1, 2, 3, 4]:
|
for level in [1, 2, 3, 4]:
|
||||||
for routine in routines[level-1]:
|
for routine in ROUTINES[level - 1]:
|
||||||
if routine.has_tests:
|
if routine.has_tests:
|
||||||
filename = path_clblast+"/test/correctness/routines/level"+levelnames[level-1]+"/x"+routine.name+".cpp"
|
level_string = cpp.LEVEL_NAMES[level - 1]
|
||||||
with open(filename, "w") as f:
|
routine_suffix = "level" + level_string + "/x" + routine.name + ".cpp"
|
||||||
body = ""
|
|
||||||
body += "#include \"test/correctness/testblas.hpp\"\n"
|
|
||||||
body += "#include \"test/routines/level"+levelnames[level-1]+"/x"+routine.name+".hpp\"\n\n"
|
|
||||||
body += "// Shortcuts to the clblast namespace\n"
|
|
||||||
body += "using float2 = clblast::float2;\n"
|
|
||||||
body += "using double2 = clblast::double2;\n\n"
|
|
||||||
body += "// Main function (not within the clblast namespace)\n"
|
|
||||||
body += "int main(int argc, char *argv[]) {\n"
|
|
||||||
body += " auto errors = size_t{0};\n"
|
|
||||||
not_first = "false"
|
|
||||||
for flavour in routine.flavours:
|
|
||||||
body += " errors += clblast::RunTests<clblast::TestX"+routine.name+flavour.TestTemplate()
|
|
||||||
body += ">(argc, argv, "+not_first+", \""+flavour.name+routine.name.upper()+"\");\n"
|
|
||||||
not_first = "true"
|
|
||||||
body += " if (errors > 0) { return 1; } else { return 0; }\n"
|
|
||||||
body += "}\n"
|
|
||||||
f.write(header+"\n")
|
|
||||||
f.write(body)
|
|
||||||
f.write(footer)
|
|
||||||
|
|
||||||
# Outputs all the performance-test implementations
|
# Correctness tests
|
||||||
for level in [1,2,3,4]:
|
filename = library_root + "/test/correctness/routines/" + routine_suffix
|
||||||
for routine in routines[level-1]:
|
|
||||||
if routine.has_tests:
|
|
||||||
filename = path_clblast+"/test/performance/routines/level"+levelnames[level-1]+"/x"+routine.name+".cpp"
|
|
||||||
with open(filename, "w") as f:
|
with open(filename, "w") as f:
|
||||||
body = ""
|
f.write(cpp.HEADER + "\n")
|
||||||
body += "#include \"test/performance/client.hpp\"\n"
|
f.write(cpp.correctness_test(routine, level_string))
|
||||||
body += "#include \"test/routines/level"+levelnames[level-1]+"/x"+routine.name+".hpp\"\n\n"
|
f.write(cpp.FOOTER)
|
||||||
body += "// Shortcuts to the clblast namespace\n"
|
|
||||||
body += "using float2 = clblast::float2;\n"
|
|
||||||
body += "using double2 = clblast::double2;\n\n"
|
|
||||||
body += "// Main function (not within the clblast namespace)\n"
|
|
||||||
body += "int main(int argc, char *argv[]) {\n"
|
|
||||||
default = PrecisionToFullName(routine.flavours[0].precision_name)
|
|
||||||
body += " switch(clblast::GetPrecision(argc, argv, clblast::Precision::k"+default+")) {\n"
|
|
||||||
for precision in ["H","S","D","C","Z"]:
|
|
||||||
body += " case clblast::Precision::k"+PrecisionToFullName(precision)+":"
|
|
||||||
found = False
|
|
||||||
for flavour in routine.flavours:
|
|
||||||
if flavour.precision_name == precision:
|
|
||||||
body += "\n clblast::RunClient<clblast::TestX"+routine.name+flavour.TestTemplate()
|
|
||||||
body += ">(argc, argv); break;\n"
|
|
||||||
found = True
|
|
||||||
if not found:
|
|
||||||
body += " throw std::runtime_error(\"Unsupported precision mode\");\n"
|
|
||||||
body += " }\n"
|
|
||||||
body += " return 0;\n"
|
|
||||||
body += "}\n"
|
|
||||||
f.write(header+"\n")
|
|
||||||
f.write(body)
|
|
||||||
f.write(footer)
|
|
||||||
|
|
||||||
# ==================================================================================================
|
# Performance tests
|
||||||
|
filename = library_root + "/test/performance/routines/" + routine_suffix
|
||||||
|
with open(filename, "w") as f:
|
||||||
|
f.write(cpp.HEADER + "\n")
|
||||||
|
f.write(cpp.performance_test(routine, level_string))
|
||||||
|
f.write(cpp.FOOTER)
|
||||||
|
|
||||||
# Outputs the API documentation
|
# Outputs the API documentation
|
||||||
filename = path_clblast+"/doc/clblast.md"
|
filename = cl_args.clblast_root + "/doc/clblast.md"
|
||||||
with open(filename, "w") as f:
|
with open(filename, "w") as f:
|
||||||
|
|
||||||
# Outputs the header
|
# Outputs the header
|
||||||
f.write("CLBlast: API reference\n")
|
doc_header = doc.header()
|
||||||
f.write("================\n")
|
f.write(doc_header)
|
||||||
f.write("\n\n")
|
|
||||||
|
|
||||||
# Loops over the routines
|
# Generates the documentation for each routine
|
||||||
for level in [1, 2, 3, 4]:
|
for level in [1, 2, 3, 4]:
|
||||||
for routine in routines[level-1]:
|
for routine in ROUTINES[level - 1]:
|
||||||
if routine.implemented:
|
if routine.implemented:
|
||||||
|
doc_routine = doc.generate(routine)
|
||||||
|
f.write(doc_routine)
|
||||||
|
|
||||||
# Routine header
|
if __name__ == '__main__':
|
||||||
f.write("x"+routine.name.upper()+": "+routine.description+"\n")
|
main(sys.argv[1:])
|
||||||
f.write("-------------\n")
|
|
||||||
f.write("\n")
|
|
||||||
f.write(routine.details+"\n")
|
|
||||||
f.write("\n")
|
|
||||||
|
|
||||||
# Routine API
|
|
||||||
f.write("C++ API:\n")
|
|
||||||
f.write("```\n")
|
|
||||||
f.write(routine.RoutineHeaderCPP(12, "")+"\n")
|
|
||||||
f.write("```\n")
|
|
||||||
f.write("\n")
|
|
||||||
f.write("C API:\n")
|
|
||||||
f.write("```\n")
|
|
||||||
for flavour in routine.flavours:
|
|
||||||
f.write(routine.RoutineHeaderC(flavour, 20, "")+"\n")
|
|
||||||
f.write("```\n")
|
|
||||||
f.write("\n")
|
|
||||||
|
|
||||||
# Routine arguments
|
|
||||||
f.write("Arguments to "+routine.name.upper()+":\n")
|
|
||||||
f.write("\n")
|
|
||||||
for argument in routine.ArgumentsDoc():
|
|
||||||
f.write("* "+argument+"\n")
|
|
||||||
f.write("* `cl_command_queue* queue`: Pointer to an OpenCL command queue associated with a context and device to execute the routine on.\n")
|
|
||||||
f.write("* `cl_event* event`: Pointer to an OpenCL event to be able to wait for completion of the routine's OpenCL kernel(s). This is an optional argument.\n")
|
|
||||||
f.write("\n")
|
|
||||||
|
|
||||||
# Routine requirements
|
|
||||||
if len(routine.RequirementsDoc()) > 0:
|
|
||||||
f.write("Requirements for "+routine.name.upper()+":\n")
|
|
||||||
f.write("\n")
|
|
||||||
for requirement in routine.RequirementsDoc():
|
|
||||||
f.write("* "+requirement+"\n")
|
|
||||||
f.write("\n")
|
|
||||||
|
|
||||||
# Routine footer
|
|
||||||
f.write("\n\n")
|
|
||||||
|
|
||||||
|
|
||||||
# ==================================================================================================
|
|
||||||
|
|
0
scripts/generator/generator/__init__.py
Normal file
0
scripts/generator/generator/__init__.py
Normal file
69
scripts/generator/generator/convert.py
Normal file
69
scripts/generator/generator/convert.py
Normal file
|
@ -0,0 +1,69 @@
|
||||||
|
|
||||||
|
# This file is part of the CLBlast project. The project is licensed under Apache Version 2.0. This file follows the
|
||||||
|
# PEP8 Python style guide and uses a max-width of 120 characters per line.
|
||||||
|
#
|
||||||
|
# Author(s):
|
||||||
|
# Cedric Nugteren <www.cedricnugteren.nl>
|
||||||
|
|
||||||
|
|
||||||
|
def precision_to_full_name(x):
|
||||||
|
"""Translates an option name to a CLBlast data-type"""
|
||||||
|
return {
|
||||||
|
'H': "Half",
|
||||||
|
'S': "Single",
|
||||||
|
'D': "Double",
|
||||||
|
'C': "ComplexSingle",
|
||||||
|
'Z': "ComplexDouble",
|
||||||
|
}[x]
|
||||||
|
|
||||||
|
|
||||||
|
def option_to_clblast(x):
|
||||||
|
"""Translates an option name to a CLBlast data-type"""
|
||||||
|
return {
|
||||||
|
'layout': "Layout",
|
||||||
|
'a_transpose': "Transpose",
|
||||||
|
'b_transpose': "Transpose",
|
||||||
|
'ab_transpose': "Transpose",
|
||||||
|
'side': "Side",
|
||||||
|
'triangle': "Triangle",
|
||||||
|
'diagonal': "Diagonal",
|
||||||
|
}[x]
|
||||||
|
|
||||||
|
|
||||||
|
def option_to_clblas(x):
|
||||||
|
"""As above, but for clBLAS data-types"""
|
||||||
|
return {
|
||||||
|
'layout': "clblasOrder",
|
||||||
|
'a_transpose': "clblasTranspose",
|
||||||
|
'b_transpose': "clblasTranspose",
|
||||||
|
'ab_transpose': "clblasTranspose",
|
||||||
|
'side': "clblasSide",
|
||||||
|
'triangle': "clblasUplo",
|
||||||
|
'diagonal': "clblasDiag",
|
||||||
|
}[x]
|
||||||
|
|
||||||
|
|
||||||
|
def option_to_cblas(x):
|
||||||
|
"""As above, but for CBLAS data-types"""
|
||||||
|
return {
|
||||||
|
'layout': "CBLAS_ORDER",
|
||||||
|
'a_transpose': "CBLAS_TRANSPOSE",
|
||||||
|
'b_transpose': "CBLAS_TRANSPOSE",
|
||||||
|
'ab_transpose': "CBLAS_TRANSPOSE",
|
||||||
|
'side': "CBLAS_SIDE",
|
||||||
|
'triangle': "CBLAS_UPLO",
|
||||||
|
'diagonal': "CBLAS_DIAG",
|
||||||
|
}[x]
|
||||||
|
|
||||||
|
|
||||||
|
def option_to_documentation(x):
|
||||||
|
"""Translates an option name to a documentation string"""
|
||||||
|
return {
|
||||||
|
'layout': "Data-layout of the matrices, either `Layout::kRowMajor` (101) for row-major layout or `Layout::kColMajor` (102) for column-major data-layout.",
|
||||||
|
'a_transpose': "Transposing the input matrix A, either `Transpose::kNo` (111), `Transpose::kYes` (112), or `Transpose::kConjugate` (113) for a complex-conjugate transpose.",
|
||||||
|
'b_transpose': "Transposing the input matrix B, either `Transpose::kNo` (111), `Transpose::kYes` (112), or `Transpose::kConjugate` (113) for a complex-conjugate transpose.",
|
||||||
|
'ab_transpose': "Transposing the packed input matrix AP, either `Transpose::kNo` (111), `Transpose::kYes` (112), or `Transpose::kConjugate` (113) for a complex-conjugate transpose.",
|
||||||
|
'side': "The position of the triangular matrix in the operation, either on the `Side::kLeft` (141) or `Side::kRight` (142).",
|
||||||
|
'triangle': "The part of the array of the triangular matrix to be used, either `Triangle::kUpper` (121) or `Triangle::kLower` (122).",
|
||||||
|
'diagonal': "The property of the diagonal matrix, either `Diagonal::kNonUnit` (131) for non-unit values on the diagonal or `Diagonal::kUnit` (132) for unit values on the diagonal.",
|
||||||
|
}[x]
|
257
scripts/generator/generator/cpp.py
Normal file
257
scripts/generator/generator/cpp.py
Normal file
|
@ -0,0 +1,257 @@
|
||||||
|
|
||||||
|
# This file is part of the CLBlast project. The project is licensed under Apache Version 2.0. This file follows the
|
||||||
|
# PEP8 Python style guide and uses a max-width of 120 characters per line.
|
||||||
|
#
|
||||||
|
# Author(s):
|
||||||
|
# Cedric Nugteren <www.cedricnugteren.nl>
|
||||||
|
|
||||||
|
import generator.datatype as datatype
|
||||||
|
import generator.convert as convert
|
||||||
|
|
||||||
|
|
||||||
|
NL = "\n"
|
||||||
|
SEPARATOR = "// ================================================================================================="
|
||||||
|
|
||||||
|
# Separators for the BLAS levels
|
||||||
|
LEVEL_SEPARATORS = [
|
||||||
|
NL + SEPARATOR + NL + "// BLAS level-1 (vector-vector) routines" + NL + SEPARATOR,
|
||||||
|
NL + SEPARATOR + NL + "// BLAS level-2 (matrix-vector) routines" + NL + SEPARATOR,
|
||||||
|
NL + SEPARATOR + NL + "// BLAS level-3 (matrix-matrix) routines" + NL + SEPARATOR,
|
||||||
|
NL + SEPARATOR + NL + "// Extra non-BLAS routines (level-X)" + NL + SEPARATOR
|
||||||
|
]
|
||||||
|
|
||||||
|
# Names of the level sub-folders
|
||||||
|
LEVEL_NAMES = ["1", "2", "3", "x"]
|
||||||
|
|
||||||
|
# Main header/footer for source files
|
||||||
|
FOOTER = NL + SEPARATOR + NL
|
||||||
|
HEADER = NL + SEPARATOR + """
|
||||||
|
// This file is part of the CLBlast project. The project is licensed under Apache Version 2.0. This
|
||||||
|
// project loosely follows the Google C++ styleguide and uses a tab-size of two spaces and a max-
|
||||||
|
// width of 100 characters per line.
|
||||||
|
//
|
||||||
|
// Author(s):
|
||||||
|
// Cedric Nugteren <www.cedricnugteren.nl>
|
||||||
|
//
|
||||||
|
""" + SEPARATOR + NL
|
||||||
|
|
||||||
|
|
||||||
|
def clblast_h(routine):
|
||||||
|
"""The C++ API header (.h)"""
|
||||||
|
result = NL + "// " + routine.description + ": " + routine.short_names() + NL
|
||||||
|
result += routine.routine_header_cpp(12, " = nullptr") + ";" + NL
|
||||||
|
return result
|
||||||
|
|
||||||
|
|
||||||
|
def clblast_cc(routine):
|
||||||
|
"""The C++ API implementation (.cpp)"""
|
||||||
|
indent1 = " " * (20 + routine.length())
|
||||||
|
result = NL + "// " + routine.description + ": " + routine.short_names() + NL
|
||||||
|
if routine.implemented:
|
||||||
|
result += routine.routine_header_cpp(12, "") + " {" + NL
|
||||||
|
result += " auto queue_cpp = Queue(*queue);" + NL
|
||||||
|
result += " auto routine = X" + routine.name + "<" + routine.template.template + ">(queue_cpp, event);" + NL
|
||||||
|
result += " auto status = routine.SetUp();" + NL
|
||||||
|
result += " if (status != StatusCode::kSuccess) { return status; }" + NL
|
||||||
|
result += " return routine.Do" + routine.name.capitalize() + "("
|
||||||
|
result += ("," + NL + indent1).join([a for a in routine.arguments_clcudaapi()])
|
||||||
|
result += ");" + NL
|
||||||
|
else:
|
||||||
|
result += routine.routine_header_type_cpp(12) + " {" + NL
|
||||||
|
result += " return StatusCode::kNotImplemented;" + NL
|
||||||
|
result += "}" + NL
|
||||||
|
for flavour in routine.flavours:
|
||||||
|
indent2 = " " * (34 + routine.length() + len(flavour.template))
|
||||||
|
result += "template StatusCode PUBLIC_API " + routine.name.capitalize() + "<" + flavour.template + ">("
|
||||||
|
result += ("," + NL + indent2).join([a for a in routine.arguments_type(flavour)])
|
||||||
|
result += "," + NL + indent2 + "cl_command_queue*, cl_event*);" + NL
|
||||||
|
return result
|
||||||
|
|
||||||
|
|
||||||
|
def clblast_c_h(routine):
|
||||||
|
"""The C API header (.h)"""
|
||||||
|
result = NL + "// " + routine.description + ": " + routine.short_names() + NL
|
||||||
|
for flavour in routine.flavours:
|
||||||
|
result += routine.routine_header_c(flavour, 31, " PUBLIC_API") + ";" + NL
|
||||||
|
return result
|
||||||
|
|
||||||
|
|
||||||
|
def clblast_c_cc(routine):
|
||||||
|
"""The C API implementation (.cpp)"""
|
||||||
|
result = NL + "// " + routine.name.upper() + NL
|
||||||
|
for flavour in routine.flavours:
|
||||||
|
template = "<" + flavour.template + ">" if routine.no_scalars() else ""
|
||||||
|
indent = " " * (26 + routine.length() + len(template))
|
||||||
|
result += routine.routine_header_c(flavour, 20, "") + " {" + NL
|
||||||
|
result += " auto status = clblast::" + routine.name.capitalize() + template + "("
|
||||||
|
result += ("," + NL + indent).join([a for a in routine.arguments_cast(flavour, indent)])
|
||||||
|
result += "," + NL + indent + "queue, event);"
|
||||||
|
result += NL + " return static_cast<StatusCode>(status);" + NL + "}" + NL
|
||||||
|
return result
|
||||||
|
|
||||||
|
|
||||||
|
def wrapper_clblas(routine):
|
||||||
|
"""The wrapper to the reference clBLAS routines (for performance/correctness testing)"""
|
||||||
|
result = ""
|
||||||
|
if routine.has_tests:
|
||||||
|
result += NL + "// Forwards the clBLAS calls for %s" % routine.short_names_tested() + NL
|
||||||
|
if routine.no_scalars():
|
||||||
|
result += routine.routine_header_wrapper_clblas(routine.template, True, 21) + ";" + NL
|
||||||
|
for flavour in routine.flavours:
|
||||||
|
result += routine.routine_header_wrapper_clblas(flavour, False, 21) + " {" + NL
|
||||||
|
|
||||||
|
# There is a version available in clBLAS
|
||||||
|
if flavour.precision_name in ["S", "D", "C", "Z"]:
|
||||||
|
indent = " " * (17 + routine.length())
|
||||||
|
arguments = routine.arguments_wrapper_clblas(flavour)
|
||||||
|
if routine.scratch:
|
||||||
|
result += " auto queue = Queue(queues[0]);" + NL
|
||||||
|
result += " auto context = queue.GetContext();" + NL
|
||||||
|
result += " auto scratch_buffer = Buffer<" + flavour.template + ">"
|
||||||
|
result += "(context, " + routine.scratch + ");" + NL
|
||||||
|
arguments += ["scratch_buffer()"]
|
||||||
|
result += " return clblas" + flavour.name + routine.name + "("
|
||||||
|
result += ("," + NL + indent).join([a for a in arguments])
|
||||||
|
result += "," + NL + indent + "num_queues, queues, num_wait_events, wait_events, events);"
|
||||||
|
|
||||||
|
# There is no clBLAS available, forward the call to one of the available functions
|
||||||
|
else: # Half-precision
|
||||||
|
indent = " " * (24 + routine.length())
|
||||||
|
|
||||||
|
# Convert to float (note: also integer buffers are stored as half/float)
|
||||||
|
for buf in routine.inputs + routine.outputs:
|
||||||
|
result += " auto " + buf + "_buffer_bis = HalfToFloatBuffer(" + buf + "_buffer, queues[0]);" + NL
|
||||||
|
|
||||||
|
# Call the float routine
|
||||||
|
result += " auto status = clblasX" + routine.name + "("
|
||||||
|
result += ("," + NL + indent).join([a for a in routine.arguments_half()])
|
||||||
|
result += "," + NL + indent + "num_queues, queues, num_wait_events, wait_events, events);"
|
||||||
|
result += NL
|
||||||
|
|
||||||
|
# Convert back to half
|
||||||
|
for buf in routine.outputs:
|
||||||
|
result += " FloatToHalfBuffer(" + buf + "_buffer, " + buf + "_buffer_bis, queues[0]);" + NL
|
||||||
|
result += " return status;"
|
||||||
|
|
||||||
|
# Complete
|
||||||
|
result += NL + "}" + NL
|
||||||
|
return result
|
||||||
|
|
||||||
|
|
||||||
|
def wrapper_cblas(routine):
|
||||||
|
"""The wrapper to the reference CBLAS routines (for performance/correctness testing)"""
|
||||||
|
result = ""
|
||||||
|
if routine.has_tests:
|
||||||
|
result += NL + "// Forwards the Netlib BLAS calls for %s" % routine.short_names_tested() + NL
|
||||||
|
for flavour in routine.flavours:
|
||||||
|
result += routine.routine_header_wrapper_cblas(flavour, 12) + " {" + NL
|
||||||
|
|
||||||
|
# There is a version available in CBLAS
|
||||||
|
if flavour.precision_name in ["S", "D", "C", "Z"]:
|
||||||
|
indent = " " * (10 + routine.length())
|
||||||
|
arguments = routine.arguments_wrapper_cblas(flavour)
|
||||||
|
|
||||||
|
# Complex scalars
|
||||||
|
for scalar in routine.scalars:
|
||||||
|
if flavour.is_complex(scalar):
|
||||||
|
result += " const auto " + scalar + "_array = std::vector<" + flavour.buffer_type[:-1] + ">"
|
||||||
|
result += "{" + scalar + ".real(), " + scalar + ".imag()};" + NL
|
||||||
|
|
||||||
|
# Special case for scalar outputs
|
||||||
|
assignment = ""
|
||||||
|
postfix = ""
|
||||||
|
end_of_line = ""
|
||||||
|
extra_argument = ""
|
||||||
|
for output_buffer in routine.outputs:
|
||||||
|
if output_buffer in routine.scalar_buffers_first():
|
||||||
|
if flavour in [datatype.C, datatype.Z]:
|
||||||
|
postfix += "_sub"
|
||||||
|
indent += " "
|
||||||
|
extra_argument += "," + NL + indent
|
||||||
|
extra_argument += "reinterpret_cast<return_pointer_" + flavour.buffer_type[:-1] + ">"
|
||||||
|
extra_argument += "(&" + output_buffer + "_buffer[" + output_buffer + "_offset])"
|
||||||
|
elif output_buffer in routine.index_buffers():
|
||||||
|
assignment = "((int*)&" + output_buffer + "_buffer[0])[" + output_buffer + "_offset] = "
|
||||||
|
indent += " " * len(assignment)
|
||||||
|
else:
|
||||||
|
assignment = output_buffer + "_buffer[" + output_buffer + "_offset]"
|
||||||
|
if flavour.name in ["Sc", "Dz"]:
|
||||||
|
assignment += ".real("
|
||||||
|
end_of_line += ")"
|
||||||
|
else:
|
||||||
|
assignment += " = "
|
||||||
|
indent += " " * len(assignment)
|
||||||
|
|
||||||
|
result += " " + assignment + "cblas_" + flavour.name.lower() + routine.name + postfix + "("
|
||||||
|
result += ("," + NL + indent).join([a for a in arguments])
|
||||||
|
result += extra_argument + end_of_line + ");" + NL
|
||||||
|
|
||||||
|
# There is no CBLAS available, forward the call to one of the available functions
|
||||||
|
else: # Half-precision
|
||||||
|
indent = " " * (9 + routine.length())
|
||||||
|
|
||||||
|
# Convert to float (note: also integer buffers are stored as half/float)
|
||||||
|
for buf in routine.inputs + routine.outputs:
|
||||||
|
result += " auto " + buf + "_buffer_bis = HalfToFloatBuffer(" + buf + "_buffer);" + NL
|
||||||
|
|
||||||
|
# Call the float routine
|
||||||
|
result += " cblasX" + routine.name + "("
|
||||||
|
result += ("," + NL + indent).join([a for a in routine.arguments_half()])
|
||||||
|
result += ");" + NL
|
||||||
|
|
||||||
|
# Convert back to half
|
||||||
|
for buf in routine.outputs:
|
||||||
|
result += " FloatToHalfBuffer(" + buf + "_buffer, " + buf + "_buffer_bis);" + NL
|
||||||
|
|
||||||
|
# Complete
|
||||||
|
result += "}" + NL
|
||||||
|
return result
|
||||||
|
|
||||||
|
|
||||||
|
def performance_test(routine, level_string):
|
||||||
|
"""Generates the body of a performance test for a specific routine"""
|
||||||
|
result = ""
|
||||||
|
result += "#include \"test/performance/client.hpp\"" + NL
|
||||||
|
result += "#include \"test/routines/level" + level_string + "/x" + routine.name + ".hpp\"" + NL + NL
|
||||||
|
result += "// Shortcuts to the clblast namespace" + NL
|
||||||
|
result += "using float2 = clblast::float2;" + NL
|
||||||
|
result += "using double2 = clblast::double2;" + NL + NL
|
||||||
|
result += "// Main function (not within the clblast namespace)" + NL
|
||||||
|
result += "int main(int argc, char *argv[]) {" + NL
|
||||||
|
default = convert.precision_to_full_name(routine.flavours[0].precision_name)
|
||||||
|
result += " switch(clblast::GetPrecision(argc, argv, clblast::Precision::k" + default + ")) {" + NL
|
||||||
|
for precision in ["H", "S", "D", "C", "Z"]:
|
||||||
|
result += " case clblast::Precision::k" + convert.precision_to_full_name(precision) + ":"
|
||||||
|
found = False
|
||||||
|
for flavour in routine.flavours:
|
||||||
|
if flavour.precision_name == precision:
|
||||||
|
result += NL + " clblast::RunClient<clblast::TestX" + routine.name + flavour.test_template()
|
||||||
|
result += ">(argc, argv); break;" + NL
|
||||||
|
found = True
|
||||||
|
if not found:
|
||||||
|
result += " throw std::runtime_error(\"Unsupported precision mode\");" + NL
|
||||||
|
result += " }" + NL
|
||||||
|
result += " return 0;" + NL
|
||||||
|
result += "}" + NL
|
||||||
|
return result
|
||||||
|
|
||||||
|
|
||||||
|
def correctness_test(routine, level_string):
|
||||||
|
"""Generates the body of a correctness test for a specific routine"""
|
||||||
|
result = ""
|
||||||
|
result += "#include \"test/correctness/testblas.hpp\"" + NL
|
||||||
|
result += "#include \"test/routines/level" + level_string + "/x" + routine.name + ".hpp\"" + NL + NL
|
||||||
|
result += "// Shortcuts to the clblast namespace" + NL
|
||||||
|
result += "using float2 = clblast::float2;" + NL
|
||||||
|
result += "using double2 = clblast::double2;" + NL + NL
|
||||||
|
result += "// Main function (not within the clblast namespace)" + NL
|
||||||
|
result += "int main(int argc, char *argv[]) {" + NL
|
||||||
|
result += " auto errors = size_t{0};" + NL
|
||||||
|
not_first = "false"
|
||||||
|
for flavour in routine.flavours:
|
||||||
|
result += " errors += clblast::RunTests<clblast::TestX" + routine.name + flavour.test_template()
|
||||||
|
result += ">(argc, argv, " + not_first + ", \"" + flavour.name + routine.name.upper() + "\");" + NL
|
||||||
|
not_first = "true"
|
||||||
|
result += " if (errors > 0) { return 1; } else { return 0; }" + NL
|
||||||
|
result += "}" + NL
|
||||||
|
return result
|
92
scripts/generator/generator/datatype.py
Normal file
92
scripts/generator/generator/datatype.py
Normal file
|
@ -0,0 +1,92 @@
|
||||||
|
|
||||||
|
# This file is part of the CLBlast project. The project is licensed under Apache Version 2.0. This file follows the
|
||||||
|
# PEP8 Python style guide and uses a max-width of 120 characters per line.
|
||||||
|
#
|
||||||
|
# Author(s):
|
||||||
|
# Cedric Nugteren <www.cedricnugteren.nl>
|
||||||
|
|
||||||
|
|
||||||
|
# Short-hands for data-types
|
||||||
|
D_HALF = "half"
|
||||||
|
D_FLOAT = "float"
|
||||||
|
D_DOUBLE = "double"
|
||||||
|
D_FLOAT2 = "float2"
|
||||||
|
D_DOUBLE2 = "double2"
|
||||||
|
D_HALF_OPENCL = "cl_half"
|
||||||
|
D_FLOAT2_OPENCL = "cl_float2"
|
||||||
|
D_DOUBLE2_OPENCL = "cl_double2"
|
||||||
|
|
||||||
|
|
||||||
|
class DataType:
|
||||||
|
"""Class holding data-type and precision information"""
|
||||||
|
|
||||||
|
def __init__(self, precision_name, name, template, scalars, buffer_type):
|
||||||
|
self.precision_name = precision_name
|
||||||
|
self.name = name
|
||||||
|
self.template = template
|
||||||
|
self.alpha_cpp = scalars[0]
|
||||||
|
self.beta_cpp = scalars[1]
|
||||||
|
self.alpha_cl = scalars[2]
|
||||||
|
self.beta_cl = scalars[3]
|
||||||
|
self.buffer_type = buffer_type
|
||||||
|
|
||||||
|
def use_alpha(self):
|
||||||
|
"""Outputs the name of the data-type (alpha/beta), possibly transforming into the right type"""
|
||||||
|
if self.alpha_cpp in [D_FLOAT2, D_DOUBLE2]:
|
||||||
|
return self.alpha_cpp + "{alpha.s[0], alpha.s[1]}"
|
||||||
|
return "alpha"
|
||||||
|
|
||||||
|
def use_beta(self):
|
||||||
|
"""As above, but for beta instead of alpha"""
|
||||||
|
if self.beta_cpp in [D_FLOAT2, D_DOUBLE2]:
|
||||||
|
return self.beta_cpp + "{beta.s[0], beta.s[1]}"
|
||||||
|
return "beta"
|
||||||
|
|
||||||
|
def use_alpha_opencl(self):
|
||||||
|
"""As above, but the transformation is in the opposite direction"""
|
||||||
|
if self.alpha_cpp in [D_FLOAT2, D_DOUBLE2]:
|
||||||
|
return self.alpha_cl + "{{alpha.real(), alpha.imag()}}"
|
||||||
|
return "alpha"
|
||||||
|
|
||||||
|
def use_beta_opencl(self):
|
||||||
|
"""As above, but for beta instead of alpha"""
|
||||||
|
if self.beta_cpp in [D_FLOAT2, D_DOUBLE2]:
|
||||||
|
return self.beta_cl + "{{beta.real(), beta.imag()}}"
|
||||||
|
return "beta"
|
||||||
|
|
||||||
|
def test_template(self):
|
||||||
|
"""Returns the template as used in the correctness/performance tests"""
|
||||||
|
if self.buffer_type != self.beta_cpp:
|
||||||
|
return "<" + self.buffer_type + "," + self.beta_cpp + ">, " + self.buffer_type + ", " + self.beta_cpp
|
||||||
|
return "<" + self.buffer_type + ">, " + self.buffer_type + ", " + self.beta_cpp
|
||||||
|
|
||||||
|
def is_complex(self, scalar):
|
||||||
|
"""Current scalar is complex"""
|
||||||
|
return ((scalar == "alpha" and self.alpha_cpp in [D_FLOAT2, D_DOUBLE2]) or
|
||||||
|
(scalar == "beta" and self.beta_cpp in [D_FLOAT2, D_DOUBLE2]))
|
||||||
|
|
||||||
|
|
||||||
|
# Regular data-types
|
||||||
|
H = DataType("H", "H", D_HALF, [D_HALF] * 2 + [D_HALF_OPENCL] * 2, D_HALF) # half (16)
|
||||||
|
S = DataType("S", "S", D_FLOAT, [D_FLOAT] * 4, D_FLOAT) # single (32)
|
||||||
|
D = DataType("D", "D", D_DOUBLE, [D_DOUBLE] * 4, D_DOUBLE) # double (64)
|
||||||
|
C = DataType("C", "C", D_FLOAT2, [D_FLOAT2] * 2 + [D_FLOAT2_OPENCL] * 2, D_FLOAT2) # single-complex (3232)
|
||||||
|
Z = DataType("Z", "Z", D_DOUBLE2, [D_DOUBLE2] * 2 + [D_DOUBLE2_OPENCL] * 2, D_DOUBLE2) # double-complex (6464)
|
||||||
|
|
||||||
|
# Special cases
|
||||||
|
Sc = DataType("C", "Sc", D_FLOAT2, [D_FLOAT2] * 4, D_FLOAT2) # As C, but with real output
|
||||||
|
Dz = DataType("Z", "Dz", D_DOUBLE2, [D_DOUBLE2] * 4, D_DOUBLE2) # As Z, but with real output
|
||||||
|
iH = DataType("H", "iH", D_HALF, [D_HALF] * 4, D_HALF) # As H, but with integer output
|
||||||
|
iS = DataType("S", "iS", D_FLOAT, [D_FLOAT] * 4, D_FLOAT) # As S, but with integer output
|
||||||
|
iD = DataType("D", "iD", D_DOUBLE, [D_DOUBLE] * 4, D_DOUBLE) # As D, but with integer output
|
||||||
|
iC = DataType("C", "iC", D_FLOAT2, [D_FLOAT2] * 2 + [D_FLOAT2_OPENCL] * 2, D_FLOAT2) # As C, but with integer output
|
||||||
|
iZ = DataType("Z", "iZ", D_DOUBLE2, [D_DOUBLE2] * 2 + [D_DOUBLE2_OPENCL] * 2, D_DOUBLE2) # As Z, but with int output
|
||||||
|
Css = DataType("C", "C", D_FLOAT, [D_FLOAT, D_FLOAT, D_FLOAT, D_FLOAT], D_FLOAT2) # As C, but with constants from S
|
||||||
|
Zdd = DataType("Z", "Z", D_DOUBLE, [D_DOUBLE] * 4, D_DOUBLE2) # As Z, but with constants from D
|
||||||
|
Ccs = DataType("C", "C", D_FLOAT2 + "," + D_FLOAT, [D_FLOAT2, D_FLOAT, D_FLOAT2_OPENCL, D_FLOAT], D_FLOAT2) # As C, but with one constant from S
|
||||||
|
Zzd = DataType("Z", "Z", D_DOUBLE2 + "," + D_DOUBLE, [D_DOUBLE2, D_DOUBLE, D_DOUBLE2_OPENCL, D_DOUBLE], D_DOUBLE2) # As Z, but with one constant from D
|
||||||
|
|
||||||
|
# C++ template data-types
|
||||||
|
T = DataType("T", "typename T", "T", ["T", "T", "T", "T"], "T") # regular routine
|
||||||
|
Tc = DataType("Tc", "typename T", "std::complex<T>,T", ["T", "T", "T", "T"], "std::complex<T>") # for herk
|
||||||
|
TU = DataType("TU", "typename T, typename U", "T,U", ["T", "U", "T", "U"], "T") # for her2k
|
57
scripts/generator/generator/doc.py
Normal file
57
scripts/generator/generator/doc.py
Normal file
|
@ -0,0 +1,57 @@
|
||||||
|
|
||||||
|
# This file is part of the CLBlast project. The project is licensed under Apache Version 2.0. This file follows the
|
||||||
|
# PEP8 Python style guide and uses a max-width of 120 characters per line.
|
||||||
|
#
|
||||||
|
# Author(s):
|
||||||
|
# Cedric Nugteren <www.cedricnugteren.nl>
|
||||||
|
|
||||||
|
NL = "\n"
|
||||||
|
|
||||||
|
|
||||||
|
def header():
|
||||||
|
"""Generates the header for the API documentation"""
|
||||||
|
result = "CLBlast: API reference" + NL
|
||||||
|
result += "================" + NL + NL + NL
|
||||||
|
return result
|
||||||
|
|
||||||
|
|
||||||
|
def generate(routine):
|
||||||
|
"""Generates the API documentation for a given routine"""
|
||||||
|
result = ""
|
||||||
|
|
||||||
|
# Routine header
|
||||||
|
result += "x" + routine.name.upper() + ": " + routine.description + NL
|
||||||
|
result += "-------------" + NL + NL
|
||||||
|
result += routine.details + NL + NL
|
||||||
|
|
||||||
|
# Routine API
|
||||||
|
result += "C++ API:" + NL
|
||||||
|
result += "```" + NL
|
||||||
|
result += routine.routine_header_cpp(12, "") + NL
|
||||||
|
result += "```" + NL + NL
|
||||||
|
result += "C API:" + NL
|
||||||
|
result += "```" + NL
|
||||||
|
for flavour in routine.flavours:
|
||||||
|
result += routine.routine_header_c(flavour, 20, "") + NL
|
||||||
|
result += "```" + NL + NL
|
||||||
|
|
||||||
|
# Routine arguments
|
||||||
|
result += "Arguments to " + routine.name.upper() + ":" + NL + NL
|
||||||
|
for argument in routine.arguments_doc():
|
||||||
|
result += "* " + argument + NL
|
||||||
|
result += "* `cl_command_queue* queue`: "
|
||||||
|
result += "Pointer to an OpenCL command queue associated with a context and device to execute the routine on." + NL
|
||||||
|
result += "* `cl_event* event`: "
|
||||||
|
result += "Pointer to an OpenCL event to be able to wait for completion of the routine's OpenCL kernel(s). "
|
||||||
|
result += "This is an optional argument." + NL + NL
|
||||||
|
|
||||||
|
# Routine requirements
|
||||||
|
if len(routine.requirements_doc()) > 0:
|
||||||
|
result += "Requirements for " + routine.name.upper() + ":" + NL + NL
|
||||||
|
for requirement in routine.requirements_doc():
|
||||||
|
result += "* " + requirement + NL
|
||||||
|
result += NL
|
||||||
|
|
||||||
|
# Routine footer
|
||||||
|
result += NL + NL
|
||||||
|
return result
|
552
scripts/generator/generator/routine.py
Normal file
552
scripts/generator/generator/routine.py
Normal file
|
@ -0,0 +1,552 @@
|
||||||
|
|
||||||
|
# This file is part of the CLBlast project. The project is licensed under Apache Version 2.0. This file follows the
|
||||||
|
# PEP8 Python style guide and uses a max-width of 120 characters per line.
|
||||||
|
#
|
||||||
|
# Author(s):
|
||||||
|
# Cedric Nugteren <www.cedricnugteren.nl>
|
||||||
|
|
||||||
|
from itertools import chain
|
||||||
|
|
||||||
|
import generator.convert as convert
|
||||||
|
|
||||||
|
|
||||||
|
class Routine:
|
||||||
|
"""Class holding routine-specific information (e.g. name, which arguments, which precisions)"""
|
||||||
|
def __init__(self, implemented, has_tests, level, name, template, flavours, sizes, options,
|
||||||
|
inputs, outputs, scalars, scratch, description, details, requirements):
|
||||||
|
self.implemented = implemented
|
||||||
|
self.has_tests = has_tests
|
||||||
|
self.level = level
|
||||||
|
self.name = name
|
||||||
|
self.template = template
|
||||||
|
self.flavours = flavours
|
||||||
|
self.sizes = sizes
|
||||||
|
self.options = options
|
||||||
|
self.inputs = inputs
|
||||||
|
self.outputs = outputs
|
||||||
|
self.scalars = scalars
|
||||||
|
self.scratch = scratch # Scratch buffer (e.g. for xDOT)
|
||||||
|
self.description = description
|
||||||
|
self.details = details
|
||||||
|
self.requirements = requirements
|
||||||
|
|
||||||
|
@staticmethod
|
||||||
|
def scalar_buffers_first():
|
||||||
|
"""List of scalar buffers"""
|
||||||
|
return ["dot", "nrm2", "asum", "sum", "imax", "imin"]
|
||||||
|
|
||||||
|
@staticmethod
|
||||||
|
def scalar_buffers_second():
|
||||||
|
"""List of scalar buffers"""
|
||||||
|
return ["sa", "sb", "sc", "ss", "sd1", "sd2", "sx1", "sy1", "sparam"]
|
||||||
|
|
||||||
|
@staticmethod
|
||||||
|
def other_scalars():
|
||||||
|
"""List of scalars other than alpha and beta"""
|
||||||
|
return ["cos", "sin"]
|
||||||
|
|
||||||
|
@staticmethod
|
||||||
|
def index_buffers():
|
||||||
|
"""List of buffers with unsigned int type"""
|
||||||
|
return ["imax", "imin"]
|
||||||
|
|
||||||
|
@staticmethod
|
||||||
|
def postfix(name):
|
||||||
|
"""Retrieves the postfix for a buffer"""
|
||||||
|
return "inc" if (name in ["x", "y"]) else "ld"
|
||||||
|
|
||||||
|
@staticmethod
|
||||||
|
def buffers_vector():
|
||||||
|
"""Distinguish between vectors and matrices"""
|
||||||
|
return ["x", "y"]
|
||||||
|
|
||||||
|
@staticmethod
|
||||||
|
def buffers_matrix():
|
||||||
|
"""Distinguish between vectors and matrices"""
|
||||||
|
return ["a", "b", "c", "ap"]
|
||||||
|
|
||||||
|
def non_index_inputs(self):
|
||||||
|
"""Lists of input/output buffers not index (integer)"""
|
||||||
|
buffers = self.inputs[:] # make a copy
|
||||||
|
for i in self.index_buffers():
|
||||||
|
if i in buffers:
|
||||||
|
buffers.remove(i)
|
||||||
|
return buffers
|
||||||
|
|
||||||
|
def non_index_outputs(self):
|
||||||
|
"""Lists of input/output buffers not index (integer)"""
|
||||||
|
buffers = self.outputs[:] # make a copy
|
||||||
|
for i in self.index_buffers():
|
||||||
|
if i in buffers:
|
||||||
|
buffers.remove(i)
|
||||||
|
return buffers
|
||||||
|
|
||||||
|
def buffers_without_ld_inc(self):
|
||||||
|
"""List of buffers without 'inc' or 'ld'"""
|
||||||
|
return self.scalar_buffers_first() + self.scalar_buffers_second() + ["ap"]
|
||||||
|
|
||||||
|
def length(self):
|
||||||
|
"""Retrieves the number of characters in the routine's name"""
|
||||||
|
return len(self.name)
|
||||||
|
|
||||||
|
def no_scalars(self):
|
||||||
|
"""Determines whether or not this routine has scalar arguments (alpha/beta)"""
|
||||||
|
return self.scalars == []
|
||||||
|
|
||||||
|
def short_names(self):
|
||||||
|
"""Returns the upper-case names of these routines (all flavours)"""
|
||||||
|
return "/".join([f.name + self.name.upper() for f in self.flavours])
|
||||||
|
|
||||||
|
def short_names_tested(self):
|
||||||
|
"""As above, but excludes some"""
|
||||||
|
names = [f.name + self.name.upper() for f in self.flavours]
|
||||||
|
if "H" + self.name.upper() in names:
|
||||||
|
names.remove("H" + self.name.upper())
|
||||||
|
return "/".join(names)
|
||||||
|
|
||||||
|
def buffers_first(self):
|
||||||
|
"""Determines which buffers go first (between alpha and beta) and which ones go after"""
|
||||||
|
if self.level == "2b":
|
||||||
|
return ["x", "y"]
|
||||||
|
return ["ap", "a", "b", "x"]
|
||||||
|
|
||||||
|
def buffers_second(self):
|
||||||
|
if self.level == "2b":
|
||||||
|
return ["ap", "a", "b", "c"]
|
||||||
|
return ["y", "c"]
|
||||||
|
|
||||||
|
def buffer(self, name):
|
||||||
|
"""Retrieves a variable name for a specific input/output vector/matrix (e.g. 'x')"""
|
||||||
|
if name in self.inputs or name in self.outputs:
|
||||||
|
a = [name + "_buffer"]
|
||||||
|
b = [name + "_offset"]
|
||||||
|
c = [name + "_" + self.postfix(name)] if (name not in self.buffers_without_ld_inc()) else []
|
||||||
|
return [", ".join(a + b + c)]
|
||||||
|
return []
|
||||||
|
|
||||||
|
def buffer_bis(self, name):
|
||||||
|
"""As above but with a '_bis' suffix for the buffer name"""
|
||||||
|
if name in self.inputs or name in self.outputs:
|
||||||
|
a = [name + "_buffer_bis"]
|
||||||
|
b = [name + "_offset"]
|
||||||
|
c = [name + "_" + self.postfix(name)] if name not in self.buffers_without_ld_inc() else []
|
||||||
|
return [", ".join(a + b + c)]
|
||||||
|
return []
|
||||||
|
|
||||||
|
def buffer_def(self, name):
|
||||||
|
"""As above but with data-types"""
|
||||||
|
prefix = "const " if name in self.inputs else ""
|
||||||
|
if name in self.inputs or name in self.outputs:
|
||||||
|
a = [prefix + "cl_mem " + name + "_buffer"]
|
||||||
|
b = ["const size_t " + name + "_offset"]
|
||||||
|
c = ["const size_t " + name + "_" + self.postfix(name)] if name not in self.buffers_without_ld_inc() else []
|
||||||
|
return [", ".join(a + b + c)]
|
||||||
|
return []
|
||||||
|
|
||||||
|
def buffer_def_wrapper_cl(self, name, flavour):
|
||||||
|
"""As above but with data-types"""
|
||||||
|
prefix = "const " if name in self.inputs else ""
|
||||||
|
if name in self.inputs or name in self.outputs:
|
||||||
|
a = [prefix + "Buffer<" + flavour.buffer_type + ">& " + name + "_buffer"]
|
||||||
|
b = ["const size_t " + name + "_offset"]
|
||||||
|
c = ["const size_t " + name + "_" + self.postfix(name)] if name not in self.buffers_without_ld_inc() else []
|
||||||
|
return [", ".join(a + b + c)]
|
||||||
|
return []
|
||||||
|
|
||||||
|
def buffer_def_vector(self, name, flavour):
|
||||||
|
"""As above but as vectors"""
|
||||||
|
prefix = "const " if name in self.inputs else ""
|
||||||
|
if name in self.inputs or name in self.outputs:
|
||||||
|
a = [prefix + "std::vector<" + flavour.buffer_type + ">& " + name + "_buffer"]
|
||||||
|
b = ["const size_t " + name + "_offset"]
|
||||||
|
c = ["const size_t " + name + "_" + self.postfix(name)] if name not in self.buffers_without_ld_inc() else []
|
||||||
|
return [", ".join(a + b + c)]
|
||||||
|
return []
|
||||||
|
|
||||||
|
def buffer_clcudaapi(self, name):
|
||||||
|
"""As above but with CLCudaAPI buffers"""
|
||||||
|
if name in self.inputs or name in self.outputs:
|
||||||
|
buffer_type = "unsigned int" if (name in self.index_buffers()) else self.template.buffer_type
|
||||||
|
a = ["Buffer<" + buffer_type + ">(" + name + "_buffer)"]
|
||||||
|
b = [name + "_offset"]
|
||||||
|
c = [name + "_" + self.postfix(name)] if (name not in self.buffers_without_ld_inc()) else []
|
||||||
|
return [", ".join(a + b + c)]
|
||||||
|
return []
|
||||||
|
|
||||||
|
def buffer_wrapper_clblas(self, name):
|
||||||
|
"""As above but with a static cast for clBLAS wrapper"""
|
||||||
|
if name in self.inputs or name in self.outputs:
|
||||||
|
a = [name + "_buffer()"]
|
||||||
|
b = [name + "_offset"]
|
||||||
|
c = []
|
||||||
|
if name in ["x", "y"]:
|
||||||
|
c = ["static_cast<int>(" + name + "_" + self.postfix(name) + ")"]
|
||||||
|
elif name in ["a", "b", "c"]:
|
||||||
|
c = [name + "_" + self.postfix(name)]
|
||||||
|
return [", ".join(a + b + c)]
|
||||||
|
return []
|
||||||
|
|
||||||
|
def buffer_wrapper_cblas(self, name, flavour):
|
||||||
|
"""As above but with a static cast for CBLAS wrapper"""
|
||||||
|
prefix = "const " if name in self.inputs else ""
|
||||||
|
if name in self.inputs or name in self.outputs:
|
||||||
|
if name == "sy1":
|
||||||
|
a = [name + "_buffer[" + name + "_offset]"]
|
||||||
|
elif flavour.precision_name in ["C", "Z"]:
|
||||||
|
a = ["reinterpret_cast<" + prefix + flavour.buffer_type[:-1] + "*>" +
|
||||||
|
"(&" + name + "_buffer[" + name + "_offset])"]
|
||||||
|
else:
|
||||||
|
a = ["&" + name + "_buffer[" + name + "_offset]"]
|
||||||
|
c = []
|
||||||
|
if name in ["x", "y"]:
|
||||||
|
c = ["static_cast<int>(" + name + "_" + self.postfix(name) + ")"]
|
||||||
|
elif name in ["a", "b", "c"]:
|
||||||
|
c = [name + "_" + self.postfix(name)]
|
||||||
|
return [", ".join(a + c)]
|
||||||
|
return []
|
||||||
|
|
||||||
|
def buffer_type(self, name):
|
||||||
|
"""As above, but only data-types"""
|
||||||
|
prefix = "const " if (name in self.inputs) else ""
|
||||||
|
if (name in self.inputs) or (name in self.outputs):
|
||||||
|
a = [prefix + "cl_mem"]
|
||||||
|
b = ["const size_t"]
|
||||||
|
c = ["const size_t"] if (name not in self.buffers_without_ld_inc()) else []
|
||||||
|
return [", ".join(a + b + c)]
|
||||||
|
return []
|
||||||
|
|
||||||
|
def buffer_doc(self, name):
|
||||||
|
"""Retrieves the documentation of the buffers"""
|
||||||
|
prefix = "const " if (name in self.inputs) else ""
|
||||||
|
inout = "input" if (name in self.inputs) else "output"
|
||||||
|
if (name in self.inputs) or (name in self.outputs):
|
||||||
|
math_name = name.upper() + " matrix" if (name in self.buffers_matrix()) else name + " vector"
|
||||||
|
inc_ld_description = "Leading dimension " if (name in self.buffers_matrix()) else "Stride/increment "
|
||||||
|
a = ["`" + prefix + "cl_mem " + name + "_buffer`: OpenCL buffer to store the " + inout + " " + math_name + "."]
|
||||||
|
b = ["`const size_t " + name + "_offset`: The offset in elements from the start of the " + inout + " " + math_name + "."]
|
||||||
|
if name not in self.buffers_without_ld_inc():
|
||||||
|
c = ["`const size_t " + name + "_" + self.postfix(name) + "`: " +
|
||||||
|
inc_ld_description + "of the " + inout + " " + math_name + ". This value must be greater than 0."]
|
||||||
|
else:
|
||||||
|
c = []
|
||||||
|
return a + b + c
|
||||||
|
return []
|
||||||
|
|
||||||
|
def scalar(self, name):
|
||||||
|
"""Retrieves the name of a scalar (alpha/beta)"""
|
||||||
|
if name in self.scalars:
|
||||||
|
return [name]
|
||||||
|
return []
|
||||||
|
|
||||||
|
def scalar_half_to_float(self, name):
|
||||||
|
"""As above, but converts from float to half"""
|
||||||
|
if name in self.scalars:
|
||||||
|
return ["HalfToFloat(" + name + ")"]
|
||||||
|
return []
|
||||||
|
|
||||||
|
def scalar_use(self, name, flavour):
|
||||||
|
"""Retrieves the use of a scalar (alpha/beta)"""
|
||||||
|
if name in self.scalars:
|
||||||
|
if name == "alpha":
|
||||||
|
return [flavour.use_alpha()]
|
||||||
|
elif name == "beta":
|
||||||
|
return [flavour.use_beta()]
|
||||||
|
return [name]
|
||||||
|
return []
|
||||||
|
|
||||||
|
def scalar_use_wrapper(self, name, flavour):
|
||||||
|
"""As above, but for the clBLAS wrapper"""
|
||||||
|
if name in self.scalars:
|
||||||
|
if name == "alpha":
|
||||||
|
return [flavour.use_alpha_opencl()]
|
||||||
|
elif name == "beta":
|
||||||
|
return [flavour.use_beta_opencl()]
|
||||||
|
return [name]
|
||||||
|
return []
|
||||||
|
|
||||||
|
def scalar_use_wrapper_cblas(self, name, flavour):
|
||||||
|
"""As above, but for the CBLAS wrapper"""
|
||||||
|
if name in self.scalars:
|
||||||
|
if flavour.is_complex(name):
|
||||||
|
return [name + "_array.data()"]
|
||||||
|
return [name]
|
||||||
|
return []
|
||||||
|
|
||||||
|
def scalar_def(self, name, flavour):
|
||||||
|
"""Retrieves the definition of a scalar (alpha/beta)"""
|
||||||
|
if name in self.scalars:
|
||||||
|
if name == "alpha":
|
||||||
|
return ["const " + flavour.alpha_cl + " " + name]
|
||||||
|
return ["const " + flavour.beta_cl + " " + name]
|
||||||
|
return []
|
||||||
|
|
||||||
|
def scalar_def_plain(self, name, flavour):
|
||||||
|
"""As above, but without 'cl_' prefix"""
|
||||||
|
if name in self.scalars:
|
||||||
|
if name == "alpha":
|
||||||
|
return ["const " + flavour.alpha_cpp + " " + name]
|
||||||
|
return ["const " + flavour.beta_cpp + " " + name]
|
||||||
|
return []
|
||||||
|
|
||||||
|
def scalar_type(self, name, flavour):
|
||||||
|
"""Retrieves the type of a scalar (alpha/beta)"""
|
||||||
|
if name in self.scalars:
|
||||||
|
if name == "alpha":
|
||||||
|
return ["const " + flavour.alpha_cpp]
|
||||||
|
return ["const " + flavour.beta_cpp]
|
||||||
|
return []
|
||||||
|
|
||||||
|
def scalar_doc(self, name):
|
||||||
|
"""Retrieves the documentation of a scalar"""
|
||||||
|
if name in self.scalars:
|
||||||
|
if name == "alpha":
|
||||||
|
return ["`const " + self.template.alpha_cpp + " " + name + "`: Input scalar constant."]
|
||||||
|
return ["`const " + self.template.beta_cpp + " " + name + "`: Input scalar constant."]
|
||||||
|
return []
|
||||||
|
|
||||||
|
def sizes_list(self):
|
||||||
|
"""Retrieves a list of comma-separated sizes (m, n, k)"""
|
||||||
|
if self.sizes:
|
||||||
|
return [", ".join([s for s in self.sizes])]
|
||||||
|
return []
|
||||||
|
|
||||||
|
def sizes_def(self):
|
||||||
|
"""Retrieves the definition of the sizes (m,n,k)"""
|
||||||
|
if self.sizes:
|
||||||
|
return [", ".join(["const size_t " + s for s in self.sizes])]
|
||||||
|
return []
|
||||||
|
|
||||||
|
def sizes_type(self):
|
||||||
|
"""Retrieves the types of the sizes (m,n,k)"""
|
||||||
|
if self.sizes:
|
||||||
|
return [", ".join(["const size_t" for s in self.sizes])]
|
||||||
|
return []
|
||||||
|
|
||||||
|
def sizes_doc(self):
|
||||||
|
"""# Retrieves the documentation of the sizes"""
|
||||||
|
if self.sizes:
|
||||||
|
definitions = ["`const size_t " + s + "`: Integer size argument. This value must be positive." for s in self.sizes]
|
||||||
|
return definitions
|
||||||
|
return []
|
||||||
|
|
||||||
|
def options_list(self):
|
||||||
|
"""Retrieves a list of options"""
|
||||||
|
if self.options:
|
||||||
|
return [", ".join(self.options)]
|
||||||
|
return []
|
||||||
|
|
||||||
|
def options_cast(self, indent):
|
||||||
|
"""As above, but now casted to CLBlast data-types"""
|
||||||
|
if self.options:
|
||||||
|
options = ["static_cast<clblast::" + convert.option_to_clblast(o) + ">(" + o + ")" for o in self.options]
|
||||||
|
return [(",\n" + indent).join(options)]
|
||||||
|
return []
|
||||||
|
|
||||||
|
def options_def(self):
|
||||||
|
"""Retrieves the definitions of the options (layout, transpose, side, etc.)"""
|
||||||
|
if self.options:
|
||||||
|
definitions = ["const " + convert.option_to_clblast(o) + " " + o for o in self.options]
|
||||||
|
return [", ".join(definitions)]
|
||||||
|
return []
|
||||||
|
|
||||||
|
def options_def_wrapper_clblas(self):
|
||||||
|
"""As above, but now using clBLAS data-types"""
|
||||||
|
if self.options:
|
||||||
|
definitions = ["const " + convert.option_to_clblas(o) + " " + o for o in self.options]
|
||||||
|
return [", ".join(definitions)]
|
||||||
|
return []
|
||||||
|
|
||||||
|
def options_def_wrapper_cblas(self):
|
||||||
|
"""As above, but now using CBLAS data-types"""
|
||||||
|
if self.options:
|
||||||
|
definitions = ["const " + convert.option_to_cblas(o) + " " + o for o in self.options]
|
||||||
|
return [", ".join(definitions)]
|
||||||
|
return []
|
||||||
|
|
||||||
|
def options_type(self):
|
||||||
|
"""Retrieves the types of the options (layout, transpose, side, etc.)"""
|
||||||
|
if self.options:
|
||||||
|
definitions = ["const " + convert.option_to_clblast(o) for o in self.options]
|
||||||
|
return [", ".join(definitions)]
|
||||||
|
return []
|
||||||
|
|
||||||
|
def options_doc(self):
|
||||||
|
"""Retrieves the documentation of the options"""
|
||||||
|
if self.options:
|
||||||
|
definitions = ["`const " + convert.option_to_clblast(o) + " " + o + "`: " + convert.option_to_documentation(o) for o in self.options]
|
||||||
|
return definitions
|
||||||
|
return []
|
||||||
|
|
||||||
|
def arguments(self):
|
||||||
|
"""Retrieves a combination of all the argument names (no types)"""
|
||||||
|
return (self.options_list() + self.sizes_list() +
|
||||||
|
list(chain(*[self.buffer(b) for b in self.scalar_buffers_first()])) +
|
||||||
|
self.scalar("alpha") +
|
||||||
|
list(chain(*[self.buffer(b) for b in self.buffers_first()])) +
|
||||||
|
self.scalar("beta") +
|
||||||
|
list(chain(*[self.buffer(b) for b in self.buffers_second()])) +
|
||||||
|
list(chain(*[self.buffer(b) for b in self.scalar_buffers_second()])) +
|
||||||
|
list(chain(*[self.scalar(s) for s in self.other_scalars()])))
|
||||||
|
|
||||||
|
def arguments_half(self):
|
||||||
|
"""As above, but with conversions from half to float"""
|
||||||
|
return (self.options_list() + self.sizes_list() +
|
||||||
|
list(chain(*[self.buffer_bis(b) for b in self.scalar_buffers_first()])) +
|
||||||
|
self.scalar_half_to_float("alpha") +
|
||||||
|
list(chain(*[self.buffer_bis(b) for b in self.buffers_first()])) +
|
||||||
|
self.scalar_half_to_float("beta") +
|
||||||
|
list(chain(*[self.buffer_bis(b) for b in self.buffers_second()])) +
|
||||||
|
list(chain(*[self.buffer_bis(b) for b in self.scalar_buffers_second()])) +
|
||||||
|
list(chain(*[self.scalar(s) for s in self.other_scalars()])))
|
||||||
|
|
||||||
|
def arguments_clcudaapi(self):
|
||||||
|
"""Retrieves a combination of all the argument names, with CLCudaAPI casts"""
|
||||||
|
return (self.options_list() + self.sizes_list() +
|
||||||
|
list(chain(*[self.buffer_clcudaapi(b) for b in self.scalar_buffers_first()])) +
|
||||||
|
self.scalar("alpha") +
|
||||||
|
list(chain(*[self.buffer_clcudaapi(b) for b in self.buffers_first()])) +
|
||||||
|
self.scalar("beta") +
|
||||||
|
list(chain(*[self.buffer_clcudaapi(b) for b in self.buffers_second()])) +
|
||||||
|
list(chain(*[self.buffer_clcudaapi(b) for b in self.scalar_buffers_second()])) +
|
||||||
|
list(chain(*[self.scalar(s) for s in self.other_scalars()])))
|
||||||
|
|
||||||
|
def arguments_cast(self, flavour, indent):
|
||||||
|
"""As above, but with CLBlast casts"""
|
||||||
|
return (self.options_cast(indent) + self.sizes_list() +
|
||||||
|
list(chain(*[self.buffer(b) for b in self.scalar_buffers_first()])) +
|
||||||
|
self.scalar_use("alpha", flavour) +
|
||||||
|
list(chain(*[self.buffer(b) for b in self.buffers_first()])) +
|
||||||
|
self.scalar_use("beta", flavour) +
|
||||||
|
list(chain(*[self.buffer(b) for b in self.buffers_second()])) +
|
||||||
|
list(chain(*[self.buffer(b) for b in self.scalar_buffers_second()])) +
|
||||||
|
list(chain(*[self.scalar_use(s, flavour) for s in self.other_scalars()])))
|
||||||
|
|
||||||
|
def arguments_wrapper_clblas(self, flavour):
|
||||||
|
"""As above, but for the clBLAS wrapper"""
|
||||||
|
return (self.options_list() + self.sizes_list() +
|
||||||
|
list(chain(*[self.buffer_wrapper_clblas(b) for b in self.scalar_buffers_first()])) +
|
||||||
|
self.scalar_use_wrapper("alpha", flavour) +
|
||||||
|
list(chain(*[self.buffer_wrapper_clblas(b) for b in self.buffers_first()])) +
|
||||||
|
self.scalar_use_wrapper("beta", flavour) +
|
||||||
|
list(chain(*[self.buffer_wrapper_clblas(b) for b in self.buffers_second()])) +
|
||||||
|
list(chain(*[self.buffer_wrapper_clblas(b) for b in self.scalar_buffers_second()])) +
|
||||||
|
list(chain(*[self.scalar_use_wrapper(s, flavour) for s in self.other_scalars()])))
|
||||||
|
|
||||||
|
def arguments_wrapper_cblas(self, flavour):
|
||||||
|
"""As above, but for the CBLAS wrapper"""
|
||||||
|
return (self.options_list() + self.sizes_list() +
|
||||||
|
self.scalar_use_wrapper_cblas("alpha", flavour) +
|
||||||
|
list(chain(*[self.buffer_wrapper_cblas(b, flavour) for b in self.buffers_first()])) +
|
||||||
|
self.scalar_use_wrapper_cblas("beta", flavour) +
|
||||||
|
list(chain(*[self.buffer_wrapper_cblas(b, flavour) for b in self.buffers_second()])) +
|
||||||
|
list(chain(*[self.buffer_wrapper_cblas(b, flavour) for b in self.scalar_buffers_second()])) +
|
||||||
|
list(chain(*[self.scalar_use_wrapper_cblas(s, flavour) for s in self.other_scalars()])))
|
||||||
|
|
||||||
|
def arguments_def(self, flavour):
|
||||||
|
"""Retrieves a combination of all the argument definitions"""
|
||||||
|
return (self.options_def() + self.sizes_def() +
|
||||||
|
list(chain(*[self.buffer_def(b) for b in self.scalar_buffers_first()])) +
|
||||||
|
self.scalar_def("alpha", flavour) +
|
||||||
|
list(chain(*[self.buffer_def(b) for b in self.buffers_first()])) +
|
||||||
|
self.scalar_def("beta", flavour) +
|
||||||
|
list(chain(*[self.buffer_def(b) for b in self.buffers_second()])) +
|
||||||
|
list(chain(*[self.buffer_def(b) for b in self.scalar_buffers_second()])) +
|
||||||
|
list(chain(*[self.scalar_def(s, flavour) for s in self.other_scalars()])))
|
||||||
|
|
||||||
|
def arguments_def_wrapper_clblas(self, flavour):
|
||||||
|
"""As above, but clBLAS wrapper plain data-types"""
|
||||||
|
return (self.options_def_wrapper_clblas() + self.sizes_def() +
|
||||||
|
list(chain(*[self.buffer_def_wrapper_cl(b, flavour) for b in self.scalar_buffers_first()])) +
|
||||||
|
self.scalar_def_plain("alpha", flavour) +
|
||||||
|
list(chain(*[self.buffer_def_wrapper_cl(b, flavour) for b in self.buffers_first()])) +
|
||||||
|
self.scalar_def_plain("beta", flavour) +
|
||||||
|
list(chain(*[self.buffer_def_wrapper_cl(b, flavour) for b in self.buffers_second()])) +
|
||||||
|
list(chain(*[self.buffer_def_wrapper_cl(b, flavour) for b in self.scalar_buffers_second()])) +
|
||||||
|
list(chain(*[self.scalar_def_plain(s, flavour) for s in self.other_scalars()])))
|
||||||
|
|
||||||
|
def arguments_def_wrapper_cblas(self, flavour):
|
||||||
|
"""As above, but CBLAS wrapper plain data-types"""
|
||||||
|
return (self.options_def_wrapper_cblas() + self.sizes_def() +
|
||||||
|
list(chain(*[self.buffer_def_vector(b, flavour) for b in self.scalar_buffers_first()])) +
|
||||||
|
self.scalar_def_plain("alpha", flavour) +
|
||||||
|
list(chain(*[self.buffer_def_vector(b, flavour) for b in self.buffers_first()])) +
|
||||||
|
self.scalar_def_plain("beta", flavour) +
|
||||||
|
list(chain(*[self.buffer_def_vector(b, flavour) for b in self.buffers_second()])) +
|
||||||
|
list(chain(*[self.buffer_def_vector(b, flavour) for b in self.scalar_buffers_second()])) +
|
||||||
|
list(chain(*[self.scalar_def_plain(s, flavour) for s in self.other_scalars()])))
|
||||||
|
|
||||||
|
def arguments_type(self, flavour):
|
||||||
|
"""Retrieves a combination of all the argument types"""
|
||||||
|
return (self.options_type() + self.sizes_type() +
|
||||||
|
list(chain(*[self.buffer_type(b) for b in self.scalar_buffers_first()])) +
|
||||||
|
self.scalar_type("alpha", flavour) +
|
||||||
|
list(chain(*[self.buffer_type(b) for b in self.buffers_first()])) +
|
||||||
|
self.scalar_type("beta", flavour) +
|
||||||
|
list(chain(*[self.buffer_type(b) for b in self.buffers_second()])) +
|
||||||
|
list(chain(*[self.buffer_type(b) for b in self.scalar_buffers_second()])) +
|
||||||
|
list(chain(*[self.scalar_type(s, flavour) for s in self.other_scalars()])))
|
||||||
|
|
||||||
|
def arguments_doc(self):
|
||||||
|
"""Retrieves a combination of all the argument types"""
|
||||||
|
return (self.options_doc() + self.sizes_doc() +
|
||||||
|
list(chain(*[self.buffer_doc(b) for b in self.scalar_buffers_first()])) +
|
||||||
|
list(chain(*[self.buffer_doc(b) for b in self.scalar_buffers_first()])) +
|
||||||
|
self.scalar_doc("alpha") +
|
||||||
|
list(chain(*[self.buffer_doc(b) for b in self.buffers_first()])) +
|
||||||
|
self.scalar_doc("beta") +
|
||||||
|
list(chain(*[self.buffer_doc(b) for b in self.buffers_second()])) +
|
||||||
|
list(chain(*[self.buffer_doc(b) for b in self.scalar_buffers_second()])) +
|
||||||
|
list(chain(*[self.scalar_doc(s) for s in self.other_scalars()])))
|
||||||
|
|
||||||
|
def requirements_doc(self):
|
||||||
|
"""Retrieves a list of routine requirements for documentation"""
|
||||||
|
return self.requirements
|
||||||
|
|
||||||
|
def routine_header_cpp(self, spaces, default_event):
|
||||||
|
"""Retrieves the C++ templated definition for a routine"""
|
||||||
|
indent = " " * (spaces + self.length())
|
||||||
|
result = "template <" + self.template.name + ">\n"
|
||||||
|
result += "StatusCode " + self.name.capitalize() + "("
|
||||||
|
result += (",\n" + indent).join([a for a in self.arguments_def(self.template)])
|
||||||
|
result += ",\n" + indent + "cl_command_queue* queue, cl_event* event" + default_event + ")"
|
||||||
|
return result
|
||||||
|
|
||||||
|
def routine_header_type_cpp(self, spaces):
|
||||||
|
"""As above, but now without variable names"""
|
||||||
|
indent = " " * (spaces + self.length())
|
||||||
|
result = "template <" + self.template.name + ">\n"
|
||||||
|
result += "StatusCode " + self.name.capitalize() + "("
|
||||||
|
result += (",\n" + indent).join([a for a in self.arguments_type(self.template)])
|
||||||
|
result += ",\n" + indent + "cl_command_queue*, cl_event*)"
|
||||||
|
return result
|
||||||
|
|
||||||
|
def routine_header_c(self, flavour, spaces, extra_qualifier):
|
||||||
|
"""As above, but now for C"""
|
||||||
|
indent = " " * (spaces + self.length())
|
||||||
|
result = "StatusCode" + extra_qualifier + " CLBlast" + flavour.name + self.name + "("
|
||||||
|
result += (",\n" + indent).join([a for a in self.arguments_def(flavour)])
|
||||||
|
result += ",\n" + indent + "cl_command_queue* queue, cl_event* event)"
|
||||||
|
return result
|
||||||
|
|
||||||
|
def routine_header_wrapper_clblas(self, flavour, def_only, spaces):
|
||||||
|
"""As above, but now for the clBLAS wrapper"""
|
||||||
|
template = "<" + flavour.template + ">" if self.no_scalars() and not def_only else ""
|
||||||
|
indent = " " * (spaces + self.length() + len(template))
|
||||||
|
result = ""
|
||||||
|
if self.no_scalars():
|
||||||
|
result += "template <"
|
||||||
|
if def_only:
|
||||||
|
result += flavour.name
|
||||||
|
result += ">\n"
|
||||||
|
result += "clblasStatus clblasX" + self.name + template + "("
|
||||||
|
result += (",\n" + indent).join([a for a in self.arguments_def_wrapper_clblas(flavour)])
|
||||||
|
result += ",\n" + indent + "cl_uint num_queues, cl_command_queue *queues"
|
||||||
|
result += ",\n" + indent + "cl_uint num_wait_events, const cl_event *wait_events, cl_event *events)"
|
||||||
|
return result
|
||||||
|
|
||||||
|
def routine_header_wrapper_cblas(self, flavour, spaces):
|
||||||
|
"""As above, but now for the CBLAS wrapper"""
|
||||||
|
indent = " " * (spaces + self.length())
|
||||||
|
result = "void cblasX" + self.name + "("
|
||||||
|
result += (",\n" + indent).join([a for a in self.arguments_def_wrapper_cblas(flavour)]) + ")"
|
||||||
|
return result
|
|
@ -1,603 +0,0 @@
|
||||||
#!/usr/bin/env python
|
|
||||||
|
|
||||||
# ==================================================================================================
|
|
||||||
# This file is part of the CLBlast project. The project is licensed under Apache Version 2.0. This
|
|
||||||
# project loosely follows the Google C++ styleguide and uses a max-width of 100 characters per line.
|
|
||||||
#
|
|
||||||
# Author(s):
|
|
||||||
# Cedric Nugteren <www.cedricnugteren.nl>
|
|
||||||
#
|
|
||||||
# This file contains the 'Routine' class, used in the generator script to generate the CLBlast API
|
|
||||||
# interface and implementation.
|
|
||||||
#
|
|
||||||
# ==================================================================================================
|
|
||||||
|
|
||||||
# System modules
|
|
||||||
from itertools import chain
|
|
||||||
|
|
||||||
# Translates an option name to a CLBlast data-type
|
|
||||||
def OptionToCLBlast(x):
|
|
||||||
return {
|
|
||||||
'layout': "Layout",
|
|
||||||
'a_transpose': "Transpose",
|
|
||||||
'b_transpose': "Transpose",
|
|
||||||
'ab_transpose': "Transpose",
|
|
||||||
'side': "Side",
|
|
||||||
'triangle': "Triangle",
|
|
||||||
'diagonal': "Diagonal",
|
|
||||||
}[x]
|
|
||||||
|
|
||||||
# As above, but for clBLAS data-types
|
|
||||||
def OptionToWrapperCL(x):
|
|
||||||
return {
|
|
||||||
'layout': "clblasOrder",
|
|
||||||
'a_transpose': "clblasTranspose",
|
|
||||||
'b_transpose': "clblasTranspose",
|
|
||||||
'ab_transpose': "clblasTranspose",
|
|
||||||
'side': "clblasSide",
|
|
||||||
'triangle': "clblasUplo",
|
|
||||||
'diagonal': "clblasDiag",
|
|
||||||
}[x]
|
|
||||||
|
|
||||||
# As above, but for CBLAS data-types
|
|
||||||
def OptionToWrapperC(x):
|
|
||||||
return {
|
|
||||||
'layout': "CBLAS_ORDER",
|
|
||||||
'a_transpose': "CBLAS_TRANSPOSE",
|
|
||||||
'b_transpose': "CBLAS_TRANSPOSE",
|
|
||||||
'ab_transpose': "CBLAS_TRANSPOSE",
|
|
||||||
'side': "CBLAS_SIDE",
|
|
||||||
'triangle': "CBLAS_UPLO",
|
|
||||||
'diagonal': "CBLAS_DIAG",
|
|
||||||
}[x]
|
|
||||||
|
|
||||||
# Translates an option name to a documentation string
|
|
||||||
def OptionToDoc(x):
|
|
||||||
return {
|
|
||||||
'layout': "Data-layout of the matrices, either `Layout::kRowMajor` (101) for row-major layout or `Layout::kColMajor` (102) for column-major data-layout.",
|
|
||||||
'a_transpose': "Transposing the input matrix A, either `Transpose::kNo` (111), `Transpose::kYes` (112), or `Transpose::kConjugate` (113) for a complex-conjugate transpose.",
|
|
||||||
'b_transpose': "Transposing the input matrix B, either `Transpose::kNo` (111), `Transpose::kYes` (112), or `Transpose::kConjugate` (113) for a complex-conjugate transpose.",
|
|
||||||
'ab_transpose': "Transposing the packed input matrix AP, either `Transpose::kNo` (111), `Transpose::kYes` (112), or `Transpose::kConjugate` (113) for a complex-conjugate transpose.",
|
|
||||||
'side': "The position of the triangular matrix in the operation, either on the `Side::kLeft` (141) or `Side::kRight` (142).",
|
|
||||||
'triangle': "The part of the array of the triangular matrix to be used, either `Triangle::kUpper` (121) or `Triangle::kLower` (122).",
|
|
||||||
'diagonal': "The property of the diagonal matrix, either `Diagonal::kNonUnit` (131) for non-unit values on the diagonal or `Diagonal::kUnit` (132) for unit values on the diagonal.",
|
|
||||||
}[x]
|
|
||||||
|
|
||||||
# ==================================================================================================
|
|
||||||
|
|
||||||
# Class holding routine-specific information (e.g. name, which arguments, which precisions)
|
|
||||||
class Routine():
|
|
||||||
def __init__(self, implemented, has_tests, level, name, template, flavours, sizes, options,
|
|
||||||
inputs, outputs, scalars, scratch, description, details, requirements):
|
|
||||||
self.implemented = implemented
|
|
||||||
self.has_tests = has_tests
|
|
||||||
self.level = level
|
|
||||||
self.name = name
|
|
||||||
self.template = template
|
|
||||||
self.flavours = flavours
|
|
||||||
self.sizes = sizes
|
|
||||||
self.options = options
|
|
||||||
self.inputs = inputs
|
|
||||||
self.outputs = outputs
|
|
||||||
self.scalars = scalars
|
|
||||||
self.scratch = scratch # Scratch buffer (e.g. for xDOT)
|
|
||||||
self.description = description
|
|
||||||
self.details = details
|
|
||||||
self.requirements = requirements
|
|
||||||
|
|
||||||
# List of scalar buffers
|
|
||||||
def ScalarBuffersFirst(self):
|
|
||||||
return ["dot","nrm2","asum","sum","imax","imin"]
|
|
||||||
def ScalarBuffersSecond(self):
|
|
||||||
return ["sa","sb","sc","ss","sd1","sd2","sx1","sy1","sparam"]
|
|
||||||
|
|
||||||
# List of scalars other than alpha and beta
|
|
||||||
def OtherScalars(self):
|
|
||||||
return ["cos","sin"]
|
|
||||||
|
|
||||||
# List of buffers with unsigned int type
|
|
||||||
def IndexBuffers(self):
|
|
||||||
return ["imax","imin"]
|
|
||||||
|
|
||||||
# Lists of input/output buffers not index (integer)
|
|
||||||
def NonIndexInputs(self):
|
|
||||||
buffers = self.inputs[:] # make a copy
|
|
||||||
for i in self.IndexBuffers():
|
|
||||||
if i in buffers: buffers.remove(i)
|
|
||||||
return buffers
|
|
||||||
def NonIndexOutputs(self):
|
|
||||||
buffers = self.outputs[:] # make a copy
|
|
||||||
for i in self.IndexBuffers():
|
|
||||||
if i in buffers: buffers.remove(i)
|
|
||||||
return buffers
|
|
||||||
|
|
||||||
# List of buffers without 'inc' or 'ld'
|
|
||||||
def BuffersWithoutLdInc(self):
|
|
||||||
return self.ScalarBuffersFirst() + self.ScalarBuffersSecond() + ["ap"]
|
|
||||||
|
|
||||||
# Retrieves the number of characters in the routine's name
|
|
||||||
def Length(self):
|
|
||||||
return len(self.name)
|
|
||||||
|
|
||||||
# Retrieves the postfix for a buffer
|
|
||||||
def Postfix(self, name):
|
|
||||||
return "inc" if (name in ["x","y"]) else "ld"
|
|
||||||
|
|
||||||
# Determines whether or not this routine has scalar arguments (alpha/beta)
|
|
||||||
def NoScalars(self):
|
|
||||||
return self.scalars == []
|
|
||||||
|
|
||||||
# Returns the upper-case names of these routines (all flavours)
|
|
||||||
def ShortNames(self):
|
|
||||||
return "/".join([f.name+self.name.upper() for f in self.flavours])
|
|
||||||
|
|
||||||
# As above, but excludes some
|
|
||||||
def ShortNamesTested(self):
|
|
||||||
names = [f.name+self.name.upper() for f in self.flavours]
|
|
||||||
if "H"+self.name.upper() in names: names.remove("H"+self.name.upper())
|
|
||||||
return "/".join(names)
|
|
||||||
|
|
||||||
# Determines which buffers go first (between alpha and beta) and which ones go after
|
|
||||||
def BuffersFirst(self):
|
|
||||||
if self.level == "2b":
|
|
||||||
return ["x","y"]
|
|
||||||
return ["ap","a","b","x"]
|
|
||||||
def BuffersSecond(self):
|
|
||||||
if self.level == "2b":
|
|
||||||
return ["ap","a","b","c"]
|
|
||||||
return ["y","c"]
|
|
||||||
|
|
||||||
# Distinguish between vectors and matrices
|
|
||||||
def BuffersVector(self):
|
|
||||||
return ["x","y"]
|
|
||||||
def BuffersMatrix(self):
|
|
||||||
return ["a","b","c","ap"]
|
|
||||||
|
|
||||||
# ==============================================================================================
|
|
||||||
|
|
||||||
# Retrieves a variable name for a specific input/output vector/matrix (e.g. 'x')
|
|
||||||
def Buffer(self, name):
|
|
||||||
if (name in self.inputs) or (name in self.outputs):
|
|
||||||
a = [name+"_buffer"]
|
|
||||||
b = [name+"_offset"]
|
|
||||||
c = [name+"_"+self.Postfix(name)] if (name not in self.BuffersWithoutLdInc()) else []
|
|
||||||
return [", ".join(a+b+c)]
|
|
||||||
return []
|
|
||||||
|
|
||||||
# As above but with a '_bis' suffix for the buffer name
|
|
||||||
def BufferBis(self, name):
|
|
||||||
#if (name in self.IndexBuffers()):
|
|
||||||
# return self.Buffer(name)
|
|
||||||
if (name in self.inputs) or (name in self.outputs):
|
|
||||||
a = [name+"_buffer_bis"]
|
|
||||||
b = [name+"_offset"]
|
|
||||||
c = [name+"_"+self.Postfix(name)] if (name not in self.BuffersWithoutLdInc()) else []
|
|
||||||
return [", ".join(a+b+c)]
|
|
||||||
return []
|
|
||||||
|
|
||||||
# As above but with data-types
|
|
||||||
def BufferDef(self, name):
|
|
||||||
prefix = "const " if (name in self.inputs) else ""
|
|
||||||
if (name in self.inputs) or (name in self.outputs):
|
|
||||||
a = [prefix+"cl_mem "+name+"_buffer"]
|
|
||||||
b = ["const size_t "+name+"_offset"]
|
|
||||||
c = ["const size_t "+name+"_"+self.Postfix(name)] if (name not in self.BuffersWithoutLdInc()) else []
|
|
||||||
return [", ".join(a+b+c)]
|
|
||||||
return []
|
|
||||||
|
|
||||||
# As above but with data-types
|
|
||||||
def BufferDefWrapperCL(self, name, flavour):
|
|
||||||
prefix = "const " if (name in self.inputs) else ""
|
|
||||||
if (name in self.inputs) or (name in self.outputs):
|
|
||||||
a = [prefix+"Buffer<"+flavour.buffertype+">& "+name+"_buffer"]
|
|
||||||
b = ["const size_t "+name+"_offset"]
|
|
||||||
c = ["const size_t "+name+"_"+self.Postfix(name)] if (name not in self.BuffersWithoutLdInc()) else []
|
|
||||||
return [", ".join(a+b+c)]
|
|
||||||
return []
|
|
||||||
|
|
||||||
# As above but as vectors
|
|
||||||
def BufferDefVector(self, name, flavour):
|
|
||||||
prefix = "const " if (name in self.inputs) else ""
|
|
||||||
if (name in self.inputs) or (name in self.outputs):
|
|
||||||
a = [prefix+"std::vector<"+flavour.buffertype+">& "+name+"_buffer"]
|
|
||||||
b = ["const size_t "+name+"_offset"]
|
|
||||||
c = ["const size_t "+name+"_"+self.Postfix(name)] if (name not in self.BuffersWithoutLdInc()) else []
|
|
||||||
return [", ".join(a+b+c)]
|
|
||||||
return []
|
|
||||||
|
|
||||||
# As above but with Claduc buffers
|
|
||||||
def BufferCladuc(self, name):
|
|
||||||
if (name in self.inputs) or (name in self.outputs):
|
|
||||||
buffertype = "unsigned int" if (name in self.IndexBuffers()) else self.template.buffertype
|
|
||||||
a = ["Buffer<"+buffertype+">("+name+"_buffer)"]
|
|
||||||
b = [name+"_offset"]
|
|
||||||
c = [name+"_"+self.Postfix(name)] if (name not in self.BuffersWithoutLdInc()) else []
|
|
||||||
return [", ".join(a+b+c)]
|
|
||||||
return []
|
|
||||||
|
|
||||||
# As above but with a static cast for clBLAS wrapper
|
|
||||||
def BufferWrapperCL(self, name):
|
|
||||||
if (name in self.inputs) or (name in self.outputs):
|
|
||||||
a = [name+"_buffer()"]
|
|
||||||
b = [name+"_offset"]
|
|
||||||
c = []
|
|
||||||
if (name in ["x","y"]):
|
|
||||||
c = ["static_cast<int>("+name+"_"+self.Postfix(name)+")"]
|
|
||||||
elif (name in ["a","b","c"]):
|
|
||||||
c = [name+"_"+self.Postfix(name)]
|
|
||||||
return [", ".join(a+b+c)]
|
|
||||||
return []
|
|
||||||
|
|
||||||
# As above but with a static cast for CBLAS wrapper
|
|
||||||
def BufferWrapperC(self, name, flavour):
|
|
||||||
prefix = "const " if (name in self.inputs) else ""
|
|
||||||
if (name in self.inputs) or (name in self.outputs):
|
|
||||||
if name == "sy1":
|
|
||||||
a = [name+"_buffer["+name+"_offset]"]
|
|
||||||
elif flavour.precision_name in ["C","Z"]:
|
|
||||||
a = ["reinterpret_cast<"+prefix+flavour.buffertype[:-1]+"*>(&"+name+"_buffer["+name+"_offset])"]
|
|
||||||
else:
|
|
||||||
a = ["&"+name+"_buffer["+name+"_offset]"]
|
|
||||||
c = []
|
|
||||||
if (name in ["x","y"]):
|
|
||||||
c = ["static_cast<int>("+name+"_"+self.Postfix(name)+")"]
|
|
||||||
elif (name in ["a","b","c"]):
|
|
||||||
c = [name+"_"+self.Postfix(name)]
|
|
||||||
return [", ".join(a+c)]
|
|
||||||
return []
|
|
||||||
|
|
||||||
# As above, but only data-types
|
|
||||||
def BufferType(self, name):
|
|
||||||
prefix = "const " if (name in self.inputs) else ""
|
|
||||||
if (name in self.inputs) or (name in self.outputs):
|
|
||||||
a = [prefix+"cl_mem"]
|
|
||||||
b = ["const size_t"]
|
|
||||||
c = ["const size_t"] if (name not in self.BuffersWithoutLdInc()) else []
|
|
||||||
return [", ".join(a+b+c)]
|
|
||||||
return []
|
|
||||||
|
|
||||||
# Retrieves the documentation of the buffers
|
|
||||||
def BufferDoc(self, name):
|
|
||||||
prefix = "const " if (name in self.inputs) else ""
|
|
||||||
inout = "input" if (name in self.inputs) else "output"
|
|
||||||
if (name in self.inputs) or (name in self.outputs):
|
|
||||||
math_name = name.upper()+" matrix" if (name in self.BuffersMatrix()) else name+" vector"
|
|
||||||
incld_description = "Leading dimension " if (name in self.BuffersMatrix()) else "Stride/increment "
|
|
||||||
a = ["`"+prefix+"cl_mem "+name+"_buffer`: OpenCL buffer to store the "+inout+" "+math_name+"."]
|
|
||||||
b = ["`const size_t "+name+"_offset`: The offset in elements from the start of the "+inout+" "+math_name+"."]
|
|
||||||
c = ["`const size_t "+name+"_"+self.Postfix(name)+"`: "+incld_description+"of the "+inout+" "+math_name+". This value must be greater than 0."] if (name not in self.BuffersWithoutLdInc()) else []
|
|
||||||
return a+b+c
|
|
||||||
return []
|
|
||||||
|
|
||||||
# ==============================================================================================
|
|
||||||
|
|
||||||
# Retrieves the name of a scalar (alpha/beta)
|
|
||||||
def Scalar(self, name):
|
|
||||||
if (name in self.scalars):
|
|
||||||
return [name]
|
|
||||||
return []
|
|
||||||
|
|
||||||
# As above, but converts from float to half
|
|
||||||
def ScalarHalfToFloat(self, name):
|
|
||||||
if name in self.scalars:
|
|
||||||
return ["HalfToFloat("+name+")"]
|
|
||||||
return []
|
|
||||||
|
|
||||||
# Retrieves the use of a scalar (alpha/beta)
|
|
||||||
def ScalarUse(self, name, flavour):
|
|
||||||
if name in self.scalars:
|
|
||||||
if name == "alpha":
|
|
||||||
return [flavour.UseAlpha()]
|
|
||||||
elif name == "beta":
|
|
||||||
return [flavour.UseBeta()]
|
|
||||||
return [name]
|
|
||||||
return []
|
|
||||||
|
|
||||||
# As above, but for the clBLAS wrapper
|
|
||||||
def ScalarUseWrapper(self, name, flavour):
|
|
||||||
if name in self.scalars:
|
|
||||||
if name == "alpha":
|
|
||||||
return [flavour.UseAlphaCL()]
|
|
||||||
elif name == "beta":
|
|
||||||
return [flavour.UseBetaCL()]
|
|
||||||
return [name]
|
|
||||||
return []
|
|
||||||
|
|
||||||
# As above, but for the CBLAS wrapper
|
|
||||||
def ScalarUseWrapperC(self, name, flavour):
|
|
||||||
if name in self.scalars:
|
|
||||||
if flavour.IsComplex(name):
|
|
||||||
return [name+"_array.data()"]
|
|
||||||
return [name]
|
|
||||||
return []
|
|
||||||
|
|
||||||
# Retrieves the definition of a scalar (alpha/beta)
|
|
||||||
def ScalarDef(self, name, flavour):
|
|
||||||
if name in self.scalars:
|
|
||||||
if name == "alpha":
|
|
||||||
return ["const "+flavour.alpha_cl+" "+name]
|
|
||||||
return ["const "+flavour.beta_cl+" "+name]
|
|
||||||
return []
|
|
||||||
|
|
||||||
# As above, but without 'cl_' prefix
|
|
||||||
def ScalarDefPlain(self, name, flavour):
|
|
||||||
if name in self.scalars:
|
|
||||||
if name == "alpha":
|
|
||||||
return ["const "+flavour.alpha_cpp+" "+name]
|
|
||||||
return ["const "+flavour.beta_cpp+" "+name]
|
|
||||||
return []
|
|
||||||
|
|
||||||
# Retrieves the type of a scalar (alpha/beta)
|
|
||||||
def ScalarType(self, name, flavour):
|
|
||||||
if name in self.scalars:
|
|
||||||
if name == "alpha":
|
|
||||||
return ["const "+flavour.alpha_cpp]
|
|
||||||
return ["const "+flavour.beta_cpp]
|
|
||||||
return []
|
|
||||||
|
|
||||||
# Retrieves the documentation of a scalar
|
|
||||||
def ScalarDoc(self, name):
|
|
||||||
if name in self.scalars:
|
|
||||||
if name == "alpha":
|
|
||||||
return ["`const "+self.template.alpha_cpp+" "+name+"`: Input scalar constant."]
|
|
||||||
return ["`const "+self.template.beta_cpp+" "+name+"`: Input scalar constant."]
|
|
||||||
return []
|
|
||||||
|
|
||||||
# ==============================================================================================
|
|
||||||
|
|
||||||
# Retrieves a list of comma-separated sizes (m, n, k)
|
|
||||||
def Sizes(self):
|
|
||||||
if self.sizes:
|
|
||||||
return [", ".join([s for s in self.sizes])]
|
|
||||||
return []
|
|
||||||
|
|
||||||
# Retrieves the definition of the sizes (m,n,k)
|
|
||||||
def SizesDef(self):
|
|
||||||
if self.sizes:
|
|
||||||
return [", ".join(["const size_t "+s for s in self.sizes])]
|
|
||||||
return []
|
|
||||||
|
|
||||||
# Retrieves the types of the sizes (m,n,k)
|
|
||||||
def SizesType(self):
|
|
||||||
if self.sizes:
|
|
||||||
return [", ".join(["const size_t" for s in self.sizes])]
|
|
||||||
return []
|
|
||||||
|
|
||||||
# Retrieves the documentation of the sizes
|
|
||||||
def SizesDoc(self):
|
|
||||||
if self.sizes:
|
|
||||||
definitions = ["`const size_t "+s+"`: Integer size argument. This value must be positive." for s in self.sizes]
|
|
||||||
return definitions
|
|
||||||
return []
|
|
||||||
|
|
||||||
# ==============================================================================================
|
|
||||||
|
|
||||||
# Retrieves a list of options
|
|
||||||
def Options(self):
|
|
||||||
if self.options:
|
|
||||||
return [", ".join(self.options)]
|
|
||||||
return []
|
|
||||||
|
|
||||||
# As above, but now casted to CLBlast data-types
|
|
||||||
def OptionsCast(self, indent):
|
|
||||||
if self.options:
|
|
||||||
options = ["static_cast<clblast::"+OptionToCLBlast(o)+">("+o+")" for o in self.options]
|
|
||||||
return [(",\n"+indent).join(options)]
|
|
||||||
return []
|
|
||||||
|
|
||||||
# Retrieves the definitions of the options (layout, transpose, side, etc.)
|
|
||||||
def OptionsDef(self):
|
|
||||||
if self.options:
|
|
||||||
definitions = ["const "+OptionToCLBlast(o)+" "+o for o in self.options]
|
|
||||||
return [", ".join(definitions)]
|
|
||||||
return []
|
|
||||||
|
|
||||||
# As above, but now using clBLAS data-types
|
|
||||||
def OptionsDefWrapperCL(self):
|
|
||||||
if self.options:
|
|
||||||
definitions = ["const "+OptionToWrapperCL(o)+" "+o for o in self.options]
|
|
||||||
return [", ".join(definitions)]
|
|
||||||
return []
|
|
||||||
|
|
||||||
# As above, but now using CBLAS data-types
|
|
||||||
def OptionsDefWrapperC(self):
|
|
||||||
if self.options:
|
|
||||||
definitions = ["const "+OptionToWrapperC(o)+" "+o for o in self.options]
|
|
||||||
return [", ".join(definitions)]
|
|
||||||
return []
|
|
||||||
|
|
||||||
# Retrieves the types of the options (layout, transpose, side, etc.)
|
|
||||||
def OptionsType(self):
|
|
||||||
if self.options:
|
|
||||||
definitions = ["const "+OptionToCLBlast(o) for o in self.options]
|
|
||||||
return [", ".join(definitions)]
|
|
||||||
return []
|
|
||||||
|
|
||||||
# Retrieves the documentation of the options
|
|
||||||
def OptionsDoc(self):
|
|
||||||
if self.options:
|
|
||||||
definitions = ["`const "+OptionToCLBlast(o)+" "+o+"`: "+OptionToDoc(o) for o in self.options]
|
|
||||||
return definitions
|
|
||||||
return []
|
|
||||||
|
|
||||||
# ==============================================================================================
|
|
||||||
|
|
||||||
# Retrieves a combination of all the argument names (no types)
|
|
||||||
def Arguments(self):
|
|
||||||
return (self.Options() + self.Sizes() +
|
|
||||||
list(chain(*[self.Buffer(b) for b in self.ScalarBuffersFirst()])) +
|
|
||||||
self.Scalar("alpha") +
|
|
||||||
list(chain(*[self.Buffer(b) for b in self.BuffersFirst()])) +
|
|
||||||
self.Scalar("beta") +
|
|
||||||
list(chain(*[self.Buffer(b) for b in self.BuffersSecond()])) +
|
|
||||||
list(chain(*[self.Buffer(b) for b in self.ScalarBuffersSecond()])) +
|
|
||||||
list(chain(*[self.Scalar(s) for s in self.OtherScalars()])))
|
|
||||||
|
|
||||||
# As above, but with conversions from half to float
|
|
||||||
def ArgumentsHalf(self):
|
|
||||||
return (self.Options() + self.Sizes() +
|
|
||||||
list(chain(*[self.BufferBis(b) for b in self.ScalarBuffersFirst()])) +
|
|
||||||
self.ScalarHalfToFloat("alpha") +
|
|
||||||
list(chain(*[self.BufferBis(b) for b in self.BuffersFirst()])) +
|
|
||||||
self.ScalarHalfToFloat("beta") +
|
|
||||||
list(chain(*[self.BufferBis(b) for b in self.BuffersSecond()])) +
|
|
||||||
list(chain(*[self.BufferBis(b) for b in self.ScalarBuffersSecond()])) +
|
|
||||||
list(chain(*[self.Scalar(s) for s in self.OtherScalars()])))
|
|
||||||
|
|
||||||
# Retrieves a combination of all the argument names, with Claduc casts
|
|
||||||
def ArgumentsCladuc(self, flavour, indent):
|
|
||||||
return (self.Options() + self.Sizes() +
|
|
||||||
list(chain(*[self.BufferCladuc(b) for b in self.ScalarBuffersFirst()])) +
|
|
||||||
self.Scalar("alpha") +
|
|
||||||
list(chain(*[self.BufferCladuc(b) for b in self.BuffersFirst()])) +
|
|
||||||
self.Scalar("beta") +
|
|
||||||
list(chain(*[self.BufferCladuc(b) for b in self.BuffersSecond()])) +
|
|
||||||
list(chain(*[self.BufferCladuc(b) for b in self.ScalarBuffersSecond()])) +
|
|
||||||
list(chain(*[self.Scalar(s) for s in self.OtherScalars()])))
|
|
||||||
|
|
||||||
# As above, but with CLBlast casts
|
|
||||||
def ArgumentsCast(self, flavour, indent):
|
|
||||||
return (self.OptionsCast(indent) + self.Sizes() +
|
|
||||||
list(chain(*[self.Buffer(b) for b in self.ScalarBuffersFirst()])) +
|
|
||||||
self.ScalarUse("alpha", flavour) +
|
|
||||||
list(chain(*[self.Buffer(b) for b in self.BuffersFirst()])) +
|
|
||||||
self.ScalarUse("beta", flavour) +
|
|
||||||
list(chain(*[self.Buffer(b) for b in self.BuffersSecond()])) +
|
|
||||||
list(chain(*[self.Buffer(b) for b in self.ScalarBuffersSecond()])) +
|
|
||||||
list(chain(*[self.ScalarUse(s, flavour) for s in self.OtherScalars()])))
|
|
||||||
|
|
||||||
# As above, but for the clBLAS wrapper
|
|
||||||
def ArgumentsWrapperCL(self, flavour):
|
|
||||||
return (self.Options() + self.Sizes() +
|
|
||||||
list(chain(*[self.BufferWrapperCL(b) for b in self.ScalarBuffersFirst()])) +
|
|
||||||
self.ScalarUseWrapper("alpha", flavour) +
|
|
||||||
list(chain(*[self.BufferWrapperCL(b) for b in self.BuffersFirst()])) +
|
|
||||||
self.ScalarUseWrapper("beta", flavour) +
|
|
||||||
list(chain(*[self.BufferWrapperCL(b) for b in self.BuffersSecond()])) +
|
|
||||||
list(chain(*[self.BufferWrapperCL(b) for b in self.ScalarBuffersSecond()])) +
|
|
||||||
list(chain(*[self.ScalarUseWrapper(s, flavour) for s in self.OtherScalars()])))
|
|
||||||
|
|
||||||
# As above, but for the CBLAS wrapper
|
|
||||||
def ArgumentsWrapperC(self, flavour):
|
|
||||||
return (self.Options() + self.Sizes() +
|
|
||||||
self.ScalarUseWrapperC("alpha", flavour) +
|
|
||||||
list(chain(*[self.BufferWrapperC(b, flavour) for b in self.BuffersFirst()])) +
|
|
||||||
self.ScalarUseWrapperC("beta", flavour) +
|
|
||||||
list(chain(*[self.BufferWrapperC(b, flavour) for b in self.BuffersSecond()])) +
|
|
||||||
list(chain(*[self.BufferWrapperC(b, flavour) for b in self.ScalarBuffersSecond()])) +
|
|
||||||
list(chain(*[self.ScalarUseWrapperC(s, flavour) for s in self.OtherScalars()])))
|
|
||||||
|
|
||||||
# Retrieves a combination of all the argument definitions
|
|
||||||
def ArgumentsDef(self, flavour):
|
|
||||||
return (self.OptionsDef() + self.SizesDef() +
|
|
||||||
list(chain(*[self.BufferDef(b) for b in self.ScalarBuffersFirst()])) +
|
|
||||||
self.ScalarDef("alpha", flavour) +
|
|
||||||
list(chain(*[self.BufferDef(b) for b in self.BuffersFirst()])) +
|
|
||||||
self.ScalarDef("beta", flavour) +
|
|
||||||
list(chain(*[self.BufferDef(b) for b in self.BuffersSecond()])) +
|
|
||||||
list(chain(*[self.BufferDef(b) for b in self.ScalarBuffersSecond()])) +
|
|
||||||
list(chain(*[self.ScalarDef(s, flavour) for s in self.OtherScalars()])))
|
|
||||||
|
|
||||||
# As above, but clBLAS wrapper plain datatypes
|
|
||||||
def ArgumentsDefWrapperCL(self, flavour):
|
|
||||||
return (self.OptionsDefWrapperCL() + self.SizesDef() +
|
|
||||||
list(chain(*[self.BufferDefWrapperCL(b, flavour) for b in self.ScalarBuffersFirst()])) +
|
|
||||||
self.ScalarDefPlain("alpha", flavour) +
|
|
||||||
list(chain(*[self.BufferDefWrapperCL(b, flavour) for b in self.BuffersFirst()])) +
|
|
||||||
self.ScalarDefPlain("beta", flavour) +
|
|
||||||
list(chain(*[self.BufferDefWrapperCL(b, flavour) for b in self.BuffersSecond()])) +
|
|
||||||
list(chain(*[self.BufferDefWrapperCL(b, flavour) for b in self.ScalarBuffersSecond()])) +
|
|
||||||
list(chain(*[self.ScalarDefPlain(s, flavour) for s in self.OtherScalars()])))
|
|
||||||
|
|
||||||
# As above, but CBLAS wrapper plain datatypes
|
|
||||||
def ArgumentsDefWrapperC(self, flavour):
|
|
||||||
return (self.OptionsDefWrapperC() + self.SizesDef() +
|
|
||||||
list(chain(*[self.BufferDefVector(b, flavour) for b in self.ScalarBuffersFirst()])) +
|
|
||||||
self.ScalarDefPlain("alpha", flavour) +
|
|
||||||
list(chain(*[self.BufferDefVector(b, flavour) for b in self.BuffersFirst()])) +
|
|
||||||
self.ScalarDefPlain("beta", flavour) +
|
|
||||||
list(chain(*[self.BufferDefVector(b, flavour) for b in self.BuffersSecond()])) +
|
|
||||||
list(chain(*[self.BufferDefVector(b, flavour) for b in self.ScalarBuffersSecond()])) +
|
|
||||||
list(chain(*[self.ScalarDefPlain(s, flavour) for s in self.OtherScalars()])))
|
|
||||||
|
|
||||||
# Retrieves a combination of all the argument types
|
|
||||||
def ArgumentsType(self, flavour):
|
|
||||||
return (self.OptionsType() + self.SizesType() +
|
|
||||||
list(chain(*[self.BufferType(b) for b in self.ScalarBuffersFirst()])) +
|
|
||||||
self.ScalarType("alpha", flavour) +
|
|
||||||
list(chain(*[self.BufferType(b) for b in self.BuffersFirst()])) +
|
|
||||||
self.ScalarType("beta", flavour) +
|
|
||||||
list(chain(*[self.BufferType(b) for b in self.BuffersSecond()])) +
|
|
||||||
list(chain(*[self.BufferType(b) for b in self.ScalarBuffersSecond()])) +
|
|
||||||
list(chain(*[self.ScalarType(s, flavour) for s in self.OtherScalars()])))
|
|
||||||
|
|
||||||
# Retrieves a combination of all the argument types
|
|
||||||
def ArgumentsDoc(self):
|
|
||||||
return (self.OptionsDoc() + self.SizesDoc() +
|
|
||||||
list(chain(*[self.BufferDoc(b) for b in self.ScalarBuffersFirst()])) +
|
|
||||||
list(chain(*[self.BufferDoc(b) for b in self.ScalarBuffersFirst()])) +
|
|
||||||
self.ScalarDoc("alpha") +
|
|
||||||
list(chain(*[self.BufferDoc(b) for b in self.BuffersFirst()])) +
|
|
||||||
self.ScalarDoc("beta") +
|
|
||||||
list(chain(*[self.BufferDoc(b) for b in self.BuffersSecond()])) +
|
|
||||||
list(chain(*[self.BufferDoc(b) for b in self.ScalarBuffersSecond()])) +
|
|
||||||
list(chain(*[self.ScalarDoc(s) for s in self.OtherScalars()])))
|
|
||||||
|
|
||||||
# ==============================================================================================
|
|
||||||
|
|
||||||
# Retrieves a list of routine requirements for documentation
|
|
||||||
def RequirementsDoc(self):
|
|
||||||
return self.requirements
|
|
||||||
|
|
||||||
# ==============================================================================================
|
|
||||||
|
|
||||||
# Retrieves the C++ templated definition for a routine
|
|
||||||
def RoutineHeaderCPP(self, spaces, default_event):
|
|
||||||
indent = " "*(spaces + self.Length())
|
|
||||||
result = "template <"+self.template.name+">\n"
|
|
||||||
result += "StatusCode "+self.name.capitalize()+"("
|
|
||||||
result += (",\n"+indent).join([a for a in self.ArgumentsDef(self.template)])
|
|
||||||
result += ",\n"+indent+"cl_command_queue* queue, cl_event* event"+default_event+")"
|
|
||||||
return result
|
|
||||||
|
|
||||||
# As above, but now without variable names
|
|
||||||
def RoutineHeaderTypeCPP(self, spaces):
|
|
||||||
indent = " "*(spaces + self.Length())
|
|
||||||
result = "template <"+self.template.name+">\n"
|
|
||||||
result += "StatusCode "+self.name.capitalize()+"("
|
|
||||||
result += (",\n"+indent).join([a for a in self.ArgumentsType(self.template)])
|
|
||||||
result += ",\n"+indent+"cl_command_queue*, cl_event*)"
|
|
||||||
return result
|
|
||||||
|
|
||||||
# As above, but now for C
|
|
||||||
def RoutineHeaderC(self, flavour, spaces, extra_qualifier):
|
|
||||||
indent = " "*(spaces + self.Length())
|
|
||||||
result = "StatusCode"+extra_qualifier+" CLBlast"+flavour.name+self.name+"("
|
|
||||||
result += (",\n"+indent).join([a for a in self.ArgumentsDef(flavour)])
|
|
||||||
result += ",\n"+indent+"cl_command_queue* queue, cl_event* event)"
|
|
||||||
return result
|
|
||||||
|
|
||||||
# As above, but now for the clBLAS wrapper
|
|
||||||
def RoutineHeaderWrapperCL(self, flavour, def_only, spaces):
|
|
||||||
template = "<"+flavour.template+">" if self.NoScalars() and not def_only else ""
|
|
||||||
indent = " "*(spaces + self.Length() + len(template))
|
|
||||||
result = ""
|
|
||||||
if self.NoScalars():
|
|
||||||
result += "template <"
|
|
||||||
if def_only:
|
|
||||||
result += flavour.name
|
|
||||||
result += ">\n"
|
|
||||||
result += "clblasStatus clblasX"+self.name+template+"("
|
|
||||||
result += (",\n"+indent).join([a for a in self.ArgumentsDefWrapperCL(flavour)])
|
|
||||||
result += ",\n"+indent+"cl_uint num_queues, cl_command_queue *queues"
|
|
||||||
result += ",\n"+indent+"cl_uint num_wait_events, const cl_event *wait_events, cl_event *events)"
|
|
||||||
return result
|
|
||||||
|
|
||||||
# As above, but now for the CBLAS wrapper
|
|
||||||
def RoutineHeaderWrapperC(self, flavour, def_only, spaces):
|
|
||||||
indent = " "*(spaces + self.Length())
|
|
||||||
result = "void cblasX"+self.name+"("
|
|
||||||
result += (",\n"+indent).join([a for a in self.ArgumentsDefWrapperC(flavour)])+")"
|
|
||||||
return result
|
|
||||||
|
|
||||||
# ==================================================================================================
|
|
|
@ -23,6 +23,9 @@ namespace clblast {
|
||||||
// Stores the compiled binary or IR in the cache
|
// Stores the compiled binary or IR in the cache
|
||||||
void StoreBinaryToCache(const std::string &binary, const std::string &device_name,
|
void StoreBinaryToCache(const std::string &binary, const std::string &device_name,
|
||||||
const Precision &precision, const std::string &routine_name) {
|
const Precision &precision, const std::string &routine_name) {
|
||||||
|
#ifdef VERBOSE
|
||||||
|
printf("[DEBUG] Storing binary in cache\n");
|
||||||
|
#endif
|
||||||
binary_cache_mutex_.lock();
|
binary_cache_mutex_.lock();
|
||||||
binary_cache_.push_back(BinaryCache{binary, device_name, precision, routine_name});
|
binary_cache_.push_back(BinaryCache{binary, device_name, precision, routine_name});
|
||||||
binary_cache_mutex_.unlock();
|
binary_cache_mutex_.unlock();
|
||||||
|
@ -31,8 +34,11 @@ void StoreBinaryToCache(const std::string &binary, const std::string &device_nam
|
||||||
// Stores the compiled program in the cache
|
// Stores the compiled program in the cache
|
||||||
void StoreProgramToCache(const Program &program, const Context &context,
|
void StoreProgramToCache(const Program &program, const Context &context,
|
||||||
const Precision &precision, const std::string &routine_name) {
|
const Precision &precision, const std::string &routine_name) {
|
||||||
|
#ifdef VERBOSE
|
||||||
|
printf("[DEBUG] Storing program in cache\n");
|
||||||
|
#endif
|
||||||
program_cache_mutex_.lock();
|
program_cache_mutex_.lock();
|
||||||
program_cache_.push_back(ProgramCache{program, context.pointer(), precision, routine_name});
|
program_cache_.push_back(ProgramCache{program, context(), precision, routine_name});
|
||||||
program_cache_mutex_.unlock();
|
program_cache_mutex_.unlock();
|
||||||
}
|
}
|
||||||
|
|
||||||
|
@ -40,6 +46,9 @@ void StoreProgramToCache(const Program &program, const Context &context,
|
||||||
// otherwise.
|
// otherwise.
|
||||||
const std::string& GetBinaryFromCache(const std::string &device_name, const Precision &precision,
|
const std::string& GetBinaryFromCache(const std::string &device_name, const Precision &precision,
|
||||||
const std::string &routine_name) {
|
const std::string &routine_name) {
|
||||||
|
#ifdef VERBOSE
|
||||||
|
printf("[DEBUG] Retrieving binary from cache\n");
|
||||||
|
#endif
|
||||||
binary_cache_mutex_.lock();
|
binary_cache_mutex_.lock();
|
||||||
for (auto &cached_binary: binary_cache_) {
|
for (auto &cached_binary: binary_cache_) {
|
||||||
if (cached_binary.MatchInCache(device_name, precision, routine_name)) {
|
if (cached_binary.MatchInCache(device_name, precision, routine_name)) {
|
||||||
|
@ -55,9 +64,12 @@ const std::string& GetBinaryFromCache(const std::string &device_name, const Prec
|
||||||
// otherwise.
|
// otherwise.
|
||||||
const Program& GetProgramFromCache(const Context &context, const Precision &precision,
|
const Program& GetProgramFromCache(const Context &context, const Precision &precision,
|
||||||
const std::string &routine_name) {
|
const std::string &routine_name) {
|
||||||
|
#ifdef VERBOSE
|
||||||
|
printf("[DEBUG] Retrieving program from cache\n");
|
||||||
|
#endif
|
||||||
program_cache_mutex_.lock();
|
program_cache_mutex_.lock();
|
||||||
for (auto &cached_program: program_cache_) {
|
for (auto &cached_program: program_cache_) {
|
||||||
if (cached_program.MatchInCache(context.pointer(), precision, routine_name)) {
|
if (cached_program.MatchInCache(context(), precision, routine_name)) {
|
||||||
program_cache_mutex_.unlock();
|
program_cache_mutex_.unlock();
|
||||||
return cached_program.program;
|
return cached_program.program;
|
||||||
}
|
}
|
||||||
|
@ -85,7 +97,7 @@ bool ProgramIsInCache(const Context &context, const Precision &precision,
|
||||||
const std::string &routine_name) {
|
const std::string &routine_name) {
|
||||||
program_cache_mutex_.lock();
|
program_cache_mutex_.lock();
|
||||||
for (auto &cached_program: program_cache_) {
|
for (auto &cached_program: program_cache_) {
|
||||||
if (cached_program.MatchInCache(context.pointer(), precision, routine_name)) {
|
if (cached_program.MatchInCache(context(), precision, routine_name)) {
|
||||||
program_cache_mutex_.unlock();
|
program_cache_mutex_.unlock();
|
||||||
return true;
|
return true;
|
||||||
}
|
}
|
||||||
|
|
|
@ -48,14 +48,14 @@ static std::mutex binary_cache_mutex_;
|
||||||
// The cache of compiled OpenCL programs, along with some meta-data
|
// The cache of compiled OpenCL programs, along with some meta-data
|
||||||
struct ProgramCache {
|
struct ProgramCache {
|
||||||
Program program;
|
Program program;
|
||||||
ContextPointer context_ptr;
|
cl_context context;
|
||||||
Precision precision;
|
Precision precision;
|
||||||
std::string routine_name_;
|
std::string routine_name_;
|
||||||
|
|
||||||
// Finds out whether the properties match
|
// Finds out whether the properties match
|
||||||
bool MatchInCache(const ContextPointer ref_context, const Precision &ref_precision,
|
bool MatchInCache(const cl_context ref_context, const Precision &ref_precision,
|
||||||
const std::string &ref_routine) {
|
const std::string &ref_routine) {
|
||||||
return (context_ptr == ref_context &&
|
return (context == ref_context &&
|
||||||
precision == ref_precision &&
|
precision == ref_precision &&
|
||||||
routine_name_ == ref_routine);
|
routine_name_ == ref_routine);
|
||||||
}
|
}
|
||||||
|
|
|
@ -16,7 +16,6 @@
|
||||||
#include <string>
|
#include <string>
|
||||||
|
|
||||||
#include "clblast.h"
|
#include "clblast.h"
|
||||||
#include "public_api.hpp"
|
|
||||||
#include "cache.hpp"
|
#include "cache.hpp"
|
||||||
|
|
||||||
// BLAS level-1 includes
|
// BLAS level-1 includes
|
||||||
|
|
116
src/clpp11.hpp
116
src/clpp11.hpp
|
@ -72,15 +72,24 @@ inline void CheckError(const cl_int status) {
|
||||||
class Event {
|
class Event {
|
||||||
public:
|
public:
|
||||||
|
|
||||||
// Constructor based on the regular OpenCL data-type
|
// Constructor based on the regular OpenCL data-type: memory management is handled elsewhere
|
||||||
explicit Event(const cl_event event): event_(event) { }
|
explicit Event(const cl_event event):
|
||||||
|
event_(new cl_event) {
|
||||||
|
*event_ = event;
|
||||||
|
}
|
||||||
|
|
||||||
// Regular constructor
|
// Regular constructor with memory management
|
||||||
explicit Event(): event_(nullptr) { }
|
explicit Event():
|
||||||
|
event_(new cl_event, [](cl_event* e) {
|
||||||
|
if (*e) { CheckError(clReleaseEvent(*e)); }
|
||||||
|
delete e;
|
||||||
|
}) {
|
||||||
|
*event_ = nullptr;
|
||||||
|
}
|
||||||
|
|
||||||
// Waits for completion of this event
|
// Waits for completion of this event
|
||||||
void WaitForCompletion() const {
|
void WaitForCompletion() const {
|
||||||
CheckError(clWaitForEvents(1, &event_));
|
CheckError(clWaitForEvents(1, &(*event_)));
|
||||||
}
|
}
|
||||||
|
|
||||||
// Retrieves the elapsed time of the last recorded event. Note that no error checking is done on
|
// Retrieves the elapsed time of the last recorded event. Note that no error checking is done on
|
||||||
|
@ -89,20 +98,22 @@ class Event {
|
||||||
float GetElapsedTime() const {
|
float GetElapsedTime() const {
|
||||||
WaitForCompletion();
|
WaitForCompletion();
|
||||||
auto bytes = size_t{0};
|
auto bytes = size_t{0};
|
||||||
clGetEventProfilingInfo(event_, CL_PROFILING_COMMAND_START, 0, nullptr, &bytes);
|
clGetEventProfilingInfo(*event_, CL_PROFILING_COMMAND_START, 0, nullptr, &bytes);
|
||||||
auto time_start = size_t{0};
|
auto time_start = size_t{0};
|
||||||
clGetEventProfilingInfo(event_, CL_PROFILING_COMMAND_START, bytes, &time_start, nullptr);
|
clGetEventProfilingInfo(*event_, CL_PROFILING_COMMAND_START, bytes, &time_start, nullptr);
|
||||||
clGetEventProfilingInfo(event_, CL_PROFILING_COMMAND_END, 0, nullptr, &bytes);
|
clGetEventProfilingInfo(*event_, CL_PROFILING_COMMAND_END, 0, nullptr, &bytes);
|
||||||
auto time_end = size_t{0};
|
auto time_end = size_t{0};
|
||||||
clGetEventProfilingInfo(event_, CL_PROFILING_COMMAND_END, bytes, &time_end, nullptr);
|
clGetEventProfilingInfo(*event_, CL_PROFILING_COMMAND_END, bytes, &time_end, nullptr);
|
||||||
return (time_end - time_start) * 1.0e-6f;
|
return (time_end - time_start) * 1.0e-6f;
|
||||||
}
|
}
|
||||||
|
|
||||||
// Accessor to the private data-member
|
// Accessor to the private data-member
|
||||||
cl_event& operator()() { return event_; }
|
cl_event& operator()() { return *event_; }
|
||||||
cl_event* pointer() { return &event_; }
|
const cl_event& operator()() const { return *event_; }
|
||||||
|
cl_event* pointer() { return &(*event_); }
|
||||||
|
const cl_event* pointer() const { return &(*event_); }
|
||||||
private:
|
private:
|
||||||
cl_event event_;
|
std::shared_ptr<cl_event> event_;
|
||||||
};
|
};
|
||||||
|
|
||||||
// Pointer to an OpenCL event
|
// Pointer to an OpenCL event
|
||||||
|
@ -163,6 +174,15 @@ class Device {
|
||||||
|
|
||||||
// Methods to retrieve device information
|
// Methods to retrieve device information
|
||||||
std::string Version() const { return GetInfoString(CL_DEVICE_VERSION); }
|
std::string Version() const { return GetInfoString(CL_DEVICE_VERSION); }
|
||||||
|
size_t VersionNumber() const
|
||||||
|
{
|
||||||
|
std::string version_string = Version().substr(7);
|
||||||
|
// Space separates the end of the OpenCL version number from the beginning of the
|
||||||
|
// vendor-specific information.
|
||||||
|
size_t next_whitespace = version_string.find(' ');
|
||||||
|
size_t version = (size_t) (100.0 * std::stod(version_string.substr(0, next_whitespace)));
|
||||||
|
return version;
|
||||||
|
}
|
||||||
std::string Vendor() const { return GetInfoString(CL_DEVICE_VENDOR); }
|
std::string Vendor() const { return GetInfoString(CL_DEVICE_VENDOR); }
|
||||||
std::string Name() const { return GetInfoString(CL_DEVICE_NAME); }
|
std::string Name() const { return GetInfoString(CL_DEVICE_NAME); }
|
||||||
std::string Type() const {
|
std::string Type() const {
|
||||||
|
@ -176,24 +196,32 @@ class Device {
|
||||||
}
|
}
|
||||||
size_t MaxWorkGroupSize() const { return GetInfo<size_t>(CL_DEVICE_MAX_WORK_GROUP_SIZE); }
|
size_t MaxWorkGroupSize() const { return GetInfo<size_t>(CL_DEVICE_MAX_WORK_GROUP_SIZE); }
|
||||||
size_t MaxWorkItemDimensions() const {
|
size_t MaxWorkItemDimensions() const {
|
||||||
return GetInfo(CL_DEVICE_MAX_WORK_ITEM_DIMENSIONS);
|
return static_cast<size_t>(GetInfo<cl_uint>(CL_DEVICE_MAX_WORK_ITEM_DIMENSIONS));
|
||||||
}
|
}
|
||||||
std::vector<size_t> MaxWorkItemSizes() const {
|
std::vector<size_t> MaxWorkItemSizes() const {
|
||||||
return GetInfoVector<size_t>(CL_DEVICE_MAX_WORK_ITEM_SIZES);
|
return GetInfoVector<size_t>(CL_DEVICE_MAX_WORK_ITEM_SIZES);
|
||||||
}
|
}
|
||||||
size_t LocalMemSize() const {
|
cl_ulong LocalMemSize() const {
|
||||||
return static_cast<size_t>(GetInfo<cl_ulong>(CL_DEVICE_LOCAL_MEM_SIZE));
|
return GetInfo<cl_ulong>(CL_DEVICE_LOCAL_MEM_SIZE);
|
||||||
}
|
}
|
||||||
std::string Capabilities() const { return GetInfoString(CL_DEVICE_EXTENSIONS); }
|
std::string Capabilities() const { return GetInfoString(CL_DEVICE_EXTENSIONS); }
|
||||||
size_t CoreClock() const { return GetInfo(CL_DEVICE_MAX_CLOCK_FREQUENCY); }
|
size_t CoreClock() const {
|
||||||
size_t ComputeUnits() const { return GetInfo(CL_DEVICE_MAX_COMPUTE_UNITS); }
|
return static_cast<size_t>(GetInfo<cl_uint>(CL_DEVICE_MAX_CLOCK_FREQUENCY));
|
||||||
size_t MemorySize() const { return GetInfo(CL_DEVICE_GLOBAL_MEM_SIZE); }
|
}
|
||||||
size_t MaxAllocSize() const { return GetInfo(CL_DEVICE_MAX_MEM_ALLOC_SIZE); }
|
size_t ComputeUnits() const {
|
||||||
|
return static_cast<size_t>(GetInfo<cl_uint>(CL_DEVICE_MAX_COMPUTE_UNITS));
|
||||||
|
}
|
||||||
|
unsigned long MemorySize() const {
|
||||||
|
return static_cast<unsigned long>(GetInfo<cl_ulong>(CL_DEVICE_GLOBAL_MEM_SIZE));
|
||||||
|
}
|
||||||
|
unsigned long MaxAllocSize() const {
|
||||||
|
return static_cast<unsigned long>(GetInfo<cl_ulong>(CL_DEVICE_MAX_MEM_ALLOC_SIZE));
|
||||||
|
}
|
||||||
size_t MemoryClock() const { return 0; } // Not exposed in OpenCL
|
size_t MemoryClock() const { return 0; } // Not exposed in OpenCL
|
||||||
size_t MemoryBusWidth() const { return 0; } // Not exposed in OpenCL
|
size_t MemoryBusWidth() const { return 0; } // Not exposed in OpenCL
|
||||||
|
|
||||||
// Configuration-validity checks
|
// Configuration-validity checks
|
||||||
bool IsLocalMemoryValid(const size_t local_mem_usage) const {
|
bool IsLocalMemoryValid(const cl_ulong local_mem_usage) const {
|
||||||
return (local_mem_usage <= LocalMemSize());
|
return (local_mem_usage <= LocalMemSize());
|
||||||
}
|
}
|
||||||
bool IsThreadConfigValid(const std::vector<size_t> &local) const {
|
bool IsThreadConfigValid(const std::vector<size_t> &local) const {
|
||||||
|
@ -211,6 +239,8 @@ class Device {
|
||||||
bool IsCPU() const { return Type() == "CPU"; }
|
bool IsCPU() const { return Type() == "CPU"; }
|
||||||
bool IsGPU() const { return Type() == "GPU"; }
|
bool IsGPU() const { return Type() == "GPU"; }
|
||||||
bool IsAMD() const { return Vendor() == "AMD" || Vendor() == "Advanced Micro Devices, Inc."; }
|
bool IsAMD() const { return Vendor() == "AMD" || Vendor() == "Advanced Micro Devices, Inc."; }
|
||||||
|
bool IsNVIDIA() const { return Vendor() == "NVIDIA" || Vendor() == "NVIDIA Corporation"; }
|
||||||
|
bool IsIntel() const { return Vendor() == "Intel" || Vendor() == "GenuineIntel"; }
|
||||||
bool IsARM() const { return Vendor() == "ARM"; }
|
bool IsARM() const { return Vendor() == "ARM"; }
|
||||||
|
|
||||||
// Accessor to the private data-member
|
// Accessor to the private data-member
|
||||||
|
@ -227,13 +257,6 @@ class Device {
|
||||||
CheckError(clGetDeviceInfo(device_, info, bytes, &result, nullptr));
|
CheckError(clGetDeviceInfo(device_, info, bytes, &result, nullptr));
|
||||||
return result;
|
return result;
|
||||||
}
|
}
|
||||||
size_t GetInfo(const cl_device_info info) const {
|
|
||||||
auto bytes = size_t{0};
|
|
||||||
CheckError(clGetDeviceInfo(device_, info, 0, nullptr, &bytes));
|
|
||||||
auto result = cl_uint(0);
|
|
||||||
CheckError(clGetDeviceInfo(device_, info, bytes, &result, nullptr));
|
|
||||||
return static_cast<size_t>(result);
|
|
||||||
}
|
|
||||||
template <typename T>
|
template <typename T>
|
||||||
std::vector<T> GetInfoVector(const cl_device_info info) const {
|
std::vector<T> GetInfoVector(const cl_device_info info) const {
|
||||||
auto bytes = size_t{0};
|
auto bytes = size_t{0};
|
||||||
|
@ -386,8 +409,16 @@ class Queue {
|
||||||
delete s; }) {
|
delete s; }) {
|
||||||
auto status = CL_SUCCESS;
|
auto status = CL_SUCCESS;
|
||||||
#ifdef CL_VERSION_2_0
|
#ifdef CL_VERSION_2_0
|
||||||
|
size_t ocl_version = device.VersionNumber();
|
||||||
|
if (ocl_version >= 200)
|
||||||
|
{
|
||||||
cl_queue_properties properties[] = {CL_QUEUE_PROPERTIES, CL_QUEUE_PROFILING_ENABLE, 0};
|
cl_queue_properties properties[] = {CL_QUEUE_PROPERTIES, CL_QUEUE_PROFILING_ENABLE, 0};
|
||||||
*queue_ = clCreateCommandQueueWithProperties(context(), device(), properties, &status);
|
*queue_ = clCreateCommandQueueWithProperties(context(), device(), properties, &status);
|
||||||
|
}
|
||||||
|
else
|
||||||
|
{
|
||||||
|
*queue_ = clCreateCommandQueue(context(), device(), CL_QUEUE_PROFILING_ENABLE, &status);
|
||||||
|
}
|
||||||
#else
|
#else
|
||||||
*queue_ = clCreateCommandQueue(context(), device(), CL_QUEUE_PROFILING_ENABLE, &status);
|
*queue_ = clCreateCommandQueue(context(), device(), CL_QUEUE_PROFILING_ENABLE, &status);
|
||||||
#endif
|
#endif
|
||||||
|
@ -627,15 +658,25 @@ class Kernel {
|
||||||
}
|
}
|
||||||
|
|
||||||
// Retrieves the amount of local memory used per work-group for this kernel
|
// Retrieves the amount of local memory used per work-group for this kernel
|
||||||
size_t LocalMemUsage(const Device &device) const {
|
cl_ulong LocalMemUsage(const Device &device) const {
|
||||||
auto bytes = size_t{0};
|
auto bytes = size_t{0};
|
||||||
auto query = cl_kernel_work_group_info{CL_KERNEL_LOCAL_MEM_SIZE};
|
auto query = cl_kernel_work_group_info{CL_KERNEL_LOCAL_MEM_SIZE};
|
||||||
CheckError(clGetKernelWorkGroupInfo(*kernel_, device(), query, 0, nullptr, &bytes));
|
CheckError(clGetKernelWorkGroupInfo(*kernel_, device(), query, 0, nullptr, &bytes));
|
||||||
auto result = size_t{0};
|
auto result = cl_ulong{0};
|
||||||
CheckError(clGetKernelWorkGroupInfo(*kernel_, device(), query, bytes, &result, nullptr));
|
CheckError(clGetKernelWorkGroupInfo(*kernel_, device(), query, bytes, &result, nullptr));
|
||||||
return result;
|
return result;
|
||||||
}
|
}
|
||||||
|
|
||||||
|
// Retrieves the name of the kernel
|
||||||
|
std::string GetFunctionName() {
|
||||||
|
auto bytes = size_t{0};
|
||||||
|
CheckError(clGetKernelInfo(*kernel_, CL_KERNEL_FUNCTION_NAME, 0, nullptr, &bytes));
|
||||||
|
auto result = std::string{};
|
||||||
|
result.resize(bytes);
|
||||||
|
CheckError(clGetKernelInfo(*kernel_, CL_KERNEL_FUNCTION_NAME, bytes, &result[0], nullptr));
|
||||||
|
return std::string{result.c_str()}; // Removes any trailing '\0'-characters
|
||||||
|
}
|
||||||
|
|
||||||
// Launches a kernel onto the specified queue
|
// Launches a kernel onto the specified queue
|
||||||
void Launch(const Queue &queue, const std::vector<size_t> &global,
|
void Launch(const Queue &queue, const std::vector<size_t> &global,
|
||||||
const std::vector<size_t> &local, EventPointer event) {
|
const std::vector<size_t> &local, EventPointer event) {
|
||||||
|
@ -647,30 +688,21 @@ class Kernel {
|
||||||
// As above, but with an event waiting list
|
// As above, but with an event waiting list
|
||||||
void Launch(const Queue &queue, const std::vector<size_t> &global,
|
void Launch(const Queue &queue, const std::vector<size_t> &global,
|
||||||
const std::vector<size_t> &local, EventPointer event,
|
const std::vector<size_t> &local, EventPointer event,
|
||||||
std::vector<Event>& waitForEvents) {
|
const std::vector<Event> &waitForEvents) {
|
||||||
if (waitForEvents.size() == 0) { return Launch(queue, global, local, event); }
|
|
||||||
|
|
||||||
// Builds a plain version of the events waiting list
|
// Builds a plain version of the events waiting list
|
||||||
auto waitForEventsPlain = std::vector<cl_event>();
|
auto waitForEventsPlain = std::vector<cl_event>();
|
||||||
for (auto &waitEvent : waitForEvents) {
|
for (auto &waitEvent : waitForEvents) {
|
||||||
waitForEventsPlain.push_back(waitEvent());
|
if (waitEvent()) { waitForEventsPlain.push_back(waitEvent()); }
|
||||||
}
|
}
|
||||||
|
|
||||||
// Launches the kernel while waiting for other events
|
// Launches the kernel while waiting for other events
|
||||||
CheckError(clEnqueueNDRangeKernel(queue(), *kernel_, static_cast<cl_uint>(global.size()),
|
CheckError(clEnqueueNDRangeKernel(queue(), *kernel_, static_cast<cl_uint>(global.size()),
|
||||||
nullptr, global.data(), local.data(),
|
nullptr, global.data(), !local.empty() ? local.data() : nullptr,
|
||||||
static_cast<cl_uint>(waitForEventsPlain.size()),
|
static_cast<cl_uint>(waitForEventsPlain.size()),
|
||||||
waitForEventsPlain.data(),
|
!waitForEventsPlain.empty() ? waitForEventsPlain.data() : nullptr,
|
||||||
event));
|
event));
|
||||||
}
|
}
|
||||||
|
|
||||||
// As above, but with the default local workgroup size
|
|
||||||
void Launch(const Queue &queue, const std::vector<size_t> &global, EventPointer event) {
|
|
||||||
CheckError(clEnqueueNDRangeKernel(queue(), *kernel_, static_cast<cl_uint>(global.size()),
|
|
||||||
nullptr, global.data(), nullptr,
|
|
||||||
0, nullptr, event));
|
|
||||||
}
|
|
||||||
|
|
||||||
// Accessor to the private data-member
|
// Accessor to the private data-member
|
||||||
const cl_kernel& operator()() const { return *kernel_; }
|
const cl_kernel& operator()() const { return *kernel_; }
|
||||||
private:
|
private:
|
||||||
|
|
|
@ -17,6 +17,8 @@
|
||||||
#include "database/kernels/xaxpy.hpp"
|
#include "database/kernels/xaxpy.hpp"
|
||||||
#include "database/kernels/xdot.hpp"
|
#include "database/kernels/xdot.hpp"
|
||||||
#include "database/kernels/xgemv.hpp"
|
#include "database/kernels/xgemv.hpp"
|
||||||
|
#include "database/kernels/xgemv_fast.hpp"
|
||||||
|
#include "database/kernels/xgemv_fast_rot.hpp"
|
||||||
#include "database/kernels/xger.hpp"
|
#include "database/kernels/xger.hpp"
|
||||||
#include "database/kernels/xgemm.hpp"
|
#include "database/kernels/xgemm.hpp"
|
||||||
#include "database/kernels/copy.hpp"
|
#include "database/kernels/copy.hpp"
|
||||||
|
@ -32,6 +34,8 @@ const std::vector<Database::DatabaseEntry> Database::database = {
|
||||||
XaxpyHalf, XaxpySingle, XaxpyDouble, XaxpyComplexSingle, XaxpyComplexDouble,
|
XaxpyHalf, XaxpySingle, XaxpyDouble, XaxpyComplexSingle, XaxpyComplexDouble,
|
||||||
XdotHalf, XdotSingle, XdotDouble, XdotComplexSingle, XdotComplexDouble,
|
XdotHalf, XdotSingle, XdotDouble, XdotComplexSingle, XdotComplexDouble,
|
||||||
XgemvHalf, XgemvSingle, XgemvDouble, XgemvComplexSingle, XgemvComplexDouble,
|
XgemvHalf, XgemvSingle, XgemvDouble, XgemvComplexSingle, XgemvComplexDouble,
|
||||||
|
XgemvFastHalf, XgemvFastSingle, XgemvFastDouble, XgemvFastComplexSingle, XgemvFastComplexDouble,
|
||||||
|
XgemvFastRotHalf, XgemvFastRotSingle, XgemvFastRotDouble, XgemvFastRotComplexSingle, XgemvFastRotComplexDouble,
|
||||||
XgerHalf, XgerSingle, XgerDouble, XgerComplexSingle, XgerComplexDouble,
|
XgerHalf, XgerSingle, XgerDouble, XgerComplexSingle, XgerComplexDouble,
|
||||||
XgemmHalf, XgemmSingle, XgemmDouble, XgemmComplexSingle, XgemmComplexDouble,
|
XgemmHalf, XgemmSingle, XgemmDouble, XgemmComplexSingle, XgemmComplexDouble,
|
||||||
CopyHalf, CopySingle, CopyDouble, CopyComplexSingle, CopyComplexDouble,
|
CopyHalf, CopySingle, CopyDouble, CopyComplexSingle, CopyComplexDouble,
|
||||||
|
@ -42,9 +46,10 @@ const std::vector<Database::DatabaseEntry> Database::database = {
|
||||||
|
|
||||||
// =================================================================================================
|
// =================================================================================================
|
||||||
|
|
||||||
// Constructor, computing device properties and populating the parameter-vector from the database
|
// Constructor, computing device properties and populating the parameter-vector from the database.
|
||||||
|
// This takes an optional overlay database in case of custom tuning or custom kernels.
|
||||||
Database::Database(const Queue &queue, const std::vector<std::string> &kernels,
|
Database::Database(const Queue &queue, const std::vector<std::string> &kernels,
|
||||||
const Precision precision):
|
const Precision precision, const std::vector<DatabaseEntry> &overlay):
|
||||||
parameters_{} {
|
parameters_{} {
|
||||||
|
|
||||||
// Finds information of the current device
|
// Finds information of the current device
|
||||||
|
@ -53,10 +58,26 @@ Database::Database(const Queue &queue, const std::vector<std::string> &kernels,
|
||||||
auto device_vendor = device.Vendor();
|
auto device_vendor = device.Vendor();
|
||||||
auto device_name = device.Name();
|
auto device_name = device.Name();
|
||||||
|
|
||||||
|
// Set the short vendor name
|
||||||
|
for (auto &combination : kVendorNames) {
|
||||||
|
if (device_vendor == combination.first) {
|
||||||
|
device_vendor = combination.second;
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
// Iterates over all kernels to include, and retrieves the parameters for each of them
|
// Iterates over all kernels to include, and retrieves the parameters for each of them
|
||||||
for (auto &kernel: kernels) {
|
for (auto &kernel: kernels) {
|
||||||
auto search_result = Search(kernel, device_type, device_vendor, device_name, precision);
|
auto search_result = ParametersPtr{};
|
||||||
parameters_.insert(search_result.begin(), search_result.end());
|
|
||||||
|
for (auto db: { &overlay, &database }) {
|
||||||
|
search_result = Search(kernel, device_type, device_vendor, device_name, precision, *db);
|
||||||
|
if (search_result) {
|
||||||
|
parameters_.insert(search_result->begin(), search_result->end());
|
||||||
|
break;
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
if (!search_result) { throw std::runtime_error("Database error, could not find a suitable entry"); }
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
|
|
||||||
|
@ -73,28 +94,22 @@ std::string Database::GetDefines() const {
|
||||||
|
|
||||||
// =================================================================================================
|
// =================================================================================================
|
||||||
|
|
||||||
// Searches the database for the right kernel and precision
|
// Searches a particular database for the right kernel and precision
|
||||||
Database::Parameters Database::Search(const std::string &this_kernel,
|
Database::ParametersPtr Database::Search(const std::string &this_kernel,
|
||||||
const std::string &this_type,
|
const std::string &this_type,
|
||||||
const std::string &this_vendor,
|
const std::string &this_vendor,
|
||||||
const std::string &this_device,
|
const std::string &this_device,
|
||||||
const Precision this_precision) const {
|
const Precision this_precision,
|
||||||
// Set the short vendor name
|
const std::vector<DatabaseEntry> &this_database) const {
|
||||||
auto this_short_vendor = this_vendor;
|
|
||||||
for (auto &combination : kVendorNames) {
|
|
||||||
if (this_vendor == combination.first) {
|
|
||||||
this_short_vendor = combination.second;
|
|
||||||
}
|
|
||||||
}
|
|
||||||
|
|
||||||
// Selects the right kernel
|
// Selects the right kernel
|
||||||
for (auto &db: database) {
|
for (auto &db: this_database) {
|
||||||
if (db.kernel == this_kernel && db.precision == this_precision) {
|
if (db.kernel == this_kernel && db.precision == this_precision) {
|
||||||
|
|
||||||
// Searches for the right vendor and device type, or selects the default if unavailable. This
|
// Searches for the right vendor and device type, or selects the default if unavailable. This
|
||||||
// assumes that the default vendor / device type is last in the database.
|
// assumes that the default vendor / device type is last in the database.
|
||||||
for (auto &vendor: db.vendors) {
|
for (auto &vendor: db.vendors) {
|
||||||
if ((vendor.name == this_short_vendor || vendor.name == kDeviceVendorAll) &&
|
if ((vendor.name == this_vendor || vendor.name == kDeviceVendorAll) &&
|
||||||
(vendor.type == this_type || vendor.type == kDeviceTypeAll)) {
|
(vendor.type == this_type || vendor.type == kDeviceTypeAll)) {
|
||||||
|
|
||||||
// Searches for the right device. If the current device is unavailable, selects the vendor
|
// Searches for the right device. If the current device is unavailable, selects the vendor
|
||||||
|
@ -104,7 +119,7 @@ Database::Parameters Database::Search(const std::string &this_kernel,
|
||||||
if (device.name == this_device || device.name == "default") {
|
if (device.name == this_device || device.name == "default") {
|
||||||
|
|
||||||
// Sets the parameters accordingly
|
// Sets the parameters accordingly
|
||||||
return device.parameters;
|
return &device.parameters;
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
|
@ -112,8 +127,8 @@ Database::Parameters Database::Search(const std::string &this_kernel,
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
|
|
||||||
// If we reached this point, something is wrong
|
// If we reached this point, the entry was not found in this database
|
||||||
throw std::runtime_error("Database error, could not find a suitable entry");
|
return nullptr;
|
||||||
}
|
}
|
||||||
|
|
||||||
// =================================================================================================
|
// =================================================================================================
|
||||||
|
|
|
@ -32,6 +32,7 @@ class Database {
|
||||||
|
|
||||||
// Type alias for the database parameters
|
// Type alias for the database parameters
|
||||||
using Parameters = std::unordered_map<std::string,size_t>;
|
using Parameters = std::unordered_map<std::string,size_t>;
|
||||||
|
using ParametersPtr = const Parameters*;
|
||||||
|
|
||||||
// Structures for content inside the database
|
// Structures for content inside the database
|
||||||
struct DatabaseDevice {
|
struct DatabaseDevice {
|
||||||
|
@ -70,6 +71,8 @@ class Database {
|
||||||
static const DatabaseEntry XaxpyHalf, XaxpySingle, XaxpyDouble, XaxpyComplexSingle, XaxpyComplexDouble;
|
static const DatabaseEntry XaxpyHalf, XaxpySingle, XaxpyDouble, XaxpyComplexSingle, XaxpyComplexDouble;
|
||||||
static const DatabaseEntry XdotHalf, XdotSingle, XdotDouble, XdotComplexSingle, XdotComplexDouble;
|
static const DatabaseEntry XdotHalf, XdotSingle, XdotDouble, XdotComplexSingle, XdotComplexDouble;
|
||||||
static const DatabaseEntry XgemvHalf, XgemvSingle, XgemvDouble, XgemvComplexSingle, XgemvComplexDouble;
|
static const DatabaseEntry XgemvHalf, XgemvSingle, XgemvDouble, XgemvComplexSingle, XgemvComplexDouble;
|
||||||
|
static const DatabaseEntry XgemvFastHalf, XgemvFastSingle, XgemvFastDouble, XgemvFastComplexSingle, XgemvFastComplexDouble;
|
||||||
|
static const DatabaseEntry XgemvFastRotHalf, XgemvFastRotSingle, XgemvFastRotDouble, XgemvFastRotComplexSingle, XgemvFastRotComplexDouble;
|
||||||
static const DatabaseEntry XgerHalf, XgerSingle, XgerDouble, XgerComplexSingle, XgerComplexDouble;
|
static const DatabaseEntry XgerHalf, XgerSingle, XgerDouble, XgerComplexSingle, XgerComplexDouble;
|
||||||
static const DatabaseEntry XgemmHalf, XgemmSingle, XgemmDouble, XgemmComplexSingle, XgemmComplexDouble;
|
static const DatabaseEntry XgemmHalf, XgemmSingle, XgemmDouble, XgemmComplexSingle, XgemmComplexDouble;
|
||||||
static const DatabaseEntry CopyHalf, CopySingle, CopyDouble, CopyComplexSingle, CopyComplexDouble;
|
static const DatabaseEntry CopyHalf, CopySingle, CopyDouble, CopyComplexSingle, CopyComplexDouble;
|
||||||
|
@ -78,9 +81,9 @@ class Database {
|
||||||
static const DatabaseEntry PadtransposeHalf, PadtransposeSingle, PadtransposeDouble, PadtransposeComplexSingle, PadtransposeComplexDouble;
|
static const DatabaseEntry PadtransposeHalf, PadtransposeSingle, PadtransposeDouble, PadtransposeComplexSingle, PadtransposeComplexDouble;
|
||||||
static const std::vector<DatabaseEntry> database;
|
static const std::vector<DatabaseEntry> database;
|
||||||
|
|
||||||
// The constructor
|
// The constructor with a user-provided database overlay (potentially an empty vector)
|
||||||
explicit Database(const Queue &queue, const std::vector<std::string> &routines,
|
explicit Database(const Queue &queue, const std::vector<std::string> &routines,
|
||||||
const Precision precision);
|
const Precision precision, const std::vector<DatabaseEntry> &overlay);
|
||||||
|
|
||||||
// Accessor of values by key
|
// Accessor of values by key
|
||||||
size_t operator[](const std::string key) const { return parameters_.find(key)->second; }
|
size_t operator[](const std::string key) const { return parameters_.find(key)->second; }
|
||||||
|
@ -89,9 +92,10 @@ class Database {
|
||||||
std::string GetDefines() const;
|
std::string GetDefines() const;
|
||||||
|
|
||||||
private:
|
private:
|
||||||
Parameters Search(const std::string &this_kernel, const std::string &this_type,
|
// Search method for a specified database, returning pointer (possibly a nullptr)
|
||||||
|
ParametersPtr Search(const std::string &this_kernel, const std::string &this_type,
|
||||||
const std::string &this_vendor, const std::string &this_device,
|
const std::string &this_vendor, const std::string &this_device,
|
||||||
const Precision this_precision) const;
|
const Precision this_precision, const std::vector<DatabaseEntry> &db) const;
|
||||||
|
|
||||||
// Found parameters suitable for this device/kernel
|
// Found parameters suitable for this device/kernel
|
||||||
Parameters parameters_;
|
Parameters parameters_;
|
||||||
|
|
|
@ -18,6 +18,7 @@ const Database::DatabaseEntry Database::CopyHalf = {
|
||||||
"Copy", Precision::kHalf, {
|
"Copy", Precision::kHalf, {
|
||||||
{ // Intel GPUs
|
{ // Intel GPUs
|
||||||
kDeviceTypeGPU, "Intel", {
|
kDeviceTypeGPU, "Intel", {
|
||||||
|
{ "Intel(R) HD Graphics 5500 BroadWell U-Processor GT2", { {"COPY_DIMX",8}, {"COPY_DIMY",16}, {"COPY_VW",8}, {"COPY_WPT",4} } },
|
||||||
{ "Intel(R) HD Graphics Skylake ULT GT2", { {"COPY_DIMX",8}, {"COPY_DIMY",8}, {"COPY_VW",4}, {"COPY_WPT",1} } },
|
{ "Intel(R) HD Graphics Skylake ULT GT2", { {"COPY_DIMX",8}, {"COPY_DIMY",8}, {"COPY_VW",4}, {"COPY_WPT",1} } },
|
||||||
{ "default", { {"COPY_DIMX",8}, {"COPY_DIMY",8}, {"COPY_VW",4}, {"COPY_WPT",1} } },
|
{ "default", { {"COPY_DIMX",8}, {"COPY_DIMY",8}, {"COPY_VW",4}, {"COPY_WPT",1} } },
|
||||||
}
|
}
|
||||||
|
@ -38,9 +39,10 @@ const Database::DatabaseEntry Database::CopySingle = {
|
||||||
kDeviceTypeGPU, "AMD", {
|
kDeviceTypeGPU, "AMD", {
|
||||||
{ "AMD Radeon R9 M370X Compute Engine", { {"COPY_DIMX",32}, {"COPY_DIMY",8}, {"COPY_VW",4}, {"COPY_WPT",1} } },
|
{ "AMD Radeon R9 M370X Compute Engine", { {"COPY_DIMX",32}, {"COPY_DIMY",8}, {"COPY_VW",4}, {"COPY_WPT",1} } },
|
||||||
{ "Hawaii", { {"COPY_DIMX",32}, {"COPY_DIMY",8}, {"COPY_VW",2}, {"COPY_WPT",2} } },
|
{ "Hawaii", { {"COPY_DIMX",32}, {"COPY_DIMY",8}, {"COPY_VW",2}, {"COPY_WPT",2} } },
|
||||||
|
{ "Oland", { {"COPY_DIMX",32}, {"COPY_DIMY",8}, {"COPY_VW",4}, {"COPY_WPT",2} } },
|
||||||
{ "Pitcairn", { {"COPY_DIMX",8}, {"COPY_DIMY",16}, {"COPY_VW",4}, {"COPY_WPT",1} } },
|
{ "Pitcairn", { {"COPY_DIMX",8}, {"COPY_DIMY",16}, {"COPY_VW",4}, {"COPY_WPT",1} } },
|
||||||
{ "Tahiti", { {"COPY_DIMX",32}, {"COPY_DIMY",8}, {"COPY_VW",2}, {"COPY_WPT",2} } },
|
{ "Tahiti", { {"COPY_DIMX",32}, {"COPY_DIMY",8}, {"COPY_VW",2}, {"COPY_WPT",2} } },
|
||||||
{ "default", { {"COPY_DIMX",8}, {"COPY_DIMY",8}, {"COPY_VW",2}, {"COPY_WPT",1} } },
|
{ "default", { {"COPY_DIMX",32}, {"COPY_DIMY",8}, {"COPY_VW",2}, {"COPY_WPT",2} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // ARM GPUs
|
{ // ARM GPUs
|
||||||
|
@ -59,11 +61,13 @@ const Database::DatabaseEntry Database::CopySingle = {
|
||||||
},
|
},
|
||||||
{ // Intel GPUs
|
{ // Intel GPUs
|
||||||
kDeviceTypeGPU, "Intel", {
|
kDeviceTypeGPU, "Intel", {
|
||||||
{ "Intel(R) HD Graphics Haswell Ultrabook GT2 Mobile", { {"COPY_DIMX",8}, {"COPY_DIMY",8}, {"COPY_VW",2}, {"COPY_WPT",1} } },
|
{ "Intel(R) HD Graphics 530", { {"COPY_DIMX",8}, {"COPY_DIMY",8}, {"COPY_VW",2}, {"COPY_WPT",1} } },
|
||||||
|
{ "Intel(R) HD Graphics 5500 BroadWell U-Processor GT2", { {"COPY_DIMX",32}, {"COPY_DIMY",16}, {"COPY_VW",4}, {"COPY_WPT",1} } },
|
||||||
|
{ "Intel(R) HD Graphics Haswell Ultrabook GT2 Mobile", { {"COPY_DIMX",32}, {"COPY_DIMY",16}, {"COPY_VW",4}, {"COPY_WPT",1} } },
|
||||||
{ "Intel(R) HD Graphics Skylake ULT GT2", { {"COPY_DIMX",32}, {"COPY_DIMY",8}, {"COPY_VW",2}, {"COPY_WPT",1} } },
|
{ "Intel(R) HD Graphics Skylake ULT GT2", { {"COPY_DIMX",32}, {"COPY_DIMY",8}, {"COPY_VW",2}, {"COPY_WPT",1} } },
|
||||||
{ "Iris", { {"COPY_DIMX",16}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",2} } },
|
{ "Iris", { {"COPY_DIMX",16}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",2} } },
|
||||||
{ "Iris Pro", { {"COPY_DIMX",32}, {"COPY_DIMY",8}, {"COPY_VW",4}, {"COPY_WPT",4} } },
|
{ "Iris Pro", { {"COPY_DIMX",32}, {"COPY_DIMY",8}, {"COPY_VW",4}, {"COPY_WPT",4} } },
|
||||||
{ "default", { {"COPY_DIMX",8}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
{ "default", { {"COPY_DIMX",32}, {"COPY_DIMY",8}, {"COPY_VW",2}, {"COPY_WPT",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Intel accelerators
|
{ // Intel accelerators
|
||||||
|
@ -75,20 +79,23 @@ const Database::DatabaseEntry Database::CopySingle = {
|
||||||
{ // NVIDIA GPUs
|
{ // NVIDIA GPUs
|
||||||
kDeviceTypeGPU, "NVIDIA", {
|
kDeviceTypeGPU, "NVIDIA", {
|
||||||
{ "GRID K520", { {"COPY_DIMX",16}, {"COPY_DIMY",8}, {"COPY_VW",4}, {"COPY_WPT",1} } },
|
{ "GRID K520", { {"COPY_DIMX",16}, {"COPY_DIMY",8}, {"COPY_VW",4}, {"COPY_WPT",1} } },
|
||||||
|
{ "GeForce GTX 1070", { {"COPY_DIMX",8}, {"COPY_DIMY",16}, {"COPY_VW",4}, {"COPY_WPT",1} } },
|
||||||
{ "GeForce GTX 480", { {"COPY_DIMX",8}, {"COPY_DIMY",8}, {"COPY_VW",4}, {"COPY_WPT",1} } },
|
{ "GeForce GTX 480", { {"COPY_DIMX",8}, {"COPY_DIMY",8}, {"COPY_VW",4}, {"COPY_WPT",1} } },
|
||||||
|
{ "GeForce GTX 670", { {"COPY_DIMX",16}, {"COPY_DIMY",32}, {"COPY_VW",4}, {"COPY_WPT",1} } },
|
||||||
{ "GeForce GTX 680", { {"COPY_DIMX",32}, {"COPY_DIMY",16}, {"COPY_VW",4}, {"COPY_WPT",1} } },
|
{ "GeForce GTX 680", { {"COPY_DIMX",32}, {"COPY_DIMY",16}, {"COPY_VW",4}, {"COPY_WPT",1} } },
|
||||||
|
{ "GeForce GTX 750", { {"COPY_DIMX",32}, {"COPY_DIMY",8}, {"COPY_VW",2}, {"COPY_WPT",2} } },
|
||||||
{ "GeForce GTX 750 Ti", { {"COPY_DIMX",32}, {"COPY_DIMY",8}, {"COPY_VW",2}, {"COPY_WPT",1} } },
|
{ "GeForce GTX 750 Ti", { {"COPY_DIMX",32}, {"COPY_DIMY",8}, {"COPY_VW",2}, {"COPY_WPT",1} } },
|
||||||
{ "GeForce GTX 980", { {"COPY_DIMX",32}, {"COPY_DIMY",16}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
{ "GeForce GTX 980", { {"COPY_DIMX",32}, {"COPY_DIMY",16}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
||||||
{ "GeForce GTX TITAN", { {"COPY_DIMX",32}, {"COPY_DIMY",8}, {"COPY_VW",2}, {"COPY_WPT",4} } },
|
{ "GeForce GTX TITAN", { {"COPY_DIMX",32}, {"COPY_DIMY",8}, {"COPY_VW",2}, {"COPY_WPT",4} } },
|
||||||
{ "GeForce GTX TITAN X", { {"COPY_DIMX",32}, {"COPY_DIMY",8}, {"COPY_VW",2}, {"COPY_WPT",1} } },
|
{ "GeForce GTX TITAN X", { {"COPY_DIMX",32}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",2} } },
|
||||||
{ "Tesla K20m", { {"COPY_DIMX",8}, {"COPY_DIMY",8}, {"COPY_VW",4}, {"COPY_WPT",4} } },
|
{ "Tesla K20m", { {"COPY_DIMX",8}, {"COPY_DIMY",8}, {"COPY_VW",4}, {"COPY_WPT",4} } },
|
||||||
{ "Tesla K40m", { {"COPY_DIMX",8}, {"COPY_DIMY",8}, {"COPY_VW",4}, {"COPY_WPT",2} } },
|
{ "Tesla K40m", { {"COPY_DIMX",8}, {"COPY_DIMY",8}, {"COPY_VW",4}, {"COPY_WPT",2} } },
|
||||||
{ "default", { {"COPY_DIMX",8}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
{ "default", { {"COPY_DIMX",8}, {"COPY_DIMY",16}, {"COPY_VW",4}, {"COPY_WPT",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Default
|
{ // Default
|
||||||
kDeviceTypeAll, "default", {
|
kDeviceTypeAll, "default", {
|
||||||
{ "default", { {"COPY_DIMX",8}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
{ "default", { {"COPY_DIMX",32}, {"COPY_DIMY",8}, {"COPY_VW",2}, {"COPY_WPT",2} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
}
|
}
|
||||||
|
@ -102,9 +109,10 @@ const Database::DatabaseEntry Database::CopyComplexSingle = {
|
||||||
kDeviceTypeGPU, "AMD", {
|
kDeviceTypeGPU, "AMD", {
|
||||||
{ "AMD Radeon R9 M370X Compute Engine", { {"COPY_DIMX",32}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
{ "AMD Radeon R9 M370X Compute Engine", { {"COPY_DIMX",32}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
||||||
{ "Hawaii", { {"COPY_DIMX",32}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",2} } },
|
{ "Hawaii", { {"COPY_DIMX",32}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",2} } },
|
||||||
|
{ "Oland", { {"COPY_DIMX",8}, {"COPY_DIMY",16}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
||||||
{ "Pitcairn", { {"COPY_DIMX",8}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",2} } },
|
{ "Pitcairn", { {"COPY_DIMX",8}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",2} } },
|
||||||
{ "Tahiti", { {"COPY_DIMX",8}, {"COPY_DIMY",8}, {"COPY_VW",2}, {"COPY_WPT",2} } },
|
{ "Tahiti", { {"COPY_DIMX",8}, {"COPY_DIMY",8}, {"COPY_VW",2}, {"COPY_WPT",2} } },
|
||||||
{ "default", { {"COPY_DIMX",8}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
{ "default", { {"COPY_DIMX",32}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Intel CPUs
|
{ // Intel CPUs
|
||||||
|
@ -112,16 +120,18 @@ const Database::DatabaseEntry Database::CopyComplexSingle = {
|
||||||
{ "Intel(R) Core(TM) i5-6200U CPU @ 2.30GHz", { {"COPY_DIMX",16}, {"COPY_DIMY",16}, {"COPY_VW",8}, {"COPY_WPT",1} } },
|
{ "Intel(R) Core(TM) i5-6200U CPU @ 2.30GHz", { {"COPY_DIMX",16}, {"COPY_DIMY",16}, {"COPY_VW",8}, {"COPY_WPT",1} } },
|
||||||
{ "Intel(R) Core(TM) i7-3770 CPU @ 3.40GHz", { {"COPY_DIMX",32}, {"COPY_DIMY",8}, {"COPY_VW",2}, {"COPY_WPT",2} } },
|
{ "Intel(R) Core(TM) i7-3770 CPU @ 3.40GHz", { {"COPY_DIMX",32}, {"COPY_DIMY",8}, {"COPY_VW",2}, {"COPY_WPT",2} } },
|
||||||
{ "Intel(R) Core(TM) i7-5930K CPU @ 3.50GHz", { {"COPY_DIMX",16}, {"COPY_DIMY",8}, {"COPY_VW",8}, {"COPY_WPT",1} } },
|
{ "Intel(R) Core(TM) i7-5930K CPU @ 3.50GHz", { {"COPY_DIMX",16}, {"COPY_DIMY",8}, {"COPY_VW",8}, {"COPY_WPT",1} } },
|
||||||
{ "default", { {"COPY_DIMX",16}, {"COPY_DIMY",8}, {"COPY_VW",2}, {"COPY_WPT",1} } },
|
{ "default", { {"COPY_DIMX",32}, {"COPY_DIMY",8}, {"COPY_VW",8}, {"COPY_WPT",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Intel GPUs
|
{ // Intel GPUs
|
||||||
kDeviceTypeGPU, "Intel", {
|
kDeviceTypeGPU, "Intel", {
|
||||||
|
{ "Intel(R) HD Graphics 530", { {"COPY_DIMX",16}, {"COPY_DIMY",8}, {"COPY_VW",2}, {"COPY_WPT",1} } },
|
||||||
|
{ "Intel(R) HD Graphics 5500 BroadWell U-Processor GT2", { {"COPY_DIMX",16}, {"COPY_DIMY",16}, {"COPY_VW",2}, {"COPY_WPT",2} } },
|
||||||
{ "Intel(R) HD Graphics Haswell Ultrabook GT2 Mobile", { {"COPY_DIMX",8}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
{ "Intel(R) HD Graphics Haswell Ultrabook GT2 Mobile", { {"COPY_DIMX",8}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
||||||
{ "Intel(R) HD Graphics Skylake ULT GT2", { {"COPY_DIMX",8}, {"COPY_DIMY",8}, {"COPY_VW",4}, {"COPY_WPT",4} } },
|
{ "Intel(R) HD Graphics Skylake ULT GT2", { {"COPY_DIMX",8}, {"COPY_DIMY",8}, {"COPY_VW",4}, {"COPY_WPT",4} } },
|
||||||
{ "Iris", { {"COPY_DIMX",16}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",2} } },
|
{ "Iris", { {"COPY_DIMX",16}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",2} } },
|
||||||
{ "Iris Pro", { {"COPY_DIMX",32}, {"COPY_DIMY",16}, {"COPY_VW",1}, {"COPY_WPT",4} } },
|
{ "Iris Pro", { {"COPY_DIMX",32}, {"COPY_DIMY",16}, {"COPY_VW",1}, {"COPY_WPT",4} } },
|
||||||
{ "default", { {"COPY_DIMX",8}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
{ "default", { {"COPY_DIMX",16}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",2} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Intel accelerators
|
{ // Intel accelerators
|
||||||
|
@ -133,18 +143,21 @@ const Database::DatabaseEntry Database::CopyComplexSingle = {
|
||||||
{ // NVIDIA GPUs
|
{ // NVIDIA GPUs
|
||||||
kDeviceTypeGPU, "NVIDIA", {
|
kDeviceTypeGPU, "NVIDIA", {
|
||||||
{ "GRID K520", { {"COPY_DIMX",16}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
{ "GRID K520", { {"COPY_DIMX",16}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
||||||
|
{ "GeForce GTX 1070", { {"COPY_DIMX",16}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
||||||
{ "GeForce GTX 480", { {"COPY_DIMX",16}, {"COPY_DIMY",16}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
{ "GeForce GTX 480", { {"COPY_DIMX",16}, {"COPY_DIMY",16}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
||||||
|
{ "GeForce GTX 670", { {"COPY_DIMX",16}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
||||||
|
{ "GeForce GTX 750", { {"COPY_DIMX",16}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",2} } },
|
||||||
{ "GeForce GTX 750 Ti", { {"COPY_DIMX",32}, {"COPY_DIMY",16}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
{ "GeForce GTX 750 Ti", { {"COPY_DIMX",32}, {"COPY_DIMY",16}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
||||||
{ "GeForce GTX 980", { {"COPY_DIMX",8}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
{ "GeForce GTX 980", { {"COPY_DIMX",8}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
||||||
{ "GeForce GTX TITAN X", { {"COPY_DIMX",16}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
{ "GeForce GTX TITAN X", { {"COPY_DIMX",16}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
||||||
{ "Tesla K20m", { {"COPY_DIMX",8}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",4} } },
|
{ "Tesla K20m", { {"COPY_DIMX",8}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",4} } },
|
||||||
{ "Tesla K40m", { {"COPY_DIMX",16}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
{ "Tesla K40m", { {"COPY_DIMX",16}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
||||||
{ "default", { {"COPY_DIMX",8}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
{ "default", { {"COPY_DIMX",16}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Default
|
{ // Default
|
||||||
kDeviceTypeAll, "default", {
|
kDeviceTypeAll, "default", {
|
||||||
{ "default", { {"COPY_DIMX",8}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
{ "default", { {"COPY_DIMX",32}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
}
|
}
|
||||||
|
@ -158,9 +171,10 @@ const Database::DatabaseEntry Database::CopyDouble = {
|
||||||
kDeviceTypeGPU, "AMD", {
|
kDeviceTypeGPU, "AMD", {
|
||||||
{ "AMD Radeon R9 M370X Compute Engine", { {"COPY_DIMX",32}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
{ "AMD Radeon R9 M370X Compute Engine", { {"COPY_DIMX",32}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
||||||
{ "Hawaii", { {"COPY_DIMX",32}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",2} } },
|
{ "Hawaii", { {"COPY_DIMX",32}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",2} } },
|
||||||
|
{ "Oland", { {"COPY_DIMX",32}, {"COPY_DIMY",8}, {"COPY_VW",2}, {"COPY_WPT",8} } },
|
||||||
{ "Pitcairn", { {"COPY_DIMX",32}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
{ "Pitcairn", { {"COPY_DIMX",32}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
||||||
{ "Tahiti", { {"COPY_DIMX",8}, {"COPY_DIMY",32}, {"COPY_VW",2}, {"COPY_WPT",1} } },
|
{ "Tahiti", { {"COPY_DIMX",8}, {"COPY_DIMY",32}, {"COPY_VW",2}, {"COPY_WPT",1} } },
|
||||||
{ "default", { {"COPY_DIMX",8}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
{ "default", { {"COPY_DIMX",32}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",2} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // ARM GPUs
|
{ // ARM GPUs
|
||||||
|
@ -174,7 +188,7 @@ const Database::DatabaseEntry Database::CopyDouble = {
|
||||||
{ "Intel(R) Core(TM) i5-6200U CPU @ 2.30GHz", { {"COPY_DIMX",16}, {"COPY_DIMY",8}, {"COPY_VW",8}, {"COPY_WPT",1} } },
|
{ "Intel(R) Core(TM) i5-6200U CPU @ 2.30GHz", { {"COPY_DIMX",16}, {"COPY_DIMY",8}, {"COPY_VW",8}, {"COPY_WPT",1} } },
|
||||||
{ "Intel(R) Core(TM) i7-3770 CPU @ 3.40GHz", { {"COPY_DIMX",16}, {"COPY_DIMY",32}, {"COPY_VW",2}, {"COPY_WPT",1} } },
|
{ "Intel(R) Core(TM) i7-3770 CPU @ 3.40GHz", { {"COPY_DIMX",16}, {"COPY_DIMY",32}, {"COPY_VW",2}, {"COPY_WPT",1} } },
|
||||||
{ "Intel(R) Core(TM) i7-5930K CPU @ 3.50GHz", { {"COPY_DIMX",16}, {"COPY_DIMY",16}, {"COPY_VW",8}, {"COPY_WPT",1} } },
|
{ "Intel(R) Core(TM) i7-5930K CPU @ 3.50GHz", { {"COPY_DIMX",16}, {"COPY_DIMY",16}, {"COPY_VW",8}, {"COPY_WPT",1} } },
|
||||||
{ "default", { {"COPY_DIMX",16}, {"COPY_DIMY",8}, {"COPY_VW",2}, {"COPY_WPT",1} } },
|
{ "default", { {"COPY_DIMX",16}, {"COPY_DIMY",16}, {"COPY_VW",8}, {"COPY_WPT",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Intel accelerators
|
{ // Intel accelerators
|
||||||
|
@ -186,20 +200,23 @@ const Database::DatabaseEntry Database::CopyDouble = {
|
||||||
{ // NVIDIA GPUs
|
{ // NVIDIA GPUs
|
||||||
kDeviceTypeGPU, "NVIDIA", {
|
kDeviceTypeGPU, "NVIDIA", {
|
||||||
{ "GRID K520", { {"COPY_DIMX",32}, {"COPY_DIMY",16}, {"COPY_VW",2}, {"COPY_WPT",1} } },
|
{ "GRID K520", { {"COPY_DIMX",32}, {"COPY_DIMY",16}, {"COPY_VW",2}, {"COPY_WPT",1} } },
|
||||||
|
{ "GeForce GTX 1070", { {"COPY_DIMX",8}, {"COPY_DIMY",8}, {"COPY_VW",4}, {"COPY_WPT",1} } },
|
||||||
{ "GeForce GTX 480", { {"COPY_DIMX",8}, {"COPY_DIMY",8}, {"COPY_VW",2}, {"COPY_WPT",1} } },
|
{ "GeForce GTX 480", { {"COPY_DIMX",8}, {"COPY_DIMY",8}, {"COPY_VW",2}, {"COPY_WPT",1} } },
|
||||||
|
{ "GeForce GTX 670", { {"COPY_DIMX",8}, {"COPY_DIMY",8}, {"COPY_VW",2}, {"COPY_WPT",1} } },
|
||||||
{ "GeForce GTX 680", { {"COPY_DIMX",16}, {"COPY_DIMY",32}, {"COPY_VW",2}, {"COPY_WPT",1} } },
|
{ "GeForce GTX 680", { {"COPY_DIMX",16}, {"COPY_DIMY",32}, {"COPY_VW",2}, {"COPY_WPT",1} } },
|
||||||
|
{ "GeForce GTX 750", { {"COPY_DIMX",8}, {"COPY_DIMY",16}, {"COPY_VW",2}, {"COPY_WPT",1} } },
|
||||||
{ "GeForce GTX 750 Ti", { {"COPY_DIMX",8}, {"COPY_DIMY",8}, {"COPY_VW",2}, {"COPY_WPT",1} } },
|
{ "GeForce GTX 750 Ti", { {"COPY_DIMX",8}, {"COPY_DIMY",8}, {"COPY_VW",2}, {"COPY_WPT",1} } },
|
||||||
{ "GeForce GTX 980", { {"COPY_DIMX",32}, {"COPY_DIMY",8}, {"COPY_VW",2}, {"COPY_WPT",1} } },
|
{ "GeForce GTX 980", { {"COPY_DIMX",32}, {"COPY_DIMY",8}, {"COPY_VW",2}, {"COPY_WPT",1} } },
|
||||||
{ "GeForce GTX TITAN", { {"COPY_DIMX",16}, {"COPY_DIMY",32}, {"COPY_VW",2}, {"COPY_WPT",2} } },
|
{ "GeForce GTX TITAN", { {"COPY_DIMX",16}, {"COPY_DIMY",32}, {"COPY_VW",2}, {"COPY_WPT",2} } },
|
||||||
{ "GeForce GTX TITAN X", { {"COPY_DIMX",32}, {"COPY_DIMY",16}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
{ "GeForce GTX TITAN X", { {"COPY_DIMX",32}, {"COPY_DIMY",16}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
||||||
{ "Tesla K20m", { {"COPY_DIMX",8}, {"COPY_DIMY",8}, {"COPY_VW",2}, {"COPY_WPT",1} } },
|
{ "Tesla K20m", { {"COPY_DIMX",8}, {"COPY_DIMY",8}, {"COPY_VW",2}, {"COPY_WPT",1} } },
|
||||||
{ "Tesla K40m", { {"COPY_DIMX",8}, {"COPY_DIMY",8}, {"COPY_VW",2}, {"COPY_WPT",2} } },
|
{ "Tesla K40m", { {"COPY_DIMX",8}, {"COPY_DIMY",8}, {"COPY_VW",2}, {"COPY_WPT",2} } },
|
||||||
{ "default", { {"COPY_DIMX",8}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
{ "default", { {"COPY_DIMX",32}, {"COPY_DIMY",32}, {"COPY_VW",2}, {"COPY_WPT",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Default
|
{ // Default
|
||||||
kDeviceTypeAll, "default", {
|
kDeviceTypeAll, "default", {
|
||||||
{ "default", { {"COPY_DIMX",8}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
{ "default", { {"COPY_DIMX",16}, {"COPY_DIMY",8}, {"COPY_VW",2}, {"COPY_WPT",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
}
|
}
|
||||||
|
@ -213,9 +230,10 @@ const Database::DatabaseEntry Database::CopyComplexDouble = {
|
||||||
kDeviceTypeGPU, "AMD", {
|
kDeviceTypeGPU, "AMD", {
|
||||||
{ "AMD Radeon R9 M370X Compute Engine", { {"COPY_DIMX",8}, {"COPY_DIMY",16}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
{ "AMD Radeon R9 M370X Compute Engine", { {"COPY_DIMX",8}, {"COPY_DIMY",16}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
||||||
{ "Hawaii", { {"COPY_DIMX",32}, {"COPY_DIMY",8}, {"COPY_VW",2}, {"COPY_WPT",8} } },
|
{ "Hawaii", { {"COPY_DIMX",32}, {"COPY_DIMY",8}, {"COPY_VW",2}, {"COPY_WPT",8} } },
|
||||||
|
{ "Oland", { {"COPY_DIMX",8}, {"COPY_DIMY",16}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
||||||
{ "Pitcairn", { {"COPY_DIMX",16}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
{ "Pitcairn", { {"COPY_DIMX",16}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
||||||
{ "Tahiti", { {"COPY_DIMX",8}, {"COPY_DIMY",16}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
{ "Tahiti", { {"COPY_DIMX",8}, {"COPY_DIMY",16}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
||||||
{ "default", { {"COPY_DIMX",8}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
{ "default", { {"COPY_DIMX",8}, {"COPY_DIMY",16}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // ARM GPUs
|
{ // ARM GPUs
|
||||||
|
@ -229,7 +247,7 @@ const Database::DatabaseEntry Database::CopyComplexDouble = {
|
||||||
{ "Intel(R) Core(TM) i5-6200U CPU @ 2.30GHz", { {"COPY_DIMX",32}, {"COPY_DIMY",8}, {"COPY_VW",8}, {"COPY_WPT",1} } },
|
{ "Intel(R) Core(TM) i5-6200U CPU @ 2.30GHz", { {"COPY_DIMX",32}, {"COPY_DIMY",8}, {"COPY_VW",8}, {"COPY_WPT",1} } },
|
||||||
{ "Intel(R) Core(TM) i7-3770 CPU @ 3.40GHz", { {"COPY_DIMX",32}, {"COPY_DIMY",32}, {"COPY_VW",8}, {"COPY_WPT",1} } },
|
{ "Intel(R) Core(TM) i7-3770 CPU @ 3.40GHz", { {"COPY_DIMX",32}, {"COPY_DIMY",32}, {"COPY_VW",8}, {"COPY_WPT",1} } },
|
||||||
{ "Intel(R) Core(TM) i7-5930K CPU @ 3.50GHz", { {"COPY_DIMX",8}, {"COPY_DIMY",8}, {"COPY_VW",8}, {"COPY_WPT",1} } },
|
{ "Intel(R) Core(TM) i7-5930K CPU @ 3.50GHz", { {"COPY_DIMX",8}, {"COPY_DIMY",8}, {"COPY_VW",8}, {"COPY_WPT",1} } },
|
||||||
{ "default", { {"COPY_DIMX",8}, {"COPY_DIMY",8}, {"COPY_VW",8}, {"COPY_WPT",1} } },
|
{ "default", { {"COPY_DIMX",32}, {"COPY_DIMY",32}, {"COPY_VW",8}, {"COPY_WPT",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Intel accelerators
|
{ // Intel accelerators
|
||||||
|
@ -241,8 +259,11 @@ const Database::DatabaseEntry Database::CopyComplexDouble = {
|
||||||
{ // NVIDIA GPUs
|
{ // NVIDIA GPUs
|
||||||
kDeviceTypeGPU, "NVIDIA", {
|
kDeviceTypeGPU, "NVIDIA", {
|
||||||
{ "GRID K520", { {"COPY_DIMX",8}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
{ "GRID K520", { {"COPY_DIMX",8}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
||||||
|
{ "GeForce GTX 1070", { {"COPY_DIMX",8}, {"COPY_DIMY",32}, {"COPY_VW",1}, {"COPY_WPT",4} } },
|
||||||
{ "GeForce GTX 480", { {"COPY_DIMX",16}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
{ "GeForce GTX 480", { {"COPY_DIMX",16}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
||||||
|
{ "GeForce GTX 670", { {"COPY_DIMX",16}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
||||||
{ "GeForce GTX 680", { {"COPY_DIMX",8}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
{ "GeForce GTX 680", { {"COPY_DIMX",8}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
||||||
|
{ "GeForce GTX 750", { {"COPY_DIMX",32}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
||||||
{ "GeForce GTX 750 Ti", { {"COPY_DIMX",32}, {"COPY_DIMY",16}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
{ "GeForce GTX 750 Ti", { {"COPY_DIMX",32}, {"COPY_DIMY",16}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
||||||
{ "GeForce GTX 980", { {"COPY_DIMX",8}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
{ "GeForce GTX 980", { {"COPY_DIMX",8}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
||||||
{ "GeForce GTX TITAN", { {"COPY_DIMX",16}, {"COPY_DIMY",16}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
{ "GeForce GTX TITAN", { {"COPY_DIMX",16}, {"COPY_DIMY",16}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
||||||
|
@ -254,7 +275,7 @@ const Database::DatabaseEntry Database::CopyComplexDouble = {
|
||||||
},
|
},
|
||||||
{ // Default
|
{ // Default
|
||||||
kDeviceTypeAll, "default", {
|
kDeviceTypeAll, "default", {
|
||||||
{ "default", { {"COPY_DIMX",8}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
{ "default", { {"COPY_DIMX",16}, {"COPY_DIMY",8}, {"COPY_VW",1}, {"COPY_WPT",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
}
|
}
|
||||||
|
|
|
@ -18,6 +18,7 @@ const Database::DatabaseEntry Database::PadHalf = {
|
||||||
"Pad", Precision::kHalf, {
|
"Pad", Precision::kHalf, {
|
||||||
{ // Intel GPUs
|
{ // Intel GPUs
|
||||||
kDeviceTypeGPU, "Intel", {
|
kDeviceTypeGPU, "Intel", {
|
||||||
|
{ "Intel(R) HD Graphics 5500 BroadWell U-Processor GT2", { {"PAD_DIMX",8}, {"PAD_DIMY",8}, {"PAD_WPTX",4}, {"PAD_WPTY",1} } },
|
||||||
{ "Intel(R) HD Graphics Skylake ULT GT2", { {"PAD_DIMX",8}, {"PAD_DIMY",8}, {"PAD_WPTX",2}, {"PAD_WPTY",1} } },
|
{ "Intel(R) HD Graphics Skylake ULT GT2", { {"PAD_DIMX",8}, {"PAD_DIMY",8}, {"PAD_WPTX",2}, {"PAD_WPTY",1} } },
|
||||||
{ "default", { {"PAD_DIMX",8}, {"PAD_DIMY",8}, {"PAD_WPTX",2}, {"PAD_WPTY",1} } },
|
{ "default", { {"PAD_DIMX",8}, {"PAD_DIMY",8}, {"PAD_WPTX",2}, {"PAD_WPTY",1} } },
|
||||||
}
|
}
|
||||||
|
@ -38,9 +39,10 @@ const Database::DatabaseEntry Database::PadSingle = {
|
||||||
kDeviceTypeGPU, "AMD", {
|
kDeviceTypeGPU, "AMD", {
|
||||||
{ "AMD Radeon R9 M370X Compute Engine", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
{ "AMD Radeon R9 M370X Compute Engine", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
||||||
{ "Hawaii", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",4} } },
|
{ "Hawaii", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",4} } },
|
||||||
|
{ "Oland", { {"PAD_DIMX",8}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",2} } },
|
||||||
{ "Pitcairn", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",2} } },
|
{ "Pitcairn", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",2} } },
|
||||||
{ "Tahiti", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",2} } },
|
{ "Tahiti", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",2} } },
|
||||||
{ "default", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
{ "default", { {"PAD_DIMX",8}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",2} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // ARM GPUs
|
{ // ARM GPUs
|
||||||
|
@ -54,16 +56,18 @@ const Database::DatabaseEntry Database::PadSingle = {
|
||||||
{ "Intel(R) Core(TM) i5-6200U CPU @ 2.30GHz", { {"PAD_DIMX",32}, {"PAD_DIMY",16}, {"PAD_WPTX",4}, {"PAD_WPTY",1} } },
|
{ "Intel(R) Core(TM) i5-6200U CPU @ 2.30GHz", { {"PAD_DIMX",32}, {"PAD_DIMY",16}, {"PAD_WPTX",4}, {"PAD_WPTY",1} } },
|
||||||
{ "Intel(R) Core(TM) i7-3770 CPU @ 3.40GHz", { {"PAD_DIMX",16}, {"PAD_DIMY",32}, {"PAD_WPTX",4}, {"PAD_WPTY",4} } },
|
{ "Intel(R) Core(TM) i7-3770 CPU @ 3.40GHz", { {"PAD_DIMX",16}, {"PAD_DIMY",32}, {"PAD_WPTX",4}, {"PAD_WPTY",4} } },
|
||||||
{ "Intel(R) Core(TM) i7-5930K CPU @ 3.50GHz", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",4}, {"PAD_WPTY",1} } },
|
{ "Intel(R) Core(TM) i7-5930K CPU @ 3.50GHz", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",4}, {"PAD_WPTY",1} } },
|
||||||
{ "default", { {"PAD_DIMX",16}, {"PAD_DIMY",8}, {"PAD_WPTX",4}, {"PAD_WPTY",1} } },
|
{ "default", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",4}, {"PAD_WPTY",2} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Intel GPUs
|
{ // Intel GPUs
|
||||||
kDeviceTypeGPU, "Intel", {
|
kDeviceTypeGPU, "Intel", {
|
||||||
{ "Intel(R) HD Graphics Haswell Ultrabook GT2 Mobile", { {"PAD_DIMX",8}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
{ "Intel(R) HD Graphics 530", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",2}, {"PAD_WPTY",4} } },
|
||||||
|
{ "Intel(R) HD Graphics 5500 BroadWell U-Processor GT2", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",2}, {"PAD_WPTY",4} } },
|
||||||
|
{ "Intel(R) HD Graphics Haswell Ultrabook GT2 Mobile", { {"PAD_DIMX",16}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",2} } },
|
||||||
{ "Intel(R) HD Graphics Skylake ULT GT2", { {"PAD_DIMX",16}, {"PAD_DIMY",8}, {"PAD_WPTX",2}, {"PAD_WPTY",1} } },
|
{ "Intel(R) HD Graphics Skylake ULT GT2", { {"PAD_DIMX",16}, {"PAD_DIMY",8}, {"PAD_WPTX",2}, {"PAD_WPTY",1} } },
|
||||||
{ "Iris", { {"PAD_DIMX",32}, {"PAD_DIMY",16}, {"PAD_WPTX",2}, {"PAD_WPTY",1} } },
|
{ "Iris", { {"PAD_DIMX",32}, {"PAD_DIMY",16}, {"PAD_WPTX",2}, {"PAD_WPTY",1} } },
|
||||||
{ "Iris Pro", { {"PAD_DIMX",16}, {"PAD_DIMY",8}, {"PAD_WPTX",2}, {"PAD_WPTY",1} } },
|
{ "Iris Pro", { {"PAD_DIMX",16}, {"PAD_DIMY",8}, {"PAD_WPTX",2}, {"PAD_WPTY",1} } },
|
||||||
{ "default", { {"PAD_DIMX",8}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
{ "default", { {"PAD_DIMX",16}, {"PAD_DIMY",8}, {"PAD_WPTX",2}, {"PAD_WPTY",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Intel accelerators
|
{ // Intel accelerators
|
||||||
|
@ -75,20 +79,23 @@ const Database::DatabaseEntry Database::PadSingle = {
|
||||||
{ // NVIDIA GPUs
|
{ // NVIDIA GPUs
|
||||||
kDeviceTypeGPU, "NVIDIA", {
|
kDeviceTypeGPU, "NVIDIA", {
|
||||||
{ "GRID K520", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",2}, {"PAD_WPTY",1} } },
|
{ "GRID K520", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",2}, {"PAD_WPTY",1} } },
|
||||||
|
{ "GeForce GTX 1070", { {"PAD_DIMX",16}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
||||||
{ "GeForce GTX 480", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",4} } },
|
{ "GeForce GTX 480", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",4} } },
|
||||||
|
{ "GeForce GTX 670", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",2}, {"PAD_WPTY",2} } },
|
||||||
{ "GeForce GTX 680", { {"PAD_DIMX",16}, {"PAD_DIMY",8}, {"PAD_WPTX",4}, {"PAD_WPTY",1} } },
|
{ "GeForce GTX 680", { {"PAD_DIMX",16}, {"PAD_DIMY",8}, {"PAD_WPTX",4}, {"PAD_WPTY",1} } },
|
||||||
|
{ "GeForce GTX 750", { {"PAD_DIMX",32}, {"PAD_DIMY",16}, {"PAD_WPTX",4}, {"PAD_WPTY",2} } },
|
||||||
{ "GeForce GTX 750 Ti", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",4}, {"PAD_WPTY",1} } },
|
{ "GeForce GTX 750 Ti", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",4}, {"PAD_WPTY",1} } },
|
||||||
{ "GeForce GTX 980", { {"PAD_DIMX",16}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
{ "GeForce GTX 980", { {"PAD_DIMX",16}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
||||||
{ "GeForce GTX TITAN", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",2}, {"PAD_WPTY",1} } },
|
{ "GeForce GTX TITAN", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",2}, {"PAD_WPTY",1} } },
|
||||||
{ "GeForce GTX TITAN X", { {"PAD_DIMX",16}, {"PAD_DIMY",16}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
{ "GeForce GTX TITAN X", { {"PAD_DIMX",16}, {"PAD_DIMY",16}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
||||||
{ "Tesla K20m", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",2}, {"PAD_WPTY",1} } },
|
{ "Tesla K20m", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",2}, {"PAD_WPTY",1} } },
|
||||||
{ "Tesla K40m", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
{ "Tesla K40m", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
||||||
{ "default", { {"PAD_DIMX",16}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
{ "default", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",4}, {"PAD_WPTY",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Default
|
{ // Default
|
||||||
kDeviceTypeAll, "default", {
|
kDeviceTypeAll, "default", {
|
||||||
{ "default", { {"PAD_DIMX",8}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
{ "default", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",2}, {"PAD_WPTY",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
}
|
}
|
||||||
|
@ -102,9 +109,10 @@ const Database::DatabaseEntry Database::PadComplexSingle = {
|
||||||
kDeviceTypeGPU, "AMD", {
|
kDeviceTypeGPU, "AMD", {
|
||||||
{ "AMD Radeon R9 M370X Compute Engine", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
{ "AMD Radeon R9 M370X Compute Engine", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
||||||
{ "Hawaii", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",2} } },
|
{ "Hawaii", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",2} } },
|
||||||
|
{ "Oland", { {"PAD_DIMX",8}, {"PAD_DIMY",32}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
||||||
{ "Pitcairn", { {"PAD_DIMX",8}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",2} } },
|
{ "Pitcairn", { {"PAD_DIMX",8}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",2} } },
|
||||||
{ "Tahiti", { {"PAD_DIMX",16}, {"PAD_DIMY",16}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
{ "Tahiti", { {"PAD_DIMX",16}, {"PAD_DIMY",16}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
||||||
{ "default", { {"PAD_DIMX",8}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
{ "default", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // ARM GPUs
|
{ // ARM GPUs
|
||||||
|
@ -118,16 +126,18 @@ const Database::DatabaseEntry Database::PadComplexSingle = {
|
||||||
{ "Intel(R) Core(TM) i5-6200U CPU @ 2.30GHz", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",2}, {"PAD_WPTY",2} } },
|
{ "Intel(R) Core(TM) i5-6200U CPU @ 2.30GHz", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",2}, {"PAD_WPTY",2} } },
|
||||||
{ "Intel(R) Core(TM) i7-3770 CPU @ 3.40GHz", { {"PAD_DIMX",32}, {"PAD_DIMY",32}, {"PAD_WPTX",4}, {"PAD_WPTY",1} } },
|
{ "Intel(R) Core(TM) i7-3770 CPU @ 3.40GHz", { {"PAD_DIMX",32}, {"PAD_DIMY",32}, {"PAD_WPTX",4}, {"PAD_WPTY",1} } },
|
||||||
{ "Intel(R) Core(TM) i7-5930K CPU @ 3.50GHz", { {"PAD_DIMX",32}, {"PAD_DIMY",16}, {"PAD_WPTX",4}, {"PAD_WPTY",1} } },
|
{ "Intel(R) Core(TM) i7-5930K CPU @ 3.50GHz", { {"PAD_DIMX",32}, {"PAD_DIMY",16}, {"PAD_WPTX",4}, {"PAD_WPTY",1} } },
|
||||||
{ "default", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",2}, {"PAD_WPTY",1} } },
|
{ "default", { {"PAD_DIMX",32}, {"PAD_DIMY",16}, {"PAD_WPTX",4}, {"PAD_WPTY",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Intel GPUs
|
{ // Intel GPUs
|
||||||
kDeviceTypeGPU, "Intel", {
|
kDeviceTypeGPU, "Intel", {
|
||||||
|
{ "Intel(R) HD Graphics 530", { {"PAD_DIMX",8}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",2} } },
|
||||||
|
{ "Intel(R) HD Graphics 5500 BroadWell U-Processor GT2", { {"PAD_DIMX",8}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
||||||
{ "Intel(R) HD Graphics Haswell Ultrabook GT2 Mobile", { {"PAD_DIMX",8}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
{ "Intel(R) HD Graphics Haswell Ultrabook GT2 Mobile", { {"PAD_DIMX",8}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
||||||
{ "Intel(R) HD Graphics Skylake ULT GT2", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",2}, {"PAD_WPTY",4} } },
|
{ "Intel(R) HD Graphics Skylake ULT GT2", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",2}, {"PAD_WPTY",4} } },
|
||||||
{ "Iris", { {"PAD_DIMX",32}, {"PAD_DIMY",16}, {"PAD_WPTX",2}, {"PAD_WPTY",4} } },
|
{ "Iris", { {"PAD_DIMX",32}, {"PAD_DIMY",16}, {"PAD_WPTX",2}, {"PAD_WPTY",4} } },
|
||||||
{ "Iris Pro", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",2}, {"PAD_WPTY",1} } },
|
{ "Iris Pro", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",2}, {"PAD_WPTY",1} } },
|
||||||
{ "default", { {"PAD_DIMX",8}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
{ "default", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",4} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Intel accelerators
|
{ // Intel accelerators
|
||||||
|
@ -139,20 +149,23 @@ const Database::DatabaseEntry Database::PadComplexSingle = {
|
||||||
{ // NVIDIA GPUs
|
{ // NVIDIA GPUs
|
||||||
kDeviceTypeGPU, "NVIDIA", {
|
kDeviceTypeGPU, "NVIDIA", {
|
||||||
{ "GRID K520", { {"PAD_DIMX",16}, {"PAD_DIMY",16}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
{ "GRID K520", { {"PAD_DIMX",16}, {"PAD_DIMY",16}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
||||||
|
{ "GeForce GTX 1070", { {"PAD_DIMX",8}, {"PAD_DIMY",32}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
||||||
{ "GeForce GTX 480", { {"PAD_DIMX",16}, {"PAD_DIMY",8}, {"PAD_WPTX",2}, {"PAD_WPTY",1} } },
|
{ "GeForce GTX 480", { {"PAD_DIMX",16}, {"PAD_DIMY",8}, {"PAD_WPTX",2}, {"PAD_WPTY",1} } },
|
||||||
|
{ "GeForce GTX 670", { {"PAD_DIMX",16}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",2} } },
|
||||||
{ "GeForce GTX 680", { {"PAD_DIMX",16}, {"PAD_DIMY",32}, {"PAD_WPTX",1}, {"PAD_WPTY",2} } },
|
{ "GeForce GTX 680", { {"PAD_DIMX",16}, {"PAD_DIMY",32}, {"PAD_WPTX",1}, {"PAD_WPTY",2} } },
|
||||||
|
{ "GeForce GTX 750", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",2}, {"PAD_WPTY",1} } },
|
||||||
{ "GeForce GTX 750 Ti", { {"PAD_DIMX",16}, {"PAD_DIMY",16}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
{ "GeForce GTX 750 Ti", { {"PAD_DIMX",16}, {"PAD_DIMY",16}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
||||||
{ "GeForce GTX 980", { {"PAD_DIMX",16}, {"PAD_DIMY",16}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
{ "GeForce GTX 980", { {"PAD_DIMX",16}, {"PAD_DIMY",16}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
||||||
{ "GeForce GTX TITAN", { {"PAD_DIMX",16}, {"PAD_DIMY",8}, {"PAD_WPTX",2}, {"PAD_WPTY",1} } },
|
{ "GeForce GTX TITAN", { {"PAD_DIMX",16}, {"PAD_DIMY",8}, {"PAD_WPTX",2}, {"PAD_WPTY",1} } },
|
||||||
{ "GeForce GTX TITAN X", { {"PAD_DIMX",16}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
{ "GeForce GTX TITAN X", { {"PAD_DIMX",16}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
||||||
{ "Tesla K20m", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",2} } },
|
{ "Tesla K20m", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",2} } },
|
||||||
{ "Tesla K40m", { {"PAD_DIMX",16}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
{ "Tesla K40m", { {"PAD_DIMX",16}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
||||||
{ "default", { {"PAD_DIMX",16}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
{ "default", { {"PAD_DIMX",16}, {"PAD_DIMY",8}, {"PAD_WPTX",2}, {"PAD_WPTY",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Default
|
{ // Default
|
||||||
kDeviceTypeAll, "default", {
|
kDeviceTypeAll, "default", {
|
||||||
{ "default", { {"PAD_DIMX",8}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
{ "default", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
}
|
}
|
||||||
|
@ -166,9 +179,10 @@ const Database::DatabaseEntry Database::PadDouble = {
|
||||||
kDeviceTypeGPU, "AMD", {
|
kDeviceTypeGPU, "AMD", {
|
||||||
{ "AMD Radeon R9 M370X Compute Engine", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
{ "AMD Radeon R9 M370X Compute Engine", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
||||||
{ "Hawaii", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",2} } },
|
{ "Hawaii", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",2} } },
|
||||||
|
{ "Oland", { {"PAD_DIMX",8}, {"PAD_DIMY",32}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
||||||
{ "Pitcairn", { {"PAD_DIMX",8}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",2} } },
|
{ "Pitcairn", { {"PAD_DIMX",8}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",2} } },
|
||||||
{ "Tahiti", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
{ "Tahiti", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
||||||
{ "default", { {"PAD_DIMX",8}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
{ "default", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",2} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // ARM GPUs
|
{ // ARM GPUs
|
||||||
|
@ -182,7 +196,7 @@ const Database::DatabaseEntry Database::PadDouble = {
|
||||||
{ "Intel(R) Core(TM) i5-6200U CPU @ 2.30GHz", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",4}, {"PAD_WPTY",1} } },
|
{ "Intel(R) Core(TM) i5-6200U CPU @ 2.30GHz", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",4}, {"PAD_WPTY",1} } },
|
||||||
{ "Intel(R) Core(TM) i7-3770 CPU @ 3.40GHz", { {"PAD_DIMX",32}, {"PAD_DIMY",32}, {"PAD_WPTX",4}, {"PAD_WPTY",1} } },
|
{ "Intel(R) Core(TM) i7-3770 CPU @ 3.40GHz", { {"PAD_DIMX",32}, {"PAD_DIMY",32}, {"PAD_WPTX",4}, {"PAD_WPTY",1} } },
|
||||||
{ "Intel(R) Core(TM) i7-5930K CPU @ 3.50GHz", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",2}, {"PAD_WPTY",1} } },
|
{ "Intel(R) Core(TM) i7-5930K CPU @ 3.50GHz", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",2}, {"PAD_WPTY",1} } },
|
||||||
{ "default", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",2}, {"PAD_WPTY",1} } },
|
{ "default", { {"PAD_DIMX",32}, {"PAD_DIMY",16}, {"PAD_WPTX",4}, {"PAD_WPTY",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Intel accelerators
|
{ // Intel accelerators
|
||||||
|
@ -194,20 +208,23 @@ const Database::DatabaseEntry Database::PadDouble = {
|
||||||
{ // NVIDIA GPUs
|
{ // NVIDIA GPUs
|
||||||
kDeviceTypeGPU, "NVIDIA", {
|
kDeviceTypeGPU, "NVIDIA", {
|
||||||
{ "GRID K520", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
{ "GRID K520", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
||||||
|
{ "GeForce GTX 1070", { {"PAD_DIMX",8}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
||||||
{ "GeForce GTX 480", { {"PAD_DIMX",16}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
{ "GeForce GTX 480", { {"PAD_DIMX",16}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
||||||
|
{ "GeForce GTX 670", { {"PAD_DIMX",16}, {"PAD_DIMY",16}, {"PAD_WPTX",2}, {"PAD_WPTY",1} } },
|
||||||
{ "GeForce GTX 680", { {"PAD_DIMX",32}, {"PAD_DIMY",32}, {"PAD_WPTX",1}, {"PAD_WPTY",2} } },
|
{ "GeForce GTX 680", { {"PAD_DIMX",32}, {"PAD_DIMY",32}, {"PAD_WPTX",1}, {"PAD_WPTY",2} } },
|
||||||
|
{ "GeForce GTX 750", { {"PAD_DIMX",32}, {"PAD_DIMY",16}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
||||||
{ "GeForce GTX 750 Ti", { {"PAD_DIMX",8}, {"PAD_DIMY",16}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
{ "GeForce GTX 750 Ti", { {"PAD_DIMX",8}, {"PAD_DIMY",16}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
||||||
{ "GeForce GTX 980", { {"PAD_DIMX",8}, {"PAD_DIMY",16}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
{ "GeForce GTX 980", { {"PAD_DIMX",8}, {"PAD_DIMY",16}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
||||||
{ "GeForce GTX TITAN", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
{ "GeForce GTX TITAN", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
||||||
{ "GeForce GTX TITAN X", { {"PAD_DIMX",16}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
{ "GeForce GTX TITAN X", { {"PAD_DIMX",16}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
||||||
{ "Tesla K20m", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
{ "Tesla K20m", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
||||||
{ "Tesla K40m", { {"PAD_DIMX",16}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",2} } },
|
{ "Tesla K40m", { {"PAD_DIMX",16}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",2} } },
|
||||||
{ "default", { {"PAD_DIMX",8}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
{ "default", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Default
|
{ // Default
|
||||||
kDeviceTypeAll, "default", {
|
kDeviceTypeAll, "default", {
|
||||||
{ "default", { {"PAD_DIMX",8}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
{ "default", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
}
|
}
|
||||||
|
@ -221,9 +238,10 @@ const Database::DatabaseEntry Database::PadComplexDouble = {
|
||||||
kDeviceTypeGPU, "AMD", {
|
kDeviceTypeGPU, "AMD", {
|
||||||
{ "AMD Radeon R9 M370X Compute Engine", { {"PAD_DIMX",16}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
{ "AMD Radeon R9 M370X Compute Engine", { {"PAD_DIMX",16}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
||||||
{ "Hawaii", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
{ "Hawaii", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
||||||
|
{ "Oland", { {"PAD_DIMX",8}, {"PAD_DIMY",16}, {"PAD_WPTX",2}, {"PAD_WPTY",1} } },
|
||||||
{ "Pitcairn", { {"PAD_DIMX",16}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
{ "Pitcairn", { {"PAD_DIMX",16}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
||||||
{ "Tahiti", { {"PAD_DIMX",8}, {"PAD_DIMY",16}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
{ "Tahiti", { {"PAD_DIMX",8}, {"PAD_DIMY",16}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
||||||
{ "default", { {"PAD_DIMX",8}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
{ "default", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // ARM GPUs
|
{ // ARM GPUs
|
||||||
|
@ -237,7 +255,7 @@ const Database::DatabaseEntry Database::PadComplexDouble = {
|
||||||
{ "Intel(R) Core(TM) i5-6200U CPU @ 2.30GHz", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",2}, {"PAD_WPTY",1} } },
|
{ "Intel(R) Core(TM) i5-6200U CPU @ 2.30GHz", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",2}, {"PAD_WPTY",1} } },
|
||||||
{ "Intel(R) Core(TM) i7-3770 CPU @ 3.40GHz", { {"PAD_DIMX",16}, {"PAD_DIMY",32}, {"PAD_WPTX",4}, {"PAD_WPTY",1} } },
|
{ "Intel(R) Core(TM) i7-3770 CPU @ 3.40GHz", { {"PAD_DIMX",16}, {"PAD_DIMY",32}, {"PAD_WPTX",4}, {"PAD_WPTY",1} } },
|
||||||
{ "Intel(R) Core(TM) i7-5930K CPU @ 3.50GHz", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",2}, {"PAD_WPTY",1} } },
|
{ "Intel(R) Core(TM) i7-5930K CPU @ 3.50GHz", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",2}, {"PAD_WPTY",1} } },
|
||||||
{ "default", { {"PAD_DIMX",16}, {"PAD_DIMY",8}, {"PAD_WPTX",2}, {"PAD_WPTY",1} } },
|
{ "default", { {"PAD_DIMX",32}, {"PAD_DIMY",16}, {"PAD_WPTX",4}, {"PAD_WPTY",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Intel accelerators
|
{ // Intel accelerators
|
||||||
|
@ -249,20 +267,23 @@ const Database::DatabaseEntry Database::PadComplexDouble = {
|
||||||
{ // NVIDIA GPUs
|
{ // NVIDIA GPUs
|
||||||
kDeviceTypeGPU, "NVIDIA", {
|
kDeviceTypeGPU, "NVIDIA", {
|
||||||
{ "GRID K520", { {"PAD_DIMX",8}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
{ "GRID K520", { {"PAD_DIMX",8}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
||||||
|
{ "GeForce GTX 1070", { {"PAD_DIMX",8}, {"PAD_DIMY",8}, {"PAD_WPTX",2}, {"PAD_WPTY",2} } },
|
||||||
{ "GeForce GTX 480", { {"PAD_DIMX",16}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
{ "GeForce GTX 480", { {"PAD_DIMX",16}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
||||||
|
{ "GeForce GTX 670", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
||||||
{ "GeForce GTX 680", { {"PAD_DIMX",8}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
{ "GeForce GTX 680", { {"PAD_DIMX",8}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
||||||
|
{ "GeForce GTX 750", { {"PAD_DIMX",8}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
||||||
{ "GeForce GTX 750 Ti", { {"PAD_DIMX",32}, {"PAD_DIMY",32}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
{ "GeForce GTX 750 Ti", { {"PAD_DIMX",32}, {"PAD_DIMY",32}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
||||||
{ "GeForce GTX 980", { {"PAD_DIMX",16}, {"PAD_DIMY",16}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
{ "GeForce GTX 980", { {"PAD_DIMX",16}, {"PAD_DIMY",16}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
||||||
{ "GeForce GTX TITAN", { {"PAD_DIMX",8}, {"PAD_DIMY",32}, {"PAD_WPTX",1}, {"PAD_WPTY",2} } },
|
{ "GeForce GTX TITAN", { {"PAD_DIMX",8}, {"PAD_DIMY",32}, {"PAD_WPTX",1}, {"PAD_WPTY",2} } },
|
||||||
{ "GeForce GTX TITAN X", { {"PAD_DIMX",16}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
{ "GeForce GTX TITAN X", { {"PAD_DIMX",16}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
||||||
{ "Tesla K20m", { {"PAD_DIMX",8}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",2} } },
|
{ "Tesla K20m", { {"PAD_DIMX",8}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",2} } },
|
||||||
{ "Tesla K40m", { {"PAD_DIMX",8}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
{ "Tesla K40m", { {"PAD_DIMX",8}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
||||||
{ "default", { {"PAD_DIMX",8}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
{ "default", { {"PAD_DIMX",16}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Default
|
{ // Default
|
||||||
kDeviceTypeAll, "default", {
|
kDeviceTypeAll, "default", {
|
||||||
{ "default", { {"PAD_DIMX",8}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
{ "default", { {"PAD_DIMX",32}, {"PAD_DIMY",8}, {"PAD_WPTX",1}, {"PAD_WPTY",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
}
|
}
|
||||||
|
|
|
@ -18,6 +18,7 @@ const Database::DatabaseEntry Database::PadtransposeHalf = {
|
||||||
"Padtranspose", Precision::kHalf, {
|
"Padtranspose", Precision::kHalf, {
|
||||||
{ // Intel GPUs
|
{ // Intel GPUs
|
||||||
kDeviceTypeGPU, "Intel", {
|
kDeviceTypeGPU, "Intel", {
|
||||||
|
{ "Intel(R) HD Graphics 5500 BroadWell U-Processor GT2", { {"PADTRA_PAD",0}, {"PADTRA_TILE",8}, {"PADTRA_WPT",1} } },
|
||||||
{ "Intel(R) HD Graphics Skylake ULT GT2", { {"PADTRA_PAD",0}, {"PADTRA_TILE",8}, {"PADTRA_WPT",1} } },
|
{ "Intel(R) HD Graphics Skylake ULT GT2", { {"PADTRA_PAD",0}, {"PADTRA_TILE",8}, {"PADTRA_WPT",1} } },
|
||||||
{ "default", { {"PADTRA_PAD",0}, {"PADTRA_TILE",8}, {"PADTRA_WPT",1} } },
|
{ "default", { {"PADTRA_PAD",0}, {"PADTRA_TILE",8}, {"PADTRA_WPT",1} } },
|
||||||
}
|
}
|
||||||
|
@ -38,6 +39,7 @@ const Database::DatabaseEntry Database::PadtransposeSingle = {
|
||||||
kDeviceTypeGPU, "AMD", {
|
kDeviceTypeGPU, "AMD", {
|
||||||
{ "AMD Radeon R9 M370X Compute Engine", { {"PADTRA_PAD",0}, {"PADTRA_TILE",16}, {"PADTRA_WPT",4} } },
|
{ "AMD Radeon R9 M370X Compute Engine", { {"PADTRA_PAD",0}, {"PADTRA_TILE",16}, {"PADTRA_WPT",4} } },
|
||||||
{ "Hawaii", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",4} } },
|
{ "Hawaii", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",4} } },
|
||||||
|
{ "Oland", { {"PADTRA_PAD",0}, {"PADTRA_TILE",16}, {"PADTRA_WPT",4} } },
|
||||||
{ "Pitcairn", { {"PADTRA_PAD",0}, {"PADTRA_TILE",16}, {"PADTRA_WPT",4} } },
|
{ "Pitcairn", { {"PADTRA_PAD",0}, {"PADTRA_TILE",16}, {"PADTRA_WPT",4} } },
|
||||||
{ "Tahiti", { {"PADTRA_PAD",0}, {"PADTRA_TILE",16}, {"PADTRA_WPT",4} } },
|
{ "Tahiti", { {"PADTRA_PAD",0}, {"PADTRA_TILE",16}, {"PADTRA_WPT",4} } },
|
||||||
{ "default", { {"PADTRA_PAD",0}, {"PADTRA_TILE",16}, {"PADTRA_WPT",4} } },
|
{ "default", { {"PADTRA_PAD",0}, {"PADTRA_TILE",16}, {"PADTRA_WPT",4} } },
|
||||||
|
@ -54,11 +56,13 @@ const Database::DatabaseEntry Database::PadtransposeSingle = {
|
||||||
{ "Intel(R) Core(TM) i5-6200U CPU @ 2.30GHz", { {"PADTRA_PAD",0}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
{ "Intel(R) Core(TM) i5-6200U CPU @ 2.30GHz", { {"PADTRA_PAD",0}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
||||||
{ "Intel(R) Core(TM) i7-3770 CPU @ 3.40GHz", { {"PADTRA_PAD",0}, {"PADTRA_TILE",8}, {"PADTRA_WPT",8} } },
|
{ "Intel(R) Core(TM) i7-3770 CPU @ 3.40GHz", { {"PADTRA_PAD",0}, {"PADTRA_TILE",8}, {"PADTRA_WPT",8} } },
|
||||||
{ "Intel(R) Core(TM) i7-5930K CPU @ 3.50GHz", { {"PADTRA_PAD",0}, {"PADTRA_TILE",32}, {"PADTRA_WPT",1} } },
|
{ "Intel(R) Core(TM) i7-5930K CPU @ 3.50GHz", { {"PADTRA_PAD",0}, {"PADTRA_TILE",32}, {"PADTRA_WPT",1} } },
|
||||||
{ "default", { {"PADTRA_PAD",0}, {"PADTRA_TILE",8}, {"PADTRA_WPT",1} } },
|
{ "default", { {"PADTRA_PAD",0}, {"PADTRA_TILE",8}, {"PADTRA_WPT",8} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Intel GPUs
|
{ // Intel GPUs
|
||||||
kDeviceTypeGPU, "Intel", {
|
kDeviceTypeGPU, "Intel", {
|
||||||
|
{ "Intel(R) HD Graphics 530", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",2} } },
|
||||||
|
{ "Intel(R) HD Graphics 5500 BroadWell U-Processor GT2", { {"PADTRA_PAD",0}, {"PADTRA_TILE",16}, {"PADTRA_WPT",4} } },
|
||||||
{ "Intel(R) HD Graphics Haswell Ultrabook GT2 Mobile", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",2} } },
|
{ "Intel(R) HD Graphics Haswell Ultrabook GT2 Mobile", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",2} } },
|
||||||
{ "Intel(R) HD Graphics Skylake ULT GT2", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",2} } },
|
{ "Intel(R) HD Graphics Skylake ULT GT2", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",2} } },
|
||||||
{ "Iris", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",2} } },
|
{ "Iris", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",2} } },
|
||||||
|
@ -75,20 +79,23 @@ const Database::DatabaseEntry Database::PadtransposeSingle = {
|
||||||
{ // NVIDIA GPUs
|
{ // NVIDIA GPUs
|
||||||
kDeviceTypeGPU, "NVIDIA", {
|
kDeviceTypeGPU, "NVIDIA", {
|
||||||
{ "GRID K520", { {"PADTRA_PAD",1}, {"PADTRA_TILE",32}, {"PADTRA_WPT",2} } },
|
{ "GRID K520", { {"PADTRA_PAD",1}, {"PADTRA_TILE",32}, {"PADTRA_WPT",2} } },
|
||||||
|
{ "GeForce GTX 1070", { {"PADTRA_PAD",0}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
||||||
{ "GeForce GTX 480", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",2} } },
|
{ "GeForce GTX 480", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",2} } },
|
||||||
|
{ "GeForce GTX 670", { {"PADTRA_PAD",1}, {"PADTRA_TILE",32}, {"PADTRA_WPT",2} } },
|
||||||
{ "GeForce GTX 680", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",2} } },
|
{ "GeForce GTX 680", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",2} } },
|
||||||
|
{ "GeForce GTX 750", { {"PADTRA_PAD",1}, {"PADTRA_TILE",32}, {"PADTRA_WPT",2} } },
|
||||||
{ "GeForce GTX 750 Ti", { {"PADTRA_PAD",1}, {"PADTRA_TILE",32}, {"PADTRA_WPT",2} } },
|
{ "GeForce GTX 750 Ti", { {"PADTRA_PAD",1}, {"PADTRA_TILE",32}, {"PADTRA_WPT",2} } },
|
||||||
{ "GeForce GTX 980", { {"PADTRA_PAD",0}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
{ "GeForce GTX 980", { {"PADTRA_PAD",0}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
||||||
{ "GeForce GTX TITAN", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",2} } },
|
{ "GeForce GTX TITAN", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",2} } },
|
||||||
{ "GeForce GTX TITAN X", { {"PADTRA_PAD",1}, {"PADTRA_TILE",32}, {"PADTRA_WPT",1} } },
|
{ "GeForce GTX TITAN X", { {"PADTRA_PAD",1}, {"PADTRA_TILE",32}, {"PADTRA_WPT",1} } },
|
||||||
{ "Tesla K20m", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",2} } },
|
{ "Tesla K20m", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",2} } },
|
||||||
{ "Tesla K40m", { {"PADTRA_PAD",1}, {"PADTRA_TILE",32}, {"PADTRA_WPT",2} } },
|
{ "Tesla K40m", { {"PADTRA_PAD",1}, {"PADTRA_TILE",32}, {"PADTRA_WPT",2} } },
|
||||||
{ "default", { {"PADTRA_PAD",0}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
{ "default", { {"PADTRA_PAD",1}, {"PADTRA_TILE",32}, {"PADTRA_WPT",2} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Default
|
{ // Default
|
||||||
kDeviceTypeAll, "default", {
|
kDeviceTypeAll, "default", {
|
||||||
{ "default", { {"PADTRA_PAD",0}, {"PADTRA_TILE",8}, {"PADTRA_WPT",1} } },
|
{ "default", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",2} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
}
|
}
|
||||||
|
@ -102,9 +109,10 @@ const Database::DatabaseEntry Database::PadtransposeComplexSingle = {
|
||||||
kDeviceTypeGPU, "AMD", {
|
kDeviceTypeGPU, "AMD", {
|
||||||
{ "AMD Radeon R9 M370X Compute Engine", { {"PADTRA_PAD",0}, {"PADTRA_TILE",16}, {"PADTRA_WPT",4} } },
|
{ "AMD Radeon R9 M370X Compute Engine", { {"PADTRA_PAD",0}, {"PADTRA_TILE",16}, {"PADTRA_WPT",4} } },
|
||||||
{ "Hawaii", { {"PADTRA_PAD",0}, {"PADTRA_TILE",16}, {"PADTRA_WPT",2} } },
|
{ "Hawaii", { {"PADTRA_PAD",0}, {"PADTRA_TILE",16}, {"PADTRA_WPT",2} } },
|
||||||
|
{ "Oland", { {"PADTRA_PAD",0}, {"PADTRA_TILE",8}, {"PADTRA_WPT",4} } },
|
||||||
{ "Pitcairn", { {"PADTRA_PAD",0}, {"PADTRA_TILE",8}, {"PADTRA_WPT",4} } },
|
{ "Pitcairn", { {"PADTRA_PAD",0}, {"PADTRA_TILE",8}, {"PADTRA_WPT",4} } },
|
||||||
{ "Tahiti", { {"PADTRA_PAD",0}, {"PADTRA_TILE",16}, {"PADTRA_WPT",2} } },
|
{ "Tahiti", { {"PADTRA_PAD",0}, {"PADTRA_TILE",16}, {"PADTRA_WPT",2} } },
|
||||||
{ "default", { {"PADTRA_PAD",0}, {"PADTRA_TILE",8}, {"PADTRA_WPT",2} } },
|
{ "default", { {"PADTRA_PAD",0}, {"PADTRA_TILE",8}, {"PADTRA_WPT",4} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // ARM GPUs
|
{ // ARM GPUs
|
||||||
|
@ -123,11 +131,13 @@ const Database::DatabaseEntry Database::PadtransposeComplexSingle = {
|
||||||
},
|
},
|
||||||
{ // Intel GPUs
|
{ // Intel GPUs
|
||||||
kDeviceTypeGPU, "Intel", {
|
kDeviceTypeGPU, "Intel", {
|
||||||
|
{ "Intel(R) HD Graphics 530", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",2} } },
|
||||||
|
{ "Intel(R) HD Graphics 5500 BroadWell U-Processor GT2", { {"PADTRA_PAD",0}, {"PADTRA_TILE",16}, {"PADTRA_WPT",2} } },
|
||||||
{ "Intel(R) HD Graphics Haswell Ultrabook GT2 Mobile", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",2} } },
|
{ "Intel(R) HD Graphics Haswell Ultrabook GT2 Mobile", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",2} } },
|
||||||
{ "Intel(R) HD Graphics Skylake ULT GT2", { {"PADTRA_PAD",0}, {"PADTRA_TILE",16}, {"PADTRA_WPT",4} } },
|
{ "Intel(R) HD Graphics Skylake ULT GT2", { {"PADTRA_PAD",0}, {"PADTRA_TILE",16}, {"PADTRA_WPT",4} } },
|
||||||
{ "Iris", { {"PADTRA_PAD",0}, {"PADTRA_TILE",16}, {"PADTRA_WPT",2} } },
|
{ "Iris", { {"PADTRA_PAD",0}, {"PADTRA_TILE",16}, {"PADTRA_WPT",2} } },
|
||||||
{ "Iris Pro", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",2} } },
|
{ "Iris Pro", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",2} } },
|
||||||
{ "default", { {"PADTRA_PAD",0}, {"PADTRA_TILE",16}, {"PADTRA_WPT",2} } },
|
{ "default", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",2} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Intel accelerators
|
{ // Intel accelerators
|
||||||
|
@ -139,20 +149,23 @@ const Database::DatabaseEntry Database::PadtransposeComplexSingle = {
|
||||||
{ // NVIDIA GPUs
|
{ // NVIDIA GPUs
|
||||||
kDeviceTypeGPU, "NVIDIA", {
|
kDeviceTypeGPU, "NVIDIA", {
|
||||||
{ "GRID K520", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
{ "GRID K520", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
||||||
|
{ "GeForce GTX 1070", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
||||||
{ "GeForce GTX 480", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
{ "GeForce GTX 480", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
||||||
|
{ "GeForce GTX 670", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
||||||
{ "GeForce GTX 680", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
{ "GeForce GTX 680", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
||||||
|
{ "GeForce GTX 750", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",2} } },
|
||||||
{ "GeForce GTX 750 Ti", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
{ "GeForce GTX 750 Ti", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
||||||
{ "GeForce GTX 980", { {"PADTRA_PAD",0}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
{ "GeForce GTX 980", { {"PADTRA_PAD",0}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
||||||
{ "GeForce GTX TITAN", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
{ "GeForce GTX TITAN", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
||||||
{ "GeForce GTX TITAN X", { {"PADTRA_PAD",1}, {"PADTRA_TILE",32}, {"PADTRA_WPT",1} } },
|
{ "GeForce GTX TITAN X", { {"PADTRA_PAD",1}, {"PADTRA_TILE",32}, {"PADTRA_WPT",1} } },
|
||||||
{ "Tesla K20m", { {"PADTRA_PAD",0}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
{ "Tesla K20m", { {"PADTRA_PAD",0}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
||||||
{ "Tesla K40m", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
{ "Tesla K40m", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
||||||
{ "default", { {"PADTRA_PAD",0}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
{ "default", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Default
|
{ // Default
|
||||||
kDeviceTypeAll, "default", {
|
kDeviceTypeAll, "default", {
|
||||||
{ "default", { {"PADTRA_PAD",0}, {"PADTRA_TILE",8}, {"PADTRA_WPT",1} } },
|
{ "default", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",2} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
}
|
}
|
||||||
|
@ -166,9 +179,10 @@ const Database::DatabaseEntry Database::PadtransposeDouble = {
|
||||||
kDeviceTypeGPU, "AMD", {
|
kDeviceTypeGPU, "AMD", {
|
||||||
{ "AMD Radeon R9 M370X Compute Engine", { {"PADTRA_PAD",0}, {"PADTRA_TILE",16}, {"PADTRA_WPT",4} } },
|
{ "AMD Radeon R9 M370X Compute Engine", { {"PADTRA_PAD",0}, {"PADTRA_TILE",16}, {"PADTRA_WPT",4} } },
|
||||||
{ "Hawaii", { {"PADTRA_PAD",0}, {"PADTRA_TILE",16}, {"PADTRA_WPT",2} } },
|
{ "Hawaii", { {"PADTRA_PAD",0}, {"PADTRA_TILE",16}, {"PADTRA_WPT",2} } },
|
||||||
|
{ "Oland", { {"PADTRA_PAD",0}, {"PADTRA_TILE",16}, {"PADTRA_WPT",4} } },
|
||||||
{ "Pitcairn", { {"PADTRA_PAD",0}, {"PADTRA_TILE",8}, {"PADTRA_WPT",4} } },
|
{ "Pitcairn", { {"PADTRA_PAD",0}, {"PADTRA_TILE",8}, {"PADTRA_WPT",4} } },
|
||||||
{ "Tahiti", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",2} } },
|
{ "Tahiti", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",2} } },
|
||||||
{ "default", { {"PADTRA_PAD",0}, {"PADTRA_TILE",8}, {"PADTRA_WPT",2} } },
|
{ "default", { {"PADTRA_PAD",0}, {"PADTRA_TILE",16}, {"PADTRA_WPT",4} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // ARM GPUs
|
{ // ARM GPUs
|
||||||
|
@ -182,7 +196,7 @@ const Database::DatabaseEntry Database::PadtransposeDouble = {
|
||||||
{ "Intel(R) Core(TM) i5-6200U CPU @ 2.30GHz", { {"PADTRA_PAD",1}, {"PADTRA_TILE",8}, {"PADTRA_WPT",4} } },
|
{ "Intel(R) Core(TM) i5-6200U CPU @ 2.30GHz", { {"PADTRA_PAD",1}, {"PADTRA_TILE",8}, {"PADTRA_WPT",4} } },
|
||||||
{ "Intel(R) Core(TM) i7-3770 CPU @ 3.40GHz", { {"PADTRA_PAD",0}, {"PADTRA_TILE",8}, {"PADTRA_WPT",8} } },
|
{ "Intel(R) Core(TM) i7-3770 CPU @ 3.40GHz", { {"PADTRA_PAD",0}, {"PADTRA_TILE",8}, {"PADTRA_WPT",8} } },
|
||||||
{ "Intel(R) Core(TM) i7-5930K CPU @ 3.50GHz", { {"PADTRA_PAD",1}, {"PADTRA_TILE",32}, {"PADTRA_WPT",1} } },
|
{ "Intel(R) Core(TM) i7-5930K CPU @ 3.50GHz", { {"PADTRA_PAD",1}, {"PADTRA_TILE",32}, {"PADTRA_WPT",1} } },
|
||||||
{ "default", { {"PADTRA_PAD",0}, {"PADTRA_TILE",8}, {"PADTRA_WPT",1} } },
|
{ "default", { {"PADTRA_PAD",1}, {"PADTRA_TILE",8}, {"PADTRA_WPT",4} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Intel accelerators
|
{ // Intel accelerators
|
||||||
|
@ -194,20 +208,23 @@ const Database::DatabaseEntry Database::PadtransposeDouble = {
|
||||||
{ // NVIDIA GPUs
|
{ // NVIDIA GPUs
|
||||||
kDeviceTypeGPU, "NVIDIA", {
|
kDeviceTypeGPU, "NVIDIA", {
|
||||||
{ "GRID K520", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
{ "GRID K520", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
||||||
|
{ "GeForce GTX 1070", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
||||||
{ "GeForce GTX 480", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
{ "GeForce GTX 480", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
||||||
|
{ "GeForce GTX 670", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
||||||
{ "GeForce GTX 680", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
{ "GeForce GTX 680", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
||||||
|
{ "GeForce GTX 750", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",2} } },
|
||||||
{ "GeForce GTX 750 Ti", { {"PADTRA_PAD",1}, {"PADTRA_TILE",32}, {"PADTRA_WPT",2} } },
|
{ "GeForce GTX 750 Ti", { {"PADTRA_PAD",1}, {"PADTRA_TILE",32}, {"PADTRA_WPT",2} } },
|
||||||
{ "GeForce GTX 980", { {"PADTRA_PAD",1}, {"PADTRA_TILE",32}, {"PADTRA_WPT",1} } },
|
{ "GeForce GTX 980", { {"PADTRA_PAD",1}, {"PADTRA_TILE",32}, {"PADTRA_WPT",1} } },
|
||||||
{ "GeForce GTX TITAN", { {"PADTRA_PAD",0}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
{ "GeForce GTX TITAN", { {"PADTRA_PAD",0}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
||||||
{ "GeForce GTX TITAN X", { {"PADTRA_PAD",1}, {"PADTRA_TILE",32}, {"PADTRA_WPT",1} } },
|
{ "GeForce GTX TITAN X", { {"PADTRA_PAD",1}, {"PADTRA_TILE",32}, {"PADTRA_WPT",1} } },
|
||||||
{ "Tesla K20m", { {"PADTRA_PAD",0}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
{ "Tesla K20m", { {"PADTRA_PAD",0}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
||||||
{ "Tesla K40m", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
{ "Tesla K40m", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
||||||
{ "default", { {"PADTRA_PAD",0}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
{ "default", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Default
|
{ // Default
|
||||||
kDeviceTypeAll, "default", {
|
kDeviceTypeAll, "default", {
|
||||||
{ "default", { {"PADTRA_PAD",0}, {"PADTRA_TILE",8}, {"PADTRA_WPT",1} } },
|
{ "default", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",2} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
}
|
}
|
||||||
|
@ -221,9 +238,10 @@ const Database::DatabaseEntry Database::PadtransposeComplexDouble = {
|
||||||
kDeviceTypeGPU, "AMD", {
|
kDeviceTypeGPU, "AMD", {
|
||||||
{ "AMD Radeon R9 M370X Compute Engine", { {"PADTRA_PAD",0}, {"PADTRA_TILE",8}, {"PADTRA_WPT",4} } },
|
{ "AMD Radeon R9 M370X Compute Engine", { {"PADTRA_PAD",0}, {"PADTRA_TILE",8}, {"PADTRA_WPT",4} } },
|
||||||
{ "Hawaii", { {"PADTRA_PAD",0}, {"PADTRA_TILE",8}, {"PADTRA_WPT",4} } },
|
{ "Hawaii", { {"PADTRA_PAD",0}, {"PADTRA_TILE",8}, {"PADTRA_WPT",4} } },
|
||||||
|
{ "Oland", { {"PADTRA_PAD",0}, {"PADTRA_TILE",8}, {"PADTRA_WPT",4} } },
|
||||||
{ "Pitcairn", { {"PADTRA_PAD",0}, {"PADTRA_TILE",8}, {"PADTRA_WPT",4} } },
|
{ "Pitcairn", { {"PADTRA_PAD",0}, {"PADTRA_TILE",8}, {"PADTRA_WPT",4} } },
|
||||||
{ "Tahiti", { {"PADTRA_PAD",0}, {"PADTRA_TILE",8}, {"PADTRA_WPT",2} } },
|
{ "Tahiti", { {"PADTRA_PAD",0}, {"PADTRA_TILE",8}, {"PADTRA_WPT",2} } },
|
||||||
{ "default", { {"PADTRA_PAD",0}, {"PADTRA_TILE",8}, {"PADTRA_WPT",2} } },
|
{ "default", { {"PADTRA_PAD",0}, {"PADTRA_TILE",8}, {"PADTRA_WPT",4} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // ARM GPUs
|
{ // ARM GPUs
|
||||||
|
@ -237,7 +255,7 @@ const Database::DatabaseEntry Database::PadtransposeComplexDouble = {
|
||||||
{ "Intel(R) Core(TM) i5-6200U CPU @ 2.30GHz", { {"PADTRA_PAD",1}, {"PADTRA_TILE",8}, {"PADTRA_WPT",2} } },
|
{ "Intel(R) Core(TM) i5-6200U CPU @ 2.30GHz", { {"PADTRA_PAD",1}, {"PADTRA_TILE",8}, {"PADTRA_WPT",2} } },
|
||||||
{ "Intel(R) Core(TM) i7-3770 CPU @ 3.40GHz", { {"PADTRA_PAD",1}, {"PADTRA_TILE",8}, {"PADTRA_WPT",4} } },
|
{ "Intel(R) Core(TM) i7-3770 CPU @ 3.40GHz", { {"PADTRA_PAD",1}, {"PADTRA_TILE",8}, {"PADTRA_WPT",4} } },
|
||||||
{ "Intel(R) Core(TM) i7-5930K CPU @ 3.50GHz", { {"PADTRA_PAD",1}, {"PADTRA_TILE",8}, {"PADTRA_WPT",4} } },
|
{ "Intel(R) Core(TM) i7-5930K CPU @ 3.50GHz", { {"PADTRA_PAD",1}, {"PADTRA_TILE",8}, {"PADTRA_WPT",4} } },
|
||||||
{ "default", { {"PADTRA_PAD",1}, {"PADTRA_TILE",8}, {"PADTRA_WPT",2} } },
|
{ "default", { {"PADTRA_PAD",1}, {"PADTRA_TILE",8}, {"PADTRA_WPT",4} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Intel accelerators
|
{ // Intel accelerators
|
||||||
|
@ -249,20 +267,23 @@ const Database::DatabaseEntry Database::PadtransposeComplexDouble = {
|
||||||
{ // NVIDIA GPUs
|
{ // NVIDIA GPUs
|
||||||
kDeviceTypeGPU, "NVIDIA", {
|
kDeviceTypeGPU, "NVIDIA", {
|
||||||
{ "GRID K520", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
{ "GRID K520", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
||||||
|
{ "GeForce GTX 1070", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
||||||
{ "GeForce GTX 480", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
{ "GeForce GTX 480", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
||||||
|
{ "GeForce GTX 670", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
||||||
{ "GeForce GTX 680", { {"PADTRA_PAD",1}, {"PADTRA_TILE",32}, {"PADTRA_WPT",1} } },
|
{ "GeForce GTX 680", { {"PADTRA_PAD",1}, {"PADTRA_TILE",32}, {"PADTRA_WPT",1} } },
|
||||||
|
{ "GeForce GTX 750", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
||||||
{ "GeForce GTX 750 Ti", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",2} } },
|
{ "GeForce GTX 750 Ti", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",2} } },
|
||||||
{ "GeForce GTX 980", { {"PADTRA_PAD",0}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
{ "GeForce GTX 980", { {"PADTRA_PAD",0}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
||||||
{ "GeForce GTX TITAN", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
{ "GeForce GTX TITAN", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
||||||
{ "GeForce GTX TITAN X", { {"PADTRA_PAD",1}, {"PADTRA_TILE",32}, {"PADTRA_WPT",1} } },
|
{ "GeForce GTX TITAN X", { {"PADTRA_PAD",1}, {"PADTRA_TILE",32}, {"PADTRA_WPT",1} } },
|
||||||
{ "Tesla K20m", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
{ "Tesla K20m", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
||||||
{ "Tesla K40m", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
{ "Tesla K40m", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
||||||
{ "default", { {"PADTRA_PAD",0}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
{ "default", { {"PADTRA_PAD",1}, {"PADTRA_TILE",16}, {"PADTRA_WPT",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Default
|
{ // Default
|
||||||
kDeviceTypeAll, "default", {
|
kDeviceTypeAll, "default", {
|
||||||
{ "default", { {"PADTRA_PAD",0}, {"PADTRA_TILE",8}, {"PADTRA_WPT",1} } },
|
{ "default", { {"PADTRA_PAD",0}, {"PADTRA_TILE",8}, {"PADTRA_WPT",2} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
}
|
}
|
||||||
|
|
|
@ -18,6 +18,7 @@ const Database::DatabaseEntry Database::TransposeHalf = {
|
||||||
"Transpose", Precision::kHalf, {
|
"Transpose", Precision::kHalf, {
|
||||||
{ // Intel GPUs
|
{ // Intel GPUs
|
||||||
kDeviceTypeGPU, "Intel", {
|
kDeviceTypeGPU, "Intel", {
|
||||||
|
{ "Intel(R) HD Graphics 5500 BroadWell U-Processor GT2", { {"TRA_DIM",8}, {"TRA_PAD",1}, {"TRA_SHUFFLE",1}, {"TRA_WPT",8} } },
|
||||||
{ "Intel(R) HD Graphics Skylake ULT GT2", { {"TRA_DIM",16}, {"TRA_PAD",0}, {"TRA_SHUFFLE",0}, {"TRA_WPT",4} } },
|
{ "Intel(R) HD Graphics Skylake ULT GT2", { {"TRA_DIM",16}, {"TRA_PAD",0}, {"TRA_SHUFFLE",0}, {"TRA_WPT",4} } },
|
||||||
{ "default", { {"TRA_DIM",16}, {"TRA_PAD",0}, {"TRA_SHUFFLE",0}, {"TRA_WPT",4} } },
|
{ "default", { {"TRA_DIM",16}, {"TRA_PAD",0}, {"TRA_SHUFFLE",0}, {"TRA_WPT",4} } },
|
||||||
}
|
}
|
||||||
|
@ -38,9 +39,10 @@ const Database::DatabaseEntry Database::TransposeSingle = {
|
||||||
kDeviceTypeGPU, "AMD", {
|
kDeviceTypeGPU, "AMD", {
|
||||||
{ "AMD Radeon R9 M370X Compute Engine", { {"TRA_DIM",4}, {"TRA_PAD",0}, {"TRA_SHUFFLE",1}, {"TRA_WPT",8} } },
|
{ "AMD Radeon R9 M370X Compute Engine", { {"TRA_DIM",4}, {"TRA_PAD",0}, {"TRA_SHUFFLE",1}, {"TRA_WPT",8} } },
|
||||||
{ "Hawaii", { {"TRA_DIM",4}, {"TRA_PAD",0}, {"TRA_SHUFFLE",1}, {"TRA_WPT",8} } },
|
{ "Hawaii", { {"TRA_DIM",4}, {"TRA_PAD",0}, {"TRA_SHUFFLE",1}, {"TRA_WPT",8} } },
|
||||||
|
{ "Oland", { {"TRA_DIM",8}, {"TRA_PAD",0}, {"TRA_SHUFFLE",1}, {"TRA_WPT",4} } },
|
||||||
{ "Pitcairn", { {"TRA_DIM",16}, {"TRA_PAD",0}, {"TRA_SHUFFLE",1}, {"TRA_WPT",1} } },
|
{ "Pitcairn", { {"TRA_DIM",16}, {"TRA_PAD",0}, {"TRA_SHUFFLE",1}, {"TRA_WPT",1} } },
|
||||||
{ "Tahiti", { {"TRA_DIM",4}, {"TRA_PAD",0}, {"TRA_SHUFFLE",1}, {"TRA_WPT",4} } },
|
{ "Tahiti", { {"TRA_DIM",4}, {"TRA_PAD",0}, {"TRA_SHUFFLE",1}, {"TRA_WPT",4} } },
|
||||||
{ "default", { {"TRA_DIM",4}, {"TRA_PAD",0}, {"TRA_SHUFFLE",1}, {"TRA_WPT",1} } },
|
{ "default", { {"TRA_DIM",4}, {"TRA_PAD",1}, {"TRA_SHUFFLE",1}, {"TRA_WPT",4} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // ARM GPUs
|
{ // ARM GPUs
|
||||||
|
@ -59,11 +61,13 @@ const Database::DatabaseEntry Database::TransposeSingle = {
|
||||||
},
|
},
|
||||||
{ // Intel GPUs
|
{ // Intel GPUs
|
||||||
kDeviceTypeGPU, "Intel", {
|
kDeviceTypeGPU, "Intel", {
|
||||||
{ "Intel(R) HD Graphics Haswell Ultrabook GT2 Mobile", { {"TRA_DIM",8}, {"TRA_PAD",0}, {"TRA_SHUFFLE",0}, {"TRA_WPT",4} } },
|
{ "Intel(R) HD Graphics 530", { {"TRA_DIM",16}, {"TRA_PAD",0}, {"TRA_SHUFFLE",1}, {"TRA_WPT",4} } },
|
||||||
|
{ "Intel(R) HD Graphics 5500 BroadWell U-Processor GT2", { {"TRA_DIM",16}, {"TRA_PAD",0}, {"TRA_SHUFFLE",0}, {"TRA_WPT",4} } },
|
||||||
|
{ "Intel(R) HD Graphics Haswell Ultrabook GT2 Mobile", { {"TRA_DIM",16}, {"TRA_PAD",0}, {"TRA_SHUFFLE",0}, {"TRA_WPT",4} } },
|
||||||
{ "Intel(R) HD Graphics Skylake ULT GT2", { {"TRA_DIM",8}, {"TRA_PAD",0}, {"TRA_SHUFFLE",1}, {"TRA_WPT",4} } },
|
{ "Intel(R) HD Graphics Skylake ULT GT2", { {"TRA_DIM",8}, {"TRA_PAD",0}, {"TRA_SHUFFLE",1}, {"TRA_WPT",4} } },
|
||||||
{ "Iris", { {"TRA_DIM",8}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",4} } },
|
{ "Iris", { {"TRA_DIM",8}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",4} } },
|
||||||
{ "Iris Pro", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",4} } },
|
{ "Iris Pro", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",4} } },
|
||||||
{ "default", { {"TRA_DIM",8}, {"TRA_PAD",0}, {"TRA_SHUFFLE",0}, {"TRA_WPT",4} } },
|
{ "default", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",4} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Intel accelerators
|
{ // Intel accelerators
|
||||||
|
@ -75,20 +79,23 @@ const Database::DatabaseEntry Database::TransposeSingle = {
|
||||||
{ // NVIDIA GPUs
|
{ // NVIDIA GPUs
|
||||||
kDeviceTypeGPU, "NVIDIA", {
|
kDeviceTypeGPU, "NVIDIA", {
|
||||||
{ "GRID K520", { {"TRA_DIM",32}, {"TRA_PAD",1}, {"TRA_SHUFFLE",1}, {"TRA_WPT",2} } },
|
{ "GRID K520", { {"TRA_DIM",32}, {"TRA_PAD",1}, {"TRA_SHUFFLE",1}, {"TRA_WPT",2} } },
|
||||||
|
{ "GeForce GTX 1070", { {"TRA_DIM",8}, {"TRA_PAD",0}, {"TRA_SHUFFLE",1}, {"TRA_WPT",4} } },
|
||||||
{ "GeForce GTX 480", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",2} } },
|
{ "GeForce GTX 480", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",2} } },
|
||||||
|
{ "GeForce GTX 670", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",1}, {"TRA_WPT",2} } },
|
||||||
{ "GeForce GTX 680", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",1}, {"TRA_WPT",2} } },
|
{ "GeForce GTX 680", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",1}, {"TRA_WPT",2} } },
|
||||||
|
{ "GeForce GTX 750", { {"TRA_DIM",4}, {"TRA_PAD",0}, {"TRA_SHUFFLE",0}, {"TRA_WPT",8} } },
|
||||||
{ "GeForce GTX 750 Ti", { {"TRA_DIM",32}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",2} } },
|
{ "GeForce GTX 750 Ti", { {"TRA_DIM",32}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",2} } },
|
||||||
{ "GeForce GTX 980", { {"TRA_DIM",16}, {"TRA_PAD",0}, {"TRA_SHUFFLE",0}, {"TRA_WPT",1} } },
|
{ "GeForce GTX 980", { {"TRA_DIM",16}, {"TRA_PAD",0}, {"TRA_SHUFFLE",0}, {"TRA_WPT",1} } },
|
||||||
{ "GeForce GTX TITAN", { {"TRA_DIM",8}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",4} } },
|
{ "GeForce GTX TITAN", { {"TRA_DIM",8}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",4} } },
|
||||||
{ "GeForce GTX TITAN X", { {"TRA_DIM",16}, {"TRA_PAD",0}, {"TRA_SHUFFLE",0}, {"TRA_WPT",4} } },
|
{ "GeForce GTX TITAN X", { {"TRA_DIM",16}, {"TRA_PAD",0}, {"TRA_SHUFFLE",0}, {"TRA_WPT",4} } },
|
||||||
{ "Tesla K20m", { {"TRA_DIM",8}, {"TRA_PAD",0}, {"TRA_SHUFFLE",0}, {"TRA_WPT",4} } },
|
{ "Tesla K20m", { {"TRA_DIM",8}, {"TRA_PAD",0}, {"TRA_SHUFFLE",0}, {"TRA_WPT",4} } },
|
||||||
{ "Tesla K40m", { {"TRA_DIM",8}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",4} } },
|
{ "Tesla K40m", { {"TRA_DIM",8}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",4} } },
|
||||||
{ "default", { {"TRA_DIM",8}, {"TRA_PAD",0}, {"TRA_SHUFFLE",0}, {"TRA_WPT",1} } },
|
{ "default", { {"TRA_DIM",8}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",4} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Default
|
{ // Default
|
||||||
kDeviceTypeAll, "default", {
|
kDeviceTypeAll, "default", {
|
||||||
{ "default", { {"TRA_DIM",4}, {"TRA_PAD",0}, {"TRA_SHUFFLE",0}, {"TRA_WPT",1} } },
|
{ "default", { {"TRA_DIM",8}, {"TRA_PAD",0}, {"TRA_SHUFFLE",1}, {"TRA_WPT",4} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
}
|
}
|
||||||
|
@ -102,9 +109,10 @@ const Database::DatabaseEntry Database::TransposeComplexSingle = {
|
||||||
kDeviceTypeGPU, "AMD", {
|
kDeviceTypeGPU, "AMD", {
|
||||||
{ "AMD Radeon R9 M370X Compute Engine", { {"TRA_DIM",4}, {"TRA_PAD",1}, {"TRA_SHUFFLE",1}, {"TRA_WPT",4} } },
|
{ "AMD Radeon R9 M370X Compute Engine", { {"TRA_DIM",4}, {"TRA_PAD",1}, {"TRA_SHUFFLE",1}, {"TRA_WPT",4} } },
|
||||||
{ "Hawaii", { {"TRA_DIM",16}, {"TRA_PAD",0}, {"TRA_SHUFFLE",1}, {"TRA_WPT",1} } },
|
{ "Hawaii", { {"TRA_DIM",16}, {"TRA_PAD",0}, {"TRA_SHUFFLE",1}, {"TRA_WPT",1} } },
|
||||||
|
{ "Oland", { {"TRA_DIM",4}, {"TRA_PAD",0}, {"TRA_SHUFFLE",1}, {"TRA_WPT",2} } },
|
||||||
{ "Pitcairn", { {"TRA_DIM",8}, {"TRA_PAD",0}, {"TRA_SHUFFLE",1}, {"TRA_WPT",1} } },
|
{ "Pitcairn", { {"TRA_DIM",8}, {"TRA_PAD",0}, {"TRA_SHUFFLE",1}, {"TRA_WPT",1} } },
|
||||||
{ "Tahiti", { {"TRA_DIM",16}, {"TRA_PAD",0}, {"TRA_SHUFFLE",1}, {"TRA_WPT",1} } },
|
{ "Tahiti", { {"TRA_DIM",16}, {"TRA_PAD",0}, {"TRA_SHUFFLE",1}, {"TRA_WPT",1} } },
|
||||||
{ "default", { {"TRA_DIM",4}, {"TRA_PAD",0}, {"TRA_SHUFFLE",1}, {"TRA_WPT",1} } },
|
{ "default", { {"TRA_DIM",4}, {"TRA_PAD",0}, {"TRA_SHUFFLE",1}, {"TRA_WPT",2} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // ARM GPUs
|
{ // ARM GPUs
|
||||||
|
@ -118,35 +126,40 @@ const Database::DatabaseEntry Database::TransposeComplexSingle = {
|
||||||
{ "Intel(R) Core(TM) i5-6200U CPU @ 2.30GHz", { {"TRA_DIM",8}, {"TRA_PAD",0}, {"TRA_SHUFFLE",0}, {"TRA_WPT",2} } },
|
{ "Intel(R) Core(TM) i5-6200U CPU @ 2.30GHz", { {"TRA_DIM",8}, {"TRA_PAD",0}, {"TRA_SHUFFLE",0}, {"TRA_WPT",2} } },
|
||||||
{ "Intel(R) Core(TM) i7-3770 CPU @ 3.40GHz", { {"TRA_DIM",4}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",8} } },
|
{ "Intel(R) Core(TM) i7-3770 CPU @ 3.40GHz", { {"TRA_DIM",4}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",8} } },
|
||||||
{ "Intel(R) Core(TM) i7-5930K CPU @ 3.50GHz", { {"TRA_DIM",16}, {"TRA_PAD",0}, {"TRA_SHUFFLE",0}, {"TRA_WPT",4} } },
|
{ "Intel(R) Core(TM) i7-5930K CPU @ 3.50GHz", { {"TRA_DIM",16}, {"TRA_PAD",0}, {"TRA_SHUFFLE",0}, {"TRA_WPT",4} } },
|
||||||
{ "default", { {"TRA_DIM",4}, {"TRA_PAD",0}, {"TRA_SHUFFLE",0}, {"TRA_WPT",2} } },
|
{ "default", { {"TRA_DIM",4}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",8} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Intel GPUs
|
{ // Intel GPUs
|
||||||
kDeviceTypeGPU, "Intel", {
|
kDeviceTypeGPU, "Intel", {
|
||||||
|
{ "Intel(R) HD Graphics 530", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",1}, {"TRA_WPT",2} } },
|
||||||
|
{ "Intel(R) HD Graphics 5500 BroadWell U-Processor GT2", { {"TRA_DIM",8}, {"TRA_PAD",0}, {"TRA_SHUFFLE",0}, {"TRA_WPT",2} } },
|
||||||
{ "Intel(R) HD Graphics Haswell Ultrabook GT2 Mobile", { {"TRA_DIM",8}, {"TRA_PAD",0}, {"TRA_SHUFFLE",0}, {"TRA_WPT",2} } },
|
{ "Intel(R) HD Graphics Haswell Ultrabook GT2 Mobile", { {"TRA_DIM",8}, {"TRA_PAD",0}, {"TRA_SHUFFLE",0}, {"TRA_WPT",2} } },
|
||||||
{ "Intel(R) HD Graphics Skylake ULT GT2", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",1}, {"TRA_WPT",2} } },
|
{ "Intel(R) HD Graphics Skylake ULT GT2", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",1}, {"TRA_WPT",2} } },
|
||||||
{ "Iris", { {"TRA_DIM",8}, {"TRA_PAD",0}, {"TRA_SHUFFLE",0}, {"TRA_WPT",2} } },
|
{ "Iris", { {"TRA_DIM",8}, {"TRA_PAD",0}, {"TRA_SHUFFLE",0}, {"TRA_WPT",2} } },
|
||||||
{ "Iris Pro", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",2} } },
|
{ "Iris Pro", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",2} } },
|
||||||
{ "default", { {"TRA_DIM",8}, {"TRA_PAD",0}, {"TRA_SHUFFLE",0}, {"TRA_WPT",2} } },
|
{ "default", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",2} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // NVIDIA GPUs
|
{ // NVIDIA GPUs
|
||||||
kDeviceTypeGPU, "NVIDIA", {
|
kDeviceTypeGPU, "NVIDIA", {
|
||||||
{ "GRID K520", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",1}, {"TRA_WPT",1} } },
|
{ "GRID K520", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",1}, {"TRA_WPT",1} } },
|
||||||
|
{ "GeForce GTX 1070", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",1}, {"TRA_WPT",1} } },
|
||||||
{ "GeForce GTX 480", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",1} } },
|
{ "GeForce GTX 480", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",1} } },
|
||||||
|
{ "GeForce GTX 670", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",1}, {"TRA_WPT",1} } },
|
||||||
{ "GeForce GTX 680", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",1}, {"TRA_WPT",1} } },
|
{ "GeForce GTX 680", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",1}, {"TRA_WPT",1} } },
|
||||||
|
{ "GeForce GTX 750", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",1} } },
|
||||||
{ "GeForce GTX 750 Ti", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",1} } },
|
{ "GeForce GTX 750 Ti", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",1} } },
|
||||||
{ "GeForce GTX 980", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",1} } },
|
{ "GeForce GTX 980", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",1} } },
|
||||||
{ "GeForce GTX TITAN", { {"TRA_DIM",16}, {"TRA_PAD",0}, {"TRA_SHUFFLE",0}, {"TRA_WPT",1} } },
|
{ "GeForce GTX TITAN", { {"TRA_DIM",16}, {"TRA_PAD",0}, {"TRA_SHUFFLE",0}, {"TRA_WPT",1} } },
|
||||||
{ "GeForce GTX TITAN X", { {"TRA_DIM",32}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",1} } },
|
{ "GeForce GTX TITAN X", { {"TRA_DIM",32}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",1} } },
|
||||||
{ "Tesla K20m", { {"TRA_DIM",16}, {"TRA_PAD",0}, {"TRA_SHUFFLE",0}, {"TRA_WPT",1} } },
|
{ "Tesla K20m", { {"TRA_DIM",16}, {"TRA_PAD",0}, {"TRA_SHUFFLE",0}, {"TRA_WPT",1} } },
|
||||||
{ "Tesla K40m", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",1} } },
|
{ "Tesla K40m", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",1} } },
|
||||||
{ "default", { {"TRA_DIM",16}, {"TRA_PAD",0}, {"TRA_SHUFFLE",0}, {"TRA_WPT",1} } },
|
{ "default", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Default
|
{ // Default
|
||||||
kDeviceTypeAll, "default", {
|
kDeviceTypeAll, "default", {
|
||||||
{ "default", { {"TRA_DIM",4}, {"TRA_PAD",0}, {"TRA_SHUFFLE",0}, {"TRA_WPT",1} } },
|
{ "default", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
}
|
}
|
||||||
|
@ -160,9 +173,10 @@ const Database::DatabaseEntry Database::TransposeDouble = {
|
||||||
kDeviceTypeGPU, "AMD", {
|
kDeviceTypeGPU, "AMD", {
|
||||||
{ "AMD Radeon R9 M370X Compute Engine", { {"TRA_DIM",4}, {"TRA_PAD",0}, {"TRA_SHUFFLE",1}, {"TRA_WPT",4} } },
|
{ "AMD Radeon R9 M370X Compute Engine", { {"TRA_DIM",4}, {"TRA_PAD",0}, {"TRA_SHUFFLE",1}, {"TRA_WPT",4} } },
|
||||||
{ "Hawaii", { {"TRA_DIM",16}, {"TRA_PAD",0}, {"TRA_SHUFFLE",1}, {"TRA_WPT",1} } },
|
{ "Hawaii", { {"TRA_DIM",16}, {"TRA_PAD",0}, {"TRA_SHUFFLE",1}, {"TRA_WPT",1} } },
|
||||||
|
{ "Oland", { {"TRA_DIM",8}, {"TRA_PAD",1}, {"TRA_SHUFFLE",1}, {"TRA_WPT",2} } },
|
||||||
{ "Pitcairn", { {"TRA_DIM",4}, {"TRA_PAD",0}, {"TRA_SHUFFLE",1}, {"TRA_WPT",2} } },
|
{ "Pitcairn", { {"TRA_DIM",4}, {"TRA_PAD",0}, {"TRA_SHUFFLE",1}, {"TRA_WPT",2} } },
|
||||||
{ "Tahiti", { {"TRA_DIM",4}, {"TRA_PAD",1}, {"TRA_SHUFFLE",1}, {"TRA_WPT",4} } },
|
{ "Tahiti", { {"TRA_DIM",4}, {"TRA_PAD",1}, {"TRA_SHUFFLE",1}, {"TRA_WPT",4} } },
|
||||||
{ "default", { {"TRA_DIM",4}, {"TRA_PAD",0}, {"TRA_SHUFFLE",1}, {"TRA_WPT",1} } },
|
{ "default", { {"TRA_DIM",4}, {"TRA_PAD",0}, {"TRA_SHUFFLE",1}, {"TRA_WPT",4} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // ARM GPUs
|
{ // ARM GPUs
|
||||||
|
@ -176,7 +190,7 @@ const Database::DatabaseEntry Database::TransposeDouble = {
|
||||||
{ "Intel(R) Core(TM) i5-6200U CPU @ 2.30GHz", { {"TRA_DIM",4}, {"TRA_PAD",0}, {"TRA_SHUFFLE",0}, {"TRA_WPT",4} } },
|
{ "Intel(R) Core(TM) i5-6200U CPU @ 2.30GHz", { {"TRA_DIM",4}, {"TRA_PAD",0}, {"TRA_SHUFFLE",0}, {"TRA_WPT",4} } },
|
||||||
{ "Intel(R) Core(TM) i7-3770 CPU @ 3.40GHz", { {"TRA_DIM",4}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",8} } },
|
{ "Intel(R) Core(TM) i7-3770 CPU @ 3.40GHz", { {"TRA_DIM",4}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",8} } },
|
||||||
{ "Intel(R) Core(TM) i7-5930K CPU @ 3.50GHz", { {"TRA_DIM",4}, {"TRA_PAD",0}, {"TRA_SHUFFLE",0}, {"TRA_WPT",8} } },
|
{ "Intel(R) Core(TM) i7-5930K CPU @ 3.50GHz", { {"TRA_DIM",4}, {"TRA_PAD",0}, {"TRA_SHUFFLE",0}, {"TRA_WPT",8} } },
|
||||||
{ "default", { {"TRA_DIM",4}, {"TRA_PAD",0}, {"TRA_SHUFFLE",0}, {"TRA_WPT",4} } },
|
{ "default", { {"TRA_DIM",4}, {"TRA_PAD",0}, {"TRA_SHUFFLE",0}, {"TRA_WPT",8} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Intel accelerators
|
{ // Intel accelerators
|
||||||
|
@ -188,20 +202,23 @@ const Database::DatabaseEntry Database::TransposeDouble = {
|
||||||
{ // NVIDIA GPUs
|
{ // NVIDIA GPUs
|
||||||
kDeviceTypeGPU, "NVIDIA", {
|
kDeviceTypeGPU, "NVIDIA", {
|
||||||
{ "GRID K520", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",1}, {"TRA_WPT",2} } },
|
{ "GRID K520", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",1}, {"TRA_WPT",2} } },
|
||||||
|
{ "GeForce GTX 1070", { {"TRA_DIM",8}, {"TRA_PAD",0}, {"TRA_SHUFFLE",1}, {"TRA_WPT",2} } },
|
||||||
{ "GeForce GTX 480", { {"TRA_DIM",8}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",2} } },
|
{ "GeForce GTX 480", { {"TRA_DIM",8}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",2} } },
|
||||||
|
{ "GeForce GTX 670", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",1}, {"TRA_WPT",2} } },
|
||||||
{ "GeForce GTX 680", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",1}, {"TRA_WPT",2} } },
|
{ "GeForce GTX 680", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",1}, {"TRA_WPT",2} } },
|
||||||
|
{ "GeForce GTX 750", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",1} } },
|
||||||
{ "GeForce GTX 750 Ti", { {"TRA_DIM",32}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",1} } },
|
{ "GeForce GTX 750 Ti", { {"TRA_DIM",32}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",1} } },
|
||||||
{ "GeForce GTX 980", { {"TRA_DIM",16}, {"TRA_PAD",0}, {"TRA_SHUFFLE",0}, {"TRA_WPT",2} } },
|
{ "GeForce GTX 980", { {"TRA_DIM",16}, {"TRA_PAD",0}, {"TRA_SHUFFLE",0}, {"TRA_WPT",2} } },
|
||||||
{ "GeForce GTX TITAN", { {"TRA_DIM",8}, {"TRA_PAD",0}, {"TRA_SHUFFLE",0}, {"TRA_WPT",2} } },
|
{ "GeForce GTX TITAN", { {"TRA_DIM",8}, {"TRA_PAD",0}, {"TRA_SHUFFLE",0}, {"TRA_WPT",2} } },
|
||||||
{ "GeForce GTX TITAN X", { {"TRA_DIM",32}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",1} } },
|
{ "GeForce GTX TITAN X", { {"TRA_DIM",32}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",1} } },
|
||||||
{ "Tesla K20m", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",2} } },
|
{ "Tesla K20m", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",2} } },
|
||||||
{ "Tesla K40m", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",1}, {"TRA_WPT",2} } },
|
{ "Tesla K40m", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",1}, {"TRA_WPT",2} } },
|
||||||
{ "default", { {"TRA_DIM",8}, {"TRA_PAD",0}, {"TRA_SHUFFLE",0}, {"TRA_WPT",1} } },
|
{ "default", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",1}, {"TRA_WPT",2} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Default
|
{ // Default
|
||||||
kDeviceTypeAll, "default", {
|
kDeviceTypeAll, "default", {
|
||||||
{ "default", { {"TRA_DIM",4}, {"TRA_PAD",0}, {"TRA_SHUFFLE",0}, {"TRA_WPT",1} } },
|
{ "default", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",1}, {"TRA_WPT",2} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
}
|
}
|
||||||
|
@ -215,9 +232,10 @@ const Database::DatabaseEntry Database::TransposeComplexDouble = {
|
||||||
kDeviceTypeGPU, "AMD", {
|
kDeviceTypeGPU, "AMD", {
|
||||||
{ "AMD Radeon R9 M370X Compute Engine", { {"TRA_DIM",4}, {"TRA_PAD",1}, {"TRA_SHUFFLE",1}, {"TRA_WPT",2} } },
|
{ "AMD Radeon R9 M370X Compute Engine", { {"TRA_DIM",4}, {"TRA_PAD",1}, {"TRA_SHUFFLE",1}, {"TRA_WPT",2} } },
|
||||||
{ "Hawaii", { {"TRA_DIM",4}, {"TRA_PAD",0}, {"TRA_SHUFFLE",1}, {"TRA_WPT",2} } },
|
{ "Hawaii", { {"TRA_DIM",4}, {"TRA_PAD",0}, {"TRA_SHUFFLE",1}, {"TRA_WPT",2} } },
|
||||||
|
{ "Oland", { {"TRA_DIM",16}, {"TRA_PAD",0}, {"TRA_SHUFFLE",1}, {"TRA_WPT",1} } },
|
||||||
{ "Pitcairn", { {"TRA_DIM",4}, {"TRA_PAD",0}, {"TRA_SHUFFLE",1}, {"TRA_WPT",1} } },
|
{ "Pitcairn", { {"TRA_DIM",4}, {"TRA_PAD",0}, {"TRA_SHUFFLE",1}, {"TRA_WPT",1} } },
|
||||||
{ "Tahiti", { {"TRA_DIM",16}, {"TRA_PAD",0}, {"TRA_SHUFFLE",1}, {"TRA_WPT",1} } },
|
{ "Tahiti", { {"TRA_DIM",16}, {"TRA_PAD",0}, {"TRA_SHUFFLE",1}, {"TRA_WPT",1} } },
|
||||||
{ "default", { {"TRA_DIM",4}, {"TRA_PAD",0}, {"TRA_SHUFFLE",1}, {"TRA_WPT",1} } },
|
{ "default", { {"TRA_DIM",8}, {"TRA_PAD",1}, {"TRA_SHUFFLE",1}, {"TRA_WPT",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // ARM GPUs
|
{ // ARM GPUs
|
||||||
|
@ -231,26 +249,29 @@ const Database::DatabaseEntry Database::TransposeComplexDouble = {
|
||||||
{ "Intel(R) Core(TM) i5-6200U CPU @ 2.30GHz", { {"TRA_DIM",4}, {"TRA_PAD",0}, {"TRA_SHUFFLE",0}, {"TRA_WPT",4} } },
|
{ "Intel(R) Core(TM) i5-6200U CPU @ 2.30GHz", { {"TRA_DIM",4}, {"TRA_PAD",0}, {"TRA_SHUFFLE",0}, {"TRA_WPT",4} } },
|
||||||
{ "Intel(R) Core(TM) i7-3770 CPU @ 3.40GHz", { {"TRA_DIM",4}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",4} } },
|
{ "Intel(R) Core(TM) i7-3770 CPU @ 3.40GHz", { {"TRA_DIM",4}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",4} } },
|
||||||
{ "Intel(R) Core(TM) i7-5930K CPU @ 3.50GHz", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",2} } },
|
{ "Intel(R) Core(TM) i7-5930K CPU @ 3.50GHz", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",2} } },
|
||||||
{ "default", { {"TRA_DIM",4}, {"TRA_PAD",0}, {"TRA_SHUFFLE",0}, {"TRA_WPT",2} } },
|
{ "default", { {"TRA_DIM",4}, {"TRA_PAD",0}, {"TRA_SHUFFLE",0}, {"TRA_WPT",4} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // NVIDIA GPUs
|
{ // NVIDIA GPUs
|
||||||
kDeviceTypeGPU, "NVIDIA", {
|
kDeviceTypeGPU, "NVIDIA", {
|
||||||
{ "GRID K520", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",1}, {"TRA_WPT",1} } },
|
{ "GRID K520", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",1}, {"TRA_WPT",1} } },
|
||||||
|
{ "GeForce GTX 1070", { {"TRA_DIM",8}, {"TRA_PAD",0}, {"TRA_SHUFFLE",0}, {"TRA_WPT",1} } },
|
||||||
{ "GeForce GTX 480", { {"TRA_DIM",8}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",1} } },
|
{ "GeForce GTX 480", { {"TRA_DIM",8}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",1} } },
|
||||||
|
{ "GeForce GTX 670", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",1}, {"TRA_WPT",1} } },
|
||||||
{ "GeForce GTX 680", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",1}, {"TRA_WPT",1} } },
|
{ "GeForce GTX 680", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",1}, {"TRA_WPT",1} } },
|
||||||
|
{ "GeForce GTX 750", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",1} } },
|
||||||
{ "GeForce GTX 750 Ti", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",1} } },
|
{ "GeForce GTX 750 Ti", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",1} } },
|
||||||
{ "GeForce GTX 980", { {"TRA_DIM",32}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",1} } },
|
{ "GeForce GTX 980", { {"TRA_DIM",32}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",1} } },
|
||||||
{ "GeForce GTX TITAN", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",1} } },
|
{ "GeForce GTX TITAN", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",1} } },
|
||||||
{ "GeForce GTX TITAN X", { {"TRA_DIM",32}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",1} } },
|
{ "GeForce GTX TITAN X", { {"TRA_DIM",32}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",1} } },
|
||||||
{ "Tesla K20m", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",1} } },
|
{ "Tesla K20m", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",1} } },
|
||||||
{ "Tesla K40m", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",1} } },
|
{ "Tesla K40m", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",1} } },
|
||||||
{ "default", { {"TRA_DIM",8}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",1} } },
|
{ "default", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",0}, {"TRA_WPT",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Default
|
{ // Default
|
||||||
kDeviceTypeAll, "default", {
|
kDeviceTypeAll, "default", {
|
||||||
{ "default", { {"TRA_DIM",4}, {"TRA_PAD",0}, {"TRA_SHUFFLE",0}, {"TRA_WPT",1} } },
|
{ "default", { {"TRA_DIM",16}, {"TRA_PAD",1}, {"TRA_SHUFFLE",1}, {"TRA_WPT",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
}
|
}
|
||||||
|
|
|
@ -18,13 +18,14 @@ const Database::DatabaseEntry Database::XaxpyHalf = {
|
||||||
"Xaxpy", Precision::kHalf, {
|
"Xaxpy", Precision::kHalf, {
|
||||||
{ // Intel GPUs
|
{ // Intel GPUs
|
||||||
kDeviceTypeGPU, "Intel", {
|
kDeviceTypeGPU, "Intel", {
|
||||||
|
{ "Intel(R) HD Graphics 5500 BroadWell U-Processor GT2", { {"VW",1}, {"WGS",64}, {"WPT",1} } },
|
||||||
{ "Intel(R) HD Graphics Skylake ULT GT2", { {"VW",4}, {"WGS",512}, {"WPT",8} } },
|
{ "Intel(R) HD Graphics Skylake ULT GT2", { {"VW",4}, {"WGS",512}, {"WPT",8} } },
|
||||||
{ "default", { {"VW",4}, {"WGS",512}, {"WPT",8} } },
|
{ "default", { {"VW",8}, {"WGS",64}, {"WPT",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Default
|
{ // Default
|
||||||
kDeviceTypeAll, "default", {
|
kDeviceTypeAll, "default", {
|
||||||
{ "default", { {"VW",4}, {"WGS",512}, {"WPT",8} } },
|
{ "default", { {"VW",8}, {"WGS",64}, {"WPT",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
}
|
}
|
||||||
|
@ -38,9 +39,10 @@ const Database::DatabaseEntry Database::XaxpySingle = {
|
||||||
kDeviceTypeGPU, "AMD", {
|
kDeviceTypeGPU, "AMD", {
|
||||||
{ "AMD Radeon R9 M370X Compute Engine", { {"VW",1}, {"WGS",128}, {"WPT",1} } },
|
{ "AMD Radeon R9 M370X Compute Engine", { {"VW",1}, {"WGS",128}, {"WPT",1} } },
|
||||||
{ "Hawaii", { {"VW",2}, {"WGS",64}, {"WPT",2} } },
|
{ "Hawaii", { {"VW",2}, {"WGS",64}, {"WPT",2} } },
|
||||||
|
{ "Oland", { {"VW",1}, {"WGS",128}, {"WPT",1} } },
|
||||||
{ "Pitcairn", { {"VW",2}, {"WGS",128}, {"WPT",1} } },
|
{ "Pitcairn", { {"VW",2}, {"WGS",128}, {"WPT",1} } },
|
||||||
{ "Tahiti", { {"VW",2}, {"WGS",64}, {"WPT",1} } },
|
{ "Tahiti", { {"VW",2}, {"WGS",64}, {"WPT",1} } },
|
||||||
{ "default", { {"VW",1}, {"WGS",64}, {"WPT",1} } },
|
{ "default", { {"VW",2}, {"WGS",256}, {"WPT",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // ARM GPUs
|
{ // ARM GPUs
|
||||||
|
@ -54,12 +56,14 @@ const Database::DatabaseEntry Database::XaxpySingle = {
|
||||||
{ "Intel(R) Core(TM) i5-6200U CPU @ 2.30GHz", { {"VW",1}, {"WGS",512}, {"WPT",1} } },
|
{ "Intel(R) Core(TM) i5-6200U CPU @ 2.30GHz", { {"VW",1}, {"WGS",512}, {"WPT",1} } },
|
||||||
{ "Intel(R) Core(TM) i7-3770 CPU @ 3.40GHz", { {"VW",4}, {"WGS",256}, {"WPT",1} } },
|
{ "Intel(R) Core(TM) i7-3770 CPU @ 3.40GHz", { {"VW",4}, {"WGS",256}, {"WPT",1} } },
|
||||||
{ "Intel(R) Core(TM) i7-5930K CPU @ 3.50GHz", { {"VW",1}, {"WGS",128}, {"WPT",1} } },
|
{ "Intel(R) Core(TM) i7-5930K CPU @ 3.50GHz", { {"VW",1}, {"WGS",128}, {"WPT",1} } },
|
||||||
{ "default", { {"VW",1}, {"WGS",128}, {"WPT",1} } },
|
{ "default", { {"VW",2}, {"WGS",256}, {"WPT",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Intel GPUs
|
{ // Intel GPUs
|
||||||
kDeviceTypeGPU, "Intel", {
|
kDeviceTypeGPU, "Intel", {
|
||||||
{ "Intel(R) HD Graphics Haswell Ultrabook GT2 Mobile", { {"VW",8}, {"WGS",256}, {"WPT",1} } },
|
{ "Intel(R) HD Graphics 530", { {"VW",1}, {"WGS",128}, {"WPT",1} } },
|
||||||
|
{ "Intel(R) HD Graphics 5500 BroadWell U-Processor GT2", { {"VW",1}, {"WGS",256}, {"WPT",1} } },
|
||||||
|
{ "Intel(R) HD Graphics Haswell Ultrabook GT2 Mobile", { {"VW",1}, {"WGS",64}, {"WPT",1} } },
|
||||||
{ "Intel(R) HD Graphics Skylake ULT GT2", { {"VW",1}, {"WGS",512}, {"WPT",2} } },
|
{ "Intel(R) HD Graphics Skylake ULT GT2", { {"VW",1}, {"WGS",512}, {"WPT",2} } },
|
||||||
{ "Iris", { {"VW",1}, {"WGS",64}, {"WPT",1} } },
|
{ "Iris", { {"VW",1}, {"WGS",64}, {"WPT",1} } },
|
||||||
{ "Iris Pro", { {"VW",1}, {"WGS",128}, {"WPT",2} } },
|
{ "Iris Pro", { {"VW",1}, {"WGS",128}, {"WPT",2} } },
|
||||||
|
@ -75,20 +79,23 @@ const Database::DatabaseEntry Database::XaxpySingle = {
|
||||||
{ // NVIDIA GPUs
|
{ // NVIDIA GPUs
|
||||||
kDeviceTypeGPU, "NVIDIA", {
|
kDeviceTypeGPU, "NVIDIA", {
|
||||||
{ "GRID K520", { {"VW",2}, {"WGS",64}, {"WPT",1} } },
|
{ "GRID K520", { {"VW",2}, {"WGS",64}, {"WPT",1} } },
|
||||||
{ "GeForce GTX 480", { {"VW",4}, {"WGS",64}, {"WPT",1} } },
|
{ "GeForce GTX 1070", { {"VW",1}, {"WGS",64}, {"WPT",4} } },
|
||||||
{ "GeForce GTX 680", { {"VW",2}, {"WGS",64}, {"WPT",1} } },
|
{ "GeForce GTX 480", { {"VW",2}, {"WGS",128}, {"WPT",1} } },
|
||||||
|
{ "GeForce GTX 670", { {"VW",2}, {"WGS",64}, {"WPT",1} } },
|
||||||
|
{ "GeForce GTX 680", { {"VW",1}, {"WGS",128}, {"WPT",1} } },
|
||||||
|
{ "GeForce GTX 750", { {"VW",1}, {"WGS",64}, {"WPT",1} } },
|
||||||
{ "GeForce GTX 750 Ti", { {"VW",1}, {"WGS",1024}, {"WPT",1} } },
|
{ "GeForce GTX 750 Ti", { {"VW",1}, {"WGS",1024}, {"WPT",1} } },
|
||||||
{ "GeForce GTX 980", { {"VW",1}, {"WGS",1024}, {"WPT",1} } },
|
{ "GeForce GTX 980", { {"VW",1}, {"WGS",1024}, {"WPT",1} } },
|
||||||
{ "GeForce GTX TITAN", { {"VW",4}, {"WGS",256}, {"WPT",1} } },
|
{ "GeForce GTX TITAN", { {"VW",4}, {"WGS",256}, {"WPT",1} } },
|
||||||
{ "GeForce GTX TITAN X", { {"VW",1}, {"WGS",64}, {"WPT",1} } },
|
{ "GeForce GTX TITAN X", { {"VW",1}, {"WGS",64}, {"WPT",1} } },
|
||||||
{ "Tesla K20m", { {"VW",4}, {"WGS",128}, {"WPT",1} } },
|
{ "Tesla K20m", { {"VW",4}, {"WGS",128}, {"WPT",1} } },
|
||||||
{ "Tesla K40m", { {"VW",4}, {"WGS",128}, {"WPT",1} } },
|
{ "Tesla K40m", { {"VW",4}, {"WGS",128}, {"WPT",1} } },
|
||||||
{ "default", { {"VW",1}, {"WGS",64}, {"WPT",1} } },
|
{ "default", { {"VW",4}, {"WGS",64}, {"WPT",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Default
|
{ // Default
|
||||||
kDeviceTypeAll, "default", {
|
kDeviceTypeAll, "default", {
|
||||||
{ "default", { {"VW",1}, {"WGS",64}, {"WPT",1} } },
|
{ "default", { {"VW",4}, {"WGS",64}, {"WPT",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
}
|
}
|
||||||
|
@ -102,9 +109,10 @@ const Database::DatabaseEntry Database::XaxpyComplexSingle = {
|
||||||
kDeviceTypeGPU, "AMD", {
|
kDeviceTypeGPU, "AMD", {
|
||||||
{ "AMD Radeon R9 M370X Compute Engine", { {"VW",2}, {"WGS",64}, {"WPT",8} } },
|
{ "AMD Radeon R9 M370X Compute Engine", { {"VW",2}, {"WGS",64}, {"WPT",8} } },
|
||||||
{ "Hawaii", { {"VW",1}, {"WGS",128}, {"WPT",2} } },
|
{ "Hawaii", { {"VW",1}, {"WGS",128}, {"WPT",2} } },
|
||||||
|
{ "Oland", { {"VW",1}, {"WGS",128}, {"WPT",1} } },
|
||||||
{ "Pitcairn", { {"VW",1}, {"WGS",64}, {"WPT",1} } },
|
{ "Pitcairn", { {"VW",1}, {"WGS",64}, {"WPT",1} } },
|
||||||
{ "Tahiti", { {"VW",1}, {"WGS",64}, {"WPT",1} } },
|
{ "Tahiti", { {"VW",1}, {"WGS",64}, {"WPT",1} } },
|
||||||
{ "default", { {"VW",1}, {"WGS",64}, {"WPT",1} } },
|
{ "default", { {"VW",1}, {"WGS",128}, {"WPT",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // ARM GPUs
|
{ // ARM GPUs
|
||||||
|
@ -118,16 +126,18 @@ const Database::DatabaseEntry Database::XaxpyComplexSingle = {
|
||||||
{ "Intel(R) Core(TM) i5-6200U CPU @ 2.30GHz", { {"VW",4}, {"WGS",256}, {"WPT",1} } },
|
{ "Intel(R) Core(TM) i5-6200U CPU @ 2.30GHz", { {"VW",4}, {"WGS",256}, {"WPT",1} } },
|
||||||
{ "Intel(R) Core(TM) i7-3770 CPU @ 3.40GHz", { {"VW",1}, {"WGS",1024}, {"WPT",2} } },
|
{ "Intel(R) Core(TM) i7-3770 CPU @ 3.40GHz", { {"VW",1}, {"WGS",1024}, {"WPT",2} } },
|
||||||
{ "Intel(R) Core(TM) i7-5930K CPU @ 3.50GHz", { {"VW",2}, {"WGS",1024}, {"WPT",1} } },
|
{ "Intel(R) Core(TM) i7-5930K CPU @ 3.50GHz", { {"VW",2}, {"WGS",1024}, {"WPT",1} } },
|
||||||
{ "default", { {"VW",1}, {"WGS",256}, {"WPT",1} } },
|
{ "default", { {"VW",8}, {"WGS",1024}, {"WPT",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Intel GPUs
|
{ // Intel GPUs
|
||||||
kDeviceTypeGPU, "Intel", {
|
kDeviceTypeGPU, "Intel", {
|
||||||
|
{ "Intel(R) HD Graphics 530", { {"VW",4}, {"WGS",64}, {"WPT",2} } },
|
||||||
|
{ "Intel(R) HD Graphics 5500 BroadWell U-Processor GT2", { {"VW",1}, {"WGS",64}, {"WPT",1} } },
|
||||||
{ "Intel(R) HD Graphics Haswell Ultrabook GT2 Mobile", { {"VW",1}, {"WGS",64}, {"WPT",1} } },
|
{ "Intel(R) HD Graphics Haswell Ultrabook GT2 Mobile", { {"VW",1}, {"WGS",64}, {"WPT",1} } },
|
||||||
{ "Intel(R) HD Graphics Skylake ULT GT2", { {"VW",2}, {"WGS",512}, {"WPT",1} } },
|
{ "Intel(R) HD Graphics Skylake ULT GT2", { {"VW",2}, {"WGS",512}, {"WPT",1} } },
|
||||||
{ "Iris", { {"VW",2}, {"WGS",128}, {"WPT",1} } },
|
{ "Iris", { {"VW",2}, {"WGS",128}, {"WPT",1} } },
|
||||||
{ "Iris Pro", { {"VW",1}, {"WGS",256}, {"WPT",8} } },
|
{ "Iris Pro", { {"VW",1}, {"WGS",256}, {"WPT",8} } },
|
||||||
{ "default", { {"VW",1}, {"WGS",64}, {"WPT",1} } },
|
{ "default", { {"VW",1}, {"WGS",256}, {"WPT",2} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Intel accelerators
|
{ // Intel accelerators
|
||||||
|
@ -139,20 +149,23 @@ const Database::DatabaseEntry Database::XaxpyComplexSingle = {
|
||||||
{ // NVIDIA GPUs
|
{ // NVIDIA GPUs
|
||||||
kDeviceTypeGPU, "NVIDIA", {
|
kDeviceTypeGPU, "NVIDIA", {
|
||||||
{ "GRID K520", { {"VW",1}, {"WGS",512}, {"WPT",1} } },
|
{ "GRID K520", { {"VW",1}, {"WGS",512}, {"WPT",1} } },
|
||||||
|
{ "GeForce GTX 1070", { {"VW",1}, {"WGS",64}, {"WPT",2} } },
|
||||||
{ "GeForce GTX 480", { {"VW",1}, {"WGS",256}, {"WPT",1} } },
|
{ "GeForce GTX 480", { {"VW",1}, {"WGS",256}, {"WPT",1} } },
|
||||||
|
{ "GeForce GTX 670", { {"VW",1}, {"WGS",256}, {"WPT",1} } },
|
||||||
{ "GeForce GTX 680", { {"VW",1}, {"WGS",256}, {"WPT",1} } },
|
{ "GeForce GTX 680", { {"VW",1}, {"WGS",256}, {"WPT",1} } },
|
||||||
|
{ "GeForce GTX 750", { {"VW",1}, {"WGS",512}, {"WPT",1} } },
|
||||||
{ "GeForce GTX 750 Ti", { {"VW",1}, {"WGS",512}, {"WPT",1} } },
|
{ "GeForce GTX 750 Ti", { {"VW",1}, {"WGS",512}, {"WPT",1} } },
|
||||||
{ "GeForce GTX 980", { {"VW",1}, {"WGS",64}, {"WPT",1} } },
|
{ "GeForce GTX 980", { {"VW",1}, {"WGS",64}, {"WPT",1} } },
|
||||||
{ "GeForce GTX TITAN", { {"VW",1}, {"WGS",256}, {"WPT",1} } },
|
{ "GeForce GTX TITAN", { {"VW",1}, {"WGS",256}, {"WPT",1} } },
|
||||||
{ "GeForce GTX TITAN X", { {"VW",1}, {"WGS",512}, {"WPT",1} } },
|
{ "GeForce GTX TITAN X", { {"VW",1}, {"WGS",512}, {"WPT",1} } },
|
||||||
{ "Tesla K20m", { {"VW",1}, {"WGS",128}, {"WPT",1} } },
|
{ "Tesla K20m", { {"VW",1}, {"WGS",128}, {"WPT",1} } },
|
||||||
{ "Tesla K40m", { {"VW",1}, {"WGS",128}, {"WPT",1} } },
|
{ "Tesla K40m", { {"VW",1}, {"WGS",128}, {"WPT",1} } },
|
||||||
{ "default", { {"VW",1}, {"WGS",64}, {"WPT",1} } },
|
{ "default", { {"VW",1}, {"WGS",256}, {"WPT",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Default
|
{ // Default
|
||||||
kDeviceTypeAll, "default", {
|
kDeviceTypeAll, "default", {
|
||||||
{ "default", { {"VW",1}, {"WGS",64}, {"WPT",1} } },
|
{ "default", { {"VW",1}, {"WGS",128}, {"WPT",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
}
|
}
|
||||||
|
@ -166,6 +179,7 @@ const Database::DatabaseEntry Database::XaxpyDouble = {
|
||||||
kDeviceTypeGPU, "AMD", {
|
kDeviceTypeGPU, "AMD", {
|
||||||
{ "AMD Radeon R9 M370X Compute Engine", { {"VW",1}, {"WGS",256}, {"WPT",1} } },
|
{ "AMD Radeon R9 M370X Compute Engine", { {"VW",1}, {"WGS",256}, {"WPT",1} } },
|
||||||
{ "Hawaii", { {"VW",1}, {"WGS",64}, {"WPT",2} } },
|
{ "Hawaii", { {"VW",1}, {"WGS",64}, {"WPT",2} } },
|
||||||
|
{ "Oland", { {"VW",1}, {"WGS",64}, {"WPT",1} } },
|
||||||
{ "Pitcairn", { {"VW",1}, {"WGS",128}, {"WPT",1} } },
|
{ "Pitcairn", { {"VW",1}, {"WGS",128}, {"WPT",1} } },
|
||||||
{ "Tahiti", { {"VW",1}, {"WGS",64}, {"WPT",1} } },
|
{ "Tahiti", { {"VW",1}, {"WGS",64}, {"WPT",1} } },
|
||||||
{ "default", { {"VW",1}, {"WGS",64}, {"WPT",1} } },
|
{ "default", { {"VW",1}, {"WGS",64}, {"WPT",1} } },
|
||||||
|
@ -182,7 +196,7 @@ const Database::DatabaseEntry Database::XaxpyDouble = {
|
||||||
{ "Intel(R) Core(TM) i5-6200U CPU @ 2.30GHz", { {"VW",1}, {"WGS",1024}, {"WPT",1} } },
|
{ "Intel(R) Core(TM) i5-6200U CPU @ 2.30GHz", { {"VW",1}, {"WGS",1024}, {"WPT",1} } },
|
||||||
{ "Intel(R) Core(TM) i7-3770 CPU @ 3.40GHz", { {"VW",8}, {"WGS",64}, {"WPT",1} } },
|
{ "Intel(R) Core(TM) i7-3770 CPU @ 3.40GHz", { {"VW",8}, {"WGS",64}, {"WPT",1} } },
|
||||||
{ "Intel(R) Core(TM) i7-5930K CPU @ 3.50GHz", { {"VW",8}, {"WGS",2048}, {"WPT",1} } },
|
{ "Intel(R) Core(TM) i7-5930K CPU @ 3.50GHz", { {"VW",8}, {"WGS",2048}, {"WPT",1} } },
|
||||||
{ "default", { {"VW",1}, {"WGS",64}, {"WPT",1} } },
|
{ "default", { {"VW",8}, {"WGS",512}, {"WPT",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Intel accelerators
|
{ // Intel accelerators
|
||||||
|
@ -194,15 +208,18 @@ const Database::DatabaseEntry Database::XaxpyDouble = {
|
||||||
{ // NVIDIA GPUs
|
{ // NVIDIA GPUs
|
||||||
kDeviceTypeGPU, "NVIDIA", {
|
kDeviceTypeGPU, "NVIDIA", {
|
||||||
{ "GRID K520", { {"VW",1}, {"WGS",64}, {"WPT",1} } },
|
{ "GRID K520", { {"VW",1}, {"WGS",64}, {"WPT",1} } },
|
||||||
{ "GeForce GTX 480", { {"VW",2}, {"WGS",64}, {"WPT",1} } },
|
{ "GeForce GTX 1070", { {"VW",1}, {"WGS",64}, {"WPT",8} } },
|
||||||
|
{ "GeForce GTX 480", { {"VW",1}, {"WGS",128}, {"WPT",1} } },
|
||||||
|
{ "GeForce GTX 670", { {"VW",1}, {"WGS",64}, {"WPT",1} } },
|
||||||
{ "GeForce GTX 680", { {"VW",1}, {"WGS",64}, {"WPT",1} } },
|
{ "GeForce GTX 680", { {"VW",1}, {"WGS",64}, {"WPT",1} } },
|
||||||
|
{ "GeForce GTX 750", { {"VW",1}, {"WGS",128}, {"WPT",1} } },
|
||||||
{ "GeForce GTX 750 Ti", { {"VW",1}, {"WGS",64}, {"WPT",1} } },
|
{ "GeForce GTX 750 Ti", { {"VW",1}, {"WGS",64}, {"WPT",1} } },
|
||||||
{ "GeForce GTX 980", { {"VW",1}, {"WGS",256}, {"WPT",1} } },
|
{ "GeForce GTX 980", { {"VW",1}, {"WGS",256}, {"WPT",1} } },
|
||||||
{ "GeForce GTX TITAN", { {"VW",2}, {"WGS",1024}, {"WPT",1} } },
|
{ "GeForce GTX TITAN", { {"VW",2}, {"WGS",1024}, {"WPT",1} } },
|
||||||
{ "GeForce GTX TITAN X", { {"VW",1}, {"WGS",512}, {"WPT",1} } },
|
{ "GeForce GTX TITAN X", { {"VW",1}, {"WGS",512}, {"WPT",1} } },
|
||||||
{ "Tesla K20m", { {"VW",2}, {"WGS",128}, {"WPT",1} } },
|
{ "Tesla K20m", { {"VW",2}, {"WGS",128}, {"WPT",1} } },
|
||||||
{ "Tesla K40m", { {"VW",2}, {"WGS",128}, {"WPT",1} } },
|
{ "Tesla K40m", { {"VW",2}, {"WGS",128}, {"WPT",1} } },
|
||||||
{ "default", { {"VW",1}, {"WGS",64}, {"WPT",1} } },
|
{ "default", { {"VW",1}, {"WGS",128}, {"WPT",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Default
|
{ // Default
|
||||||
|
@ -221,9 +238,10 @@ const Database::DatabaseEntry Database::XaxpyComplexDouble = {
|
||||||
kDeviceTypeGPU, "AMD", {
|
kDeviceTypeGPU, "AMD", {
|
||||||
{ "AMD Radeon R9 M370X Compute Engine", { {"VW",1}, {"WGS",128}, {"WPT",1} } },
|
{ "AMD Radeon R9 M370X Compute Engine", { {"VW",1}, {"WGS",128}, {"WPT",1} } },
|
||||||
{ "Hawaii", { {"VW",2}, {"WGS",64}, {"WPT",1} } },
|
{ "Hawaii", { {"VW",2}, {"WGS",64}, {"WPT",1} } },
|
||||||
|
{ "Oland", { {"VW",1}, {"WGS",256}, {"WPT",1} } },
|
||||||
{ "Pitcairn", { {"VW",1}, {"WGS",128}, {"WPT",1} } },
|
{ "Pitcairn", { {"VW",1}, {"WGS",128}, {"WPT",1} } },
|
||||||
{ "Tahiti", { {"VW",1}, {"WGS",128}, {"WPT",1} } },
|
{ "Tahiti", { {"VW",1}, {"WGS",128}, {"WPT",1} } },
|
||||||
{ "default", { {"VW",1}, {"WGS",64}, {"WPT",1} } },
|
{ "default", { {"VW",1}, {"WGS",128}, {"WPT",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // ARM GPUs
|
{ // ARM GPUs
|
||||||
|
@ -237,7 +255,7 @@ const Database::DatabaseEntry Database::XaxpyComplexDouble = {
|
||||||
{ "Intel(R) Core(TM) i5-6200U CPU @ 2.30GHz", { {"VW",8}, {"WGS",128}, {"WPT",1} } },
|
{ "Intel(R) Core(TM) i5-6200U CPU @ 2.30GHz", { {"VW",8}, {"WGS",128}, {"WPT",1} } },
|
||||||
{ "Intel(R) Core(TM) i7-3770 CPU @ 3.40GHz", { {"VW",8}, {"WGS",512}, {"WPT",1} } },
|
{ "Intel(R) Core(TM) i7-3770 CPU @ 3.40GHz", { {"VW",8}, {"WGS",512}, {"WPT",1} } },
|
||||||
{ "Intel(R) Core(TM) i7-5930K CPU @ 3.50GHz", { {"VW",1}, {"WGS",256}, {"WPT",1} } },
|
{ "Intel(R) Core(TM) i7-5930K CPU @ 3.50GHz", { {"VW",1}, {"WGS",256}, {"WPT",1} } },
|
||||||
{ "default", { {"VW",1}, {"WGS",128}, {"WPT",1} } },
|
{ "default", { {"VW",4}, {"WGS",1024}, {"WPT",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Intel accelerators
|
{ // Intel accelerators
|
||||||
|
@ -249,8 +267,11 @@ const Database::DatabaseEntry Database::XaxpyComplexDouble = {
|
||||||
{ // NVIDIA GPUs
|
{ // NVIDIA GPUs
|
||||||
kDeviceTypeGPU, "NVIDIA", {
|
kDeviceTypeGPU, "NVIDIA", {
|
||||||
{ "GRID K520", { {"VW",1}, {"WGS",64}, {"WPT",1} } },
|
{ "GRID K520", { {"VW",1}, {"WGS",64}, {"WPT",1} } },
|
||||||
|
{ "GeForce GTX 1070", { {"VW",1}, {"WGS",64}, {"WPT",2} } },
|
||||||
{ "GeForce GTX 480", { {"VW",1}, {"WGS",128}, {"WPT",1} } },
|
{ "GeForce GTX 480", { {"VW",1}, {"WGS",128}, {"WPT",1} } },
|
||||||
|
{ "GeForce GTX 670", { {"VW",1}, {"WGS",256}, {"WPT",1} } },
|
||||||
{ "GeForce GTX 680", { {"VW",1}, {"WGS",64}, {"WPT",1} } },
|
{ "GeForce GTX 680", { {"VW",1}, {"WGS",64}, {"WPT",1} } },
|
||||||
|
{ "GeForce GTX 750", { {"VW",1}, {"WGS",1024}, {"WPT",1} } },
|
||||||
{ "GeForce GTX 750 Ti", { {"VW",1}, {"WGS",256}, {"WPT",2} } },
|
{ "GeForce GTX 750 Ti", { {"VW",1}, {"WGS",256}, {"WPT",2} } },
|
||||||
{ "GeForce GTX 980", { {"VW",1}, {"WGS",1024}, {"WPT",1} } },
|
{ "GeForce GTX 980", { {"VW",1}, {"WGS",1024}, {"WPT",1} } },
|
||||||
{ "GeForce GTX TITAN", { {"VW",1}, {"WGS",64}, {"WPT",4} } },
|
{ "GeForce GTX TITAN", { {"VW",1}, {"WGS",64}, {"WPT",4} } },
|
||||||
|
@ -262,7 +283,7 @@ const Database::DatabaseEntry Database::XaxpyComplexDouble = {
|
||||||
},
|
},
|
||||||
{ // Default
|
{ // Default
|
||||||
kDeviceTypeAll, "default", {
|
kDeviceTypeAll, "default", {
|
||||||
{ "default", { {"VW",1}, {"WGS",64}, {"WPT",1} } },
|
{ "default", { {"VW",1}, {"WGS",128}, {"WPT",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
}
|
}
|
||||||
|
|
|
@ -18,6 +18,7 @@ const Database::DatabaseEntry Database::XdotHalf = {
|
||||||
"Xdot", Precision::kHalf, {
|
"Xdot", Precision::kHalf, {
|
||||||
{ // Intel GPUs
|
{ // Intel GPUs
|
||||||
kDeviceTypeGPU, "Intel", {
|
kDeviceTypeGPU, "Intel", {
|
||||||
|
{ "Intel(R) HD Graphics 5500 BroadWell U-Processor GT2", { {"WGS1",256}, {"WGS2",32} } },
|
||||||
{ "Intel(R) HD Graphics Skylake ULT GT2", { {"WGS1",32}, {"WGS2",32} } },
|
{ "Intel(R) HD Graphics Skylake ULT GT2", { {"WGS1",32}, {"WGS2",32} } },
|
||||||
{ "default", { {"WGS1",32}, {"WGS2",32} } },
|
{ "default", { {"WGS1",32}, {"WGS2",32} } },
|
||||||
}
|
}
|
||||||
|
@ -37,7 +38,7 @@ const Database::DatabaseEntry Database::XdotSingle = {
|
||||||
{ // AMD GPUs
|
{ // AMD GPUs
|
||||||
kDeviceTypeGPU, "AMD", {
|
kDeviceTypeGPU, "AMD", {
|
||||||
{ "AMD Radeon R9 M370X Compute Engine", { {"WGS1",128}, {"WGS2",32} } },
|
{ "AMD Radeon R9 M370X Compute Engine", { {"WGS1",128}, {"WGS2",32} } },
|
||||||
{ "Hawaii", { {"WGS1",256}, {"WGS2",32} } },
|
{ "Oland", { {"WGS1",256}, {"WGS2",32} } },
|
||||||
{ "Pitcairn", { {"WGS1",128}, {"WGS2",32} } },
|
{ "Pitcairn", { {"WGS1",128}, {"WGS2",32} } },
|
||||||
{ "Tahiti", { {"WGS1",128}, {"WGS2",32} } },
|
{ "Tahiti", { {"WGS1",128}, {"WGS2",32} } },
|
||||||
{ "default", { {"WGS1",128}, {"WGS2",32} } },
|
{ "default", { {"WGS1",128}, {"WGS2",32} } },
|
||||||
|
@ -51,26 +52,31 @@ const Database::DatabaseEntry Database::XdotSingle = {
|
||||||
},
|
},
|
||||||
{ // Intel GPUs
|
{ // Intel GPUs
|
||||||
kDeviceTypeGPU, "Intel", {
|
kDeviceTypeGPU, "Intel", {
|
||||||
{ "Intel(R) HD Graphics Haswell Ultrabook GT2 Mobile", { {"WGS1",32}, {"WGS2",32} } },
|
{ "Intel(R) HD Graphics 530", { {"WGS1",64}, {"WGS2",32} } },
|
||||||
|
{ "Intel(R) HD Graphics 5500 BroadWell U-Processor GT2", { {"WGS1",256}, {"WGS2",32} } },
|
||||||
|
{ "Intel(R) HD Graphics Haswell Ultrabook GT2 Mobile", { {"WGS1",64}, {"WGS2",32} } },
|
||||||
{ "Intel(R) HD Graphics Skylake ULT GT2", { {"WGS1",64}, {"WGS2",32} } },
|
{ "Intel(R) HD Graphics Skylake ULT GT2", { {"WGS1",64}, {"WGS2",32} } },
|
||||||
{ "Iris Pro", { {"WGS1",512}, {"WGS2",64} } },
|
{ "Iris Pro", { {"WGS1",512}, {"WGS2",64} } },
|
||||||
{ "default", { {"WGS1",32}, {"WGS2",32} } },
|
{ "default", { {"WGS1",64}, {"WGS2",32} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // NVIDIA GPUs
|
{ // NVIDIA GPUs
|
||||||
kDeviceTypeGPU, "NVIDIA", {
|
kDeviceTypeGPU, "NVIDIA", {
|
||||||
{ "GRID K520", { {"WGS1",128}, {"WGS2",32} } },
|
{ "GRID K520", { {"WGS1",128}, {"WGS2",32} } },
|
||||||
|
{ "GeForce GTX 1070", { {"WGS1",128}, {"WGS2",1024} } },
|
||||||
{ "GeForce GTX 480", { {"WGS1",512}, {"WGS2",32} } },
|
{ "GeForce GTX 480", { {"WGS1",512}, {"WGS2",32} } },
|
||||||
|
{ "GeForce GTX 670", { {"WGS1",512}, {"WGS2",1024} } },
|
||||||
{ "GeForce GTX 680", { {"WGS1",128}, {"WGS2",128} } },
|
{ "GeForce GTX 680", { {"WGS1",128}, {"WGS2",128} } },
|
||||||
|
{ "GeForce GTX 750", { {"WGS1",128}, {"WGS2",32} } },
|
||||||
{ "GeForce GTX 980", { {"WGS1",256}, {"WGS2",32} } },
|
{ "GeForce GTX 980", { {"WGS1",256}, {"WGS2",32} } },
|
||||||
{ "GeForce GTX TITAN X", { {"WGS1",256}, {"WGS2",32} } },
|
{ "GeForce GTX TITAN X", { {"WGS1",256}, {"WGS2",32} } },
|
||||||
{ "Tesla K20m", { {"WGS1",1024}, {"WGS2",32} } },
|
{ "Tesla K20m", { {"WGS1",1024}, {"WGS2",32} } },
|
||||||
{ "default", { {"WGS1",128}, {"WGS2",32} } },
|
{ "default", { {"WGS1",256}, {"WGS2",256} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Default
|
{ // Default
|
||||||
kDeviceTypeAll, "default", {
|
kDeviceTypeAll, "default", {
|
||||||
{ "default", { {"WGS1",32}, {"WGS2",32} } },
|
{ "default", { {"WGS1",256}, {"WGS2",32} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
}
|
}
|
||||||
|
@ -83,10 +89,10 @@ const Database::DatabaseEntry Database::XdotComplexSingle = {
|
||||||
{ // AMD GPUs
|
{ // AMD GPUs
|
||||||
kDeviceTypeGPU, "AMD", {
|
kDeviceTypeGPU, "AMD", {
|
||||||
{ "AMD Radeon R9 M370X Compute Engine", { {"WGS1",64}, {"WGS2",32} } },
|
{ "AMD Radeon R9 M370X Compute Engine", { {"WGS1",64}, {"WGS2",32} } },
|
||||||
{ "Hawaii", { {"WGS1",256}, {"WGS2",32} } },
|
{ "Oland", { {"WGS1",128}, {"WGS2",32} } },
|
||||||
{ "Pitcairn", { {"WGS1",256}, {"WGS2",32} } },
|
{ "Pitcairn", { {"WGS1",256}, {"WGS2",32} } },
|
||||||
{ "Tahiti", { {"WGS1",64}, {"WGS2",32} } },
|
{ "Tahiti", { {"WGS1",64}, {"WGS2",32} } },
|
||||||
{ "default", { {"WGS1",64}, {"WGS2",32} } },
|
{ "default", { {"WGS1",128}, {"WGS2",32} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Intel CPUs
|
{ // Intel CPUs
|
||||||
|
@ -97,6 +103,8 @@ const Database::DatabaseEntry Database::XdotComplexSingle = {
|
||||||
},
|
},
|
||||||
{ // Intel GPUs
|
{ // Intel GPUs
|
||||||
kDeviceTypeGPU, "Intel", {
|
kDeviceTypeGPU, "Intel", {
|
||||||
|
{ "Intel(R) HD Graphics 530", { {"WGS1",256}, {"WGS2",32} } },
|
||||||
|
{ "Intel(R) HD Graphics 5500 BroadWell U-Processor GT2", { {"WGS1",256}, {"WGS2",32} } },
|
||||||
{ "Intel(R) HD Graphics Haswell Ultrabook GT2 Mobile", { {"WGS1",32}, {"WGS2",32} } },
|
{ "Intel(R) HD Graphics Haswell Ultrabook GT2 Mobile", { {"WGS1",32}, {"WGS2",32} } },
|
||||||
{ "Intel(R) HD Graphics Skylake ULT GT2", { {"WGS1",32}, {"WGS2",32} } },
|
{ "Intel(R) HD Graphics Skylake ULT GT2", { {"WGS1",32}, {"WGS2",32} } },
|
||||||
{ "Iris Pro", { {"WGS1",32}, {"WGS2",32} } },
|
{ "Iris Pro", { {"WGS1",32}, {"WGS2",32} } },
|
||||||
|
@ -106,17 +114,20 @@ const Database::DatabaseEntry Database::XdotComplexSingle = {
|
||||||
{ // NVIDIA GPUs
|
{ // NVIDIA GPUs
|
||||||
kDeviceTypeGPU, "NVIDIA", {
|
kDeviceTypeGPU, "NVIDIA", {
|
||||||
{ "GRID K520", { {"WGS1",64}, {"WGS2",32} } },
|
{ "GRID K520", { {"WGS1",64}, {"WGS2",32} } },
|
||||||
|
{ "GeForce GTX 1070", { {"WGS1",128}, {"WGS2",32} } },
|
||||||
{ "GeForce GTX 480", { {"WGS1",512}, {"WGS2",32} } },
|
{ "GeForce GTX 480", { {"WGS1",512}, {"WGS2",32} } },
|
||||||
|
{ "GeForce GTX 670", { {"WGS1",256}, {"WGS2",32} } },
|
||||||
{ "GeForce GTX 680", { {"WGS1",128}, {"WGS2",64} } },
|
{ "GeForce GTX 680", { {"WGS1",128}, {"WGS2",64} } },
|
||||||
|
{ "GeForce GTX 750", { {"WGS1",64}, {"WGS2",32} } },
|
||||||
{ "GeForce GTX 980", { {"WGS1",256}, {"WGS2",64} } },
|
{ "GeForce GTX 980", { {"WGS1",256}, {"WGS2",64} } },
|
||||||
{ "GeForce GTX TITAN X", { {"WGS1",256}, {"WGS2",32} } },
|
{ "GeForce GTX TITAN X", { {"WGS1",256}, {"WGS2",32} } },
|
||||||
{ "Tesla K20m", { {"WGS1",512}, {"WGS2",32} } },
|
{ "Tesla K20m", { {"WGS1",512}, {"WGS2",32} } },
|
||||||
{ "default", { {"WGS1",64}, {"WGS2",32} } },
|
{ "default", { {"WGS1",512}, {"WGS2",64} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Default
|
{ // Default
|
||||||
kDeviceTypeAll, "default", {
|
kDeviceTypeAll, "default", {
|
||||||
{ "default", { {"WGS1",32}, {"WGS2",32} } },
|
{ "default", { {"WGS1",256}, {"WGS2",32} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
}
|
}
|
||||||
|
@ -129,10 +140,10 @@ const Database::DatabaseEntry Database::XdotDouble = {
|
||||||
{ // AMD GPUs
|
{ // AMD GPUs
|
||||||
kDeviceTypeGPU, "AMD", {
|
kDeviceTypeGPU, "AMD", {
|
||||||
{ "AMD Radeon R9 M370X Compute Engine", { {"WGS1",64}, {"WGS2",128} } },
|
{ "AMD Radeon R9 M370X Compute Engine", { {"WGS1",64}, {"WGS2",128} } },
|
||||||
{ "Hawaii", { {"WGS1",256}, {"WGS2",32} } },
|
{ "Oland", { {"WGS1",256}, {"WGS2",32} } },
|
||||||
{ "Pitcairn", { {"WGS1",128}, {"WGS2",32} } },
|
{ "Pitcairn", { {"WGS1",128}, {"WGS2",32} } },
|
||||||
{ "Tahiti", { {"WGS1",256}, {"WGS2",32} } },
|
{ "Tahiti", { {"WGS1",256}, {"WGS2",32} } },
|
||||||
{ "default", { {"WGS1",64}, {"WGS2",32} } },
|
{ "default", { {"WGS1",128}, {"WGS2",32} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Intel CPUs
|
{ // Intel CPUs
|
||||||
|
@ -144,17 +155,20 @@ const Database::DatabaseEntry Database::XdotDouble = {
|
||||||
{ // NVIDIA GPUs
|
{ // NVIDIA GPUs
|
||||||
kDeviceTypeGPU, "NVIDIA", {
|
kDeviceTypeGPU, "NVIDIA", {
|
||||||
{ "GRID K520", { {"WGS1",128}, {"WGS2",32} } },
|
{ "GRID K520", { {"WGS1",128}, {"WGS2",32} } },
|
||||||
|
{ "GeForce GTX 1070", { {"WGS1",128}, {"WGS2",512} } },
|
||||||
{ "GeForce GTX 480", { {"WGS1",512}, {"WGS2",32} } },
|
{ "GeForce GTX 480", { {"WGS1",512}, {"WGS2",32} } },
|
||||||
|
{ "GeForce GTX 670", { {"WGS1",256}, {"WGS2",32} } },
|
||||||
{ "GeForce GTX 680", { {"WGS1",128}, {"WGS2",64} } },
|
{ "GeForce GTX 680", { {"WGS1",128}, {"WGS2",64} } },
|
||||||
|
{ "GeForce GTX 750", { {"WGS1",64}, {"WGS2",256} } },
|
||||||
{ "GeForce GTX 980", { {"WGS1",128}, {"WGS2",32} } },
|
{ "GeForce GTX 980", { {"WGS1",128}, {"WGS2",32} } },
|
||||||
{ "GeForce GTX TITAN X", { {"WGS1",256}, {"WGS2",32} } },
|
{ "GeForce GTX TITAN X", { {"WGS1",256}, {"WGS2",32} } },
|
||||||
{ "Tesla K20m", { {"WGS1",512}, {"WGS2",32} } },
|
{ "Tesla K20m", { {"WGS1",512}, {"WGS2",32} } },
|
||||||
{ "default", { {"WGS1",128}, {"WGS2",32} } },
|
{ "default", { {"WGS1",256}, {"WGS2",64} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Default
|
{ // Default
|
||||||
kDeviceTypeAll, "default", {
|
kDeviceTypeAll, "default", {
|
||||||
{ "default", { {"WGS1",64}, {"WGS2",32} } },
|
{ "default", { {"WGS1",128}, {"WGS2",64} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
}
|
}
|
||||||
|
@ -167,10 +181,10 @@ const Database::DatabaseEntry Database::XdotComplexDouble = {
|
||||||
{ // AMD GPUs
|
{ // AMD GPUs
|
||||||
kDeviceTypeGPU, "AMD", {
|
kDeviceTypeGPU, "AMD", {
|
||||||
{ "AMD Radeon R9 M370X Compute Engine", { {"WGS1",64}, {"WGS2",32} } },
|
{ "AMD Radeon R9 M370X Compute Engine", { {"WGS1",64}, {"WGS2",32} } },
|
||||||
{ "Hawaii", { {"WGS1",256}, {"WGS2",32} } },
|
{ "Oland", { {"WGS1",256}, {"WGS2",32} } },
|
||||||
{ "Pitcairn", { {"WGS1",256}, {"WGS2",32} } },
|
{ "Pitcairn", { {"WGS1",256}, {"WGS2",32} } },
|
||||||
{ "Tahiti", { {"WGS1",256}, {"WGS2",32} } },
|
{ "Tahiti", { {"WGS1",256}, {"WGS2",32} } },
|
||||||
{ "default", { {"WGS1",64}, {"WGS2",32} } },
|
{ "default", { {"WGS1",256}, {"WGS2",32} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Intel CPUs
|
{ // Intel CPUs
|
||||||
|
@ -182,17 +196,20 @@ const Database::DatabaseEntry Database::XdotComplexDouble = {
|
||||||
{ // NVIDIA GPUs
|
{ // NVIDIA GPUs
|
||||||
kDeviceTypeGPU, "NVIDIA", {
|
kDeviceTypeGPU, "NVIDIA", {
|
||||||
{ "GRID K520", { {"WGS1",64}, {"WGS2",32} } },
|
{ "GRID K520", { {"WGS1",64}, {"WGS2",32} } },
|
||||||
|
{ "GeForce GTX 1070", { {"WGS1",128}, {"WGS2",64} } },
|
||||||
{ "GeForce GTX 480", { {"WGS1",512}, {"WGS2",32} } },
|
{ "GeForce GTX 480", { {"WGS1",512}, {"WGS2",32} } },
|
||||||
|
{ "GeForce GTX 670", { {"WGS1",512}, {"WGS2",128} } },
|
||||||
{ "GeForce GTX 680", { {"WGS1",256}, {"WGS2",64} } },
|
{ "GeForce GTX 680", { {"WGS1",256}, {"WGS2",64} } },
|
||||||
|
{ "GeForce GTX 750", { {"WGS1",256}, {"WGS2",32} } },
|
||||||
{ "GeForce GTX 980", { {"WGS1",64}, {"WGS2",32} } },
|
{ "GeForce GTX 980", { {"WGS1",64}, {"WGS2",32} } },
|
||||||
{ "GeForce GTX TITAN X", { {"WGS1",128}, {"WGS2",32} } },
|
{ "GeForce GTX TITAN X", { {"WGS1",128}, {"WGS2",32} } },
|
||||||
{ "Tesla K20m", { {"WGS1",128}, {"WGS2",32} } },
|
{ "Tesla K20m", { {"WGS1",128}, {"WGS2",32} } },
|
||||||
{ "default", { {"WGS1",64}, {"WGS2",32} } },
|
{ "default", { {"WGS1",128}, {"WGS2",64} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Default
|
{ // Default
|
||||||
kDeviceTypeAll, "default", {
|
kDeviceTypeAll, "default", {
|
||||||
{ "default", { {"WGS1",64}, {"WGS2",32} } },
|
{ "default", { {"WGS1",256}, {"WGS2",64} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
}
|
}
|
||||||
|
|
|
@ -18,7 +18,7 @@ const Database::DatabaseEntry Database::XgemmHalf = {
|
||||||
"Xgemm", Precision::kHalf, {
|
"Xgemm", Precision::kHalf, {
|
||||||
{ // Default
|
{ // Default
|
||||||
kDeviceTypeAll, "default", {
|
kDeviceTypeAll, "default", {
|
||||||
{ "default", { {"KWG",16}, {"KWI",2}, {"MDIMA",8}, {"MDIMC",8}, {"MWG",32}, {"NDIMB",8}, {"NDIMC",8}, {"NWG",64}, {"SA",0}, {"SB",0}, {"STRM",0}, {"STRN",0}, {"VWM",1}, {"VWN",1} } },
|
{ "default", { {"KWG",16}, {"KWI",2}, {"MDIMA",8}, {"MDIMC",8}, {"MWG",32}, {"NDIMB",8}, {"NDIMC",8}, {"NWG",16}, {"SA",0}, {"SB",0}, {"STRM",0}, {"STRN",0}, {"VWM",1}, {"VWN",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
}
|
}
|
||||||
|
@ -32,6 +32,7 @@ const Database::DatabaseEntry Database::XgemmSingle = {
|
||||||
kDeviceTypeGPU, "AMD", {
|
kDeviceTypeGPU, "AMD", {
|
||||||
{ "AMD Radeon R9 M370X Compute Engine", { {"KWG",32}, {"KWI",2}, {"MDIMA",16}, {"MDIMC",16}, {"MWG",64}, {"NDIMB",8}, {"NDIMC",16}, {"NWG",128}, {"SA",0}, {"SB",0}, {"STRM",0}, {"STRN",0}, {"VWM",2}, {"VWN",8} } },
|
{ "AMD Radeon R9 M370X Compute Engine", { {"KWG",32}, {"KWI",2}, {"MDIMA",16}, {"MDIMC",16}, {"MWG",64}, {"NDIMB",8}, {"NDIMC",16}, {"NWG",128}, {"SA",0}, {"SB",0}, {"STRM",0}, {"STRN",0}, {"VWM",2}, {"VWN",8} } },
|
||||||
{ "Hawaii", { {"KWG",16}, {"KWI",2}, {"MDIMA",16}, {"MDIMC",32}, {"MWG",128}, {"NDIMB",32}, {"NDIMC",8}, {"NWG",64}, {"SA",1}, {"SB",1}, {"STRM",1}, {"STRN",1}, {"VWM",4}, {"VWN",2} } },
|
{ "Hawaii", { {"KWG",16}, {"KWI",2}, {"MDIMA",16}, {"MDIMC",32}, {"MWG",128}, {"NDIMB",32}, {"NDIMC",8}, {"NWG",64}, {"SA",1}, {"SB",1}, {"STRM",1}, {"STRN",1}, {"VWM",4}, {"VWN",2} } },
|
||||||
|
{ "Oland", { {"KWG",16}, {"KWI",2}, {"MDIMA",32}, {"MDIMC",16}, {"MWG",64}, {"NDIMB",32}, {"NDIMC",16}, {"NWG",128}, {"SA",1}, {"SB",1}, {"STRM",1}, {"STRN",0}, {"VWM",2}, {"VWN",4} } },
|
||||||
{ "Pitcairn", { {"KWG",16}, {"KWI",2}, {"MDIMA",16}, {"MDIMC",8}, {"MWG",32}, {"NDIMB",16}, {"NDIMC",16}, {"NWG",128}, {"SA",0}, {"SB",0}, {"STRM",1}, {"STRN",0}, {"VWM",1}, {"VWN",1} } },
|
{ "Pitcairn", { {"KWG",16}, {"KWI",2}, {"MDIMA",16}, {"MDIMC",8}, {"MWG",32}, {"NDIMB",16}, {"NDIMC",16}, {"NWG",128}, {"SA",0}, {"SB",0}, {"STRM",1}, {"STRN",0}, {"VWM",1}, {"VWN",1} } },
|
||||||
{ "Tahiti", { {"KWG",32}, {"KWI",2}, {"MDIMA",16}, {"MDIMC",32}, {"MWG",128}, {"NDIMB",16}, {"NDIMC",8}, {"NWG",64}, {"SA",0}, {"SB",0}, {"STRM",0}, {"STRN",0}, {"VWM",4}, {"VWN",1} } },
|
{ "Tahiti", { {"KWG",32}, {"KWI",2}, {"MDIMA",16}, {"MDIMC",32}, {"MWG",128}, {"NDIMB",16}, {"NDIMC",8}, {"NWG",64}, {"SA",0}, {"SB",0}, {"STRM",0}, {"STRN",0}, {"VWM",4}, {"VWN",1} } },
|
||||||
{ "default", { {"KWG",16}, {"KWI",2}, {"MDIMA",16}, {"MDIMC",8}, {"MWG",32}, {"NDIMB",8}, {"NDIMC",8}, {"NWG",64}, {"SA",0}, {"SB",0}, {"STRM",0}, {"STRN",0}, {"VWM",1}, {"VWN",1} } },
|
{ "default", { {"KWG",16}, {"KWI",2}, {"MDIMA",16}, {"MDIMC",8}, {"MWG",32}, {"NDIMB",8}, {"NDIMC",8}, {"NWG",64}, {"SA",0}, {"SB",0}, {"STRM",0}, {"STRN",0}, {"VWM",1}, {"VWN",1} } },
|
||||||
|
@ -53,11 +54,13 @@ const Database::DatabaseEntry Database::XgemmSingle = {
|
||||||
},
|
},
|
||||||
{ // Intel GPUs
|
{ // Intel GPUs
|
||||||
kDeviceTypeGPU, "Intel", {
|
kDeviceTypeGPU, "Intel", {
|
||||||
|
{ "Intel(R) HD Graphics 530", { {"KWG",32}, {"KWI",2}, {"MDIMA",8}, {"MDIMC",8}, {"MWG",128}, {"NDIMB",32}, {"NDIMC",16}, {"NWG",64}, {"SA",0}, {"SB",0}, {"STRM",1}, {"STRN",0}, {"VWM",4}, {"VWN",2} } },
|
||||||
|
{ "Intel(R) HD Graphics 5500 BroadWell U-Processor GT2", { {"KWG",32}, {"KWI",8}, {"MDIMA",8}, {"MDIMC",8}, {"MWG",64}, {"NDIMB",32}, {"NDIMC",16}, {"NWG",64}, {"SA",1}, {"SB",1}, {"STRM",1}, {"STRN",1}, {"VWM",4}, {"VWN",2} } },
|
||||||
{ "Intel(R) HD Graphics Haswell Ultrabook GT2 Mobile", { {"KWG",16}, {"KWI",2}, {"MDIMA",16}, {"MDIMC",8}, {"MWG",32}, {"NDIMB",8}, {"NDIMC",16}, {"NWG",128}, {"SA",1}, {"SB",1}, {"STRM",1}, {"STRN",1}, {"VWM",2}, {"VWN",4} } },
|
{ "Intel(R) HD Graphics Haswell Ultrabook GT2 Mobile", { {"KWG",16}, {"KWI",2}, {"MDIMA",16}, {"MDIMC",8}, {"MWG",32}, {"NDIMB",8}, {"NDIMC",16}, {"NWG",128}, {"SA",1}, {"SB",1}, {"STRM",1}, {"STRN",1}, {"VWM",2}, {"VWN",4} } },
|
||||||
{ "Intel(R) HD Graphics Skylake ULT GT2", { {"KWG",32}, {"KWI",8}, {"MDIMA",16}, {"MDIMC",16}, {"MWG",64}, {"NDIMB",16}, {"NDIMC",16}, {"NWG",128}, {"SA",0}, {"SB",0}, {"STRM",0}, {"STRN",1}, {"VWM",1}, {"VWN",8} } },
|
{ "Intel(R) HD Graphics Skylake ULT GT2", { {"KWG",32}, {"KWI",8}, {"MDIMA",16}, {"MDIMC",16}, {"MWG",64}, {"NDIMB",16}, {"NDIMC",16}, {"NWG",128}, {"SA",0}, {"SB",0}, {"STRM",0}, {"STRN",1}, {"VWM",1}, {"VWN",8} } },
|
||||||
{ "Iris", { {"KWG",16}, {"KWI",8}, {"MDIMA",16}, {"MDIMC",8}, {"MWG",128}, {"NDIMB",32}, {"NDIMC",16}, {"NWG",64}, {"SA",1}, {"SB",1}, {"STRM",1}, {"STRN",1}, {"VWM",4}, {"VWN",1} } },
|
{ "Iris", { {"KWG",16}, {"KWI",8}, {"MDIMA",16}, {"MDIMC",8}, {"MWG",128}, {"NDIMB",32}, {"NDIMC",16}, {"NWG",64}, {"SA",1}, {"SB",1}, {"STRM",1}, {"STRN",1}, {"VWM",4}, {"VWN",1} } },
|
||||||
{ "Iris Pro", { {"KWG",32}, {"KWI",8}, {"MDIMA",16}, {"MDIMC",8}, {"MWG",64}, {"NDIMB",8}, {"NDIMC",8}, {"NWG",64}, {"SA",1}, {"SB",0}, {"STRM",1}, {"STRN",0}, {"VWM",4}, {"VWN",4} } },
|
{ "Iris Pro", { {"KWG",32}, {"KWI",8}, {"MDIMA",16}, {"MDIMC",8}, {"MWG",64}, {"NDIMB",8}, {"NDIMC",8}, {"NWG",64}, {"SA",1}, {"SB",0}, {"STRM",1}, {"STRN",0}, {"VWM",4}, {"VWN",4} } },
|
||||||
{ "default", { {"KWG",16}, {"KWI",2}, {"MDIMA",16}, {"MDIMC",8}, {"MWG",32}, {"NDIMB",8}, {"NDIMC",8}, {"NWG",64}, {"SA",0}, {"SB",0}, {"STRM",0}, {"STRN",0}, {"VWM",1}, {"VWN",1} } },
|
{ "default", { {"KWG",16}, {"KWI",2}, {"MDIMA",8}, {"MDIMC",8}, {"MWG",32}, {"NDIMB",8}, {"NDIMC",8}, {"NWG",64}, {"SA",0}, {"SB",0}, {"STRM",0}, {"STRN",0}, {"VWM",1}, {"VWN",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Intel accelerators
|
{ // Intel accelerators
|
||||||
|
@ -69,20 +72,23 @@ const Database::DatabaseEntry Database::XgemmSingle = {
|
||||||
{ // NVIDIA GPUs
|
{ // NVIDIA GPUs
|
||||||
kDeviceTypeGPU, "NVIDIA", {
|
kDeviceTypeGPU, "NVIDIA", {
|
||||||
{ "GRID K520", { {"KWG",16}, {"KWI",2}, {"MDIMA",16}, {"MDIMC",8}, {"MWG",32}, {"NDIMB",8}, {"NDIMC",16}, {"NWG",64}, {"SA",1}, {"SB",1}, {"STRM",1}, {"STRN",1}, {"VWM",2}, {"VWN",4} } },
|
{ "GRID K520", { {"KWG",16}, {"KWI",2}, {"MDIMA",16}, {"MDIMC",8}, {"MWG",32}, {"NDIMB",8}, {"NDIMC",16}, {"NWG",64}, {"SA",1}, {"SB",1}, {"STRM",1}, {"STRN",1}, {"VWM",2}, {"VWN",4} } },
|
||||||
|
{ "GeForce GTX 1070", { {"KWG",16}, {"KWI",2}, {"MDIMA",32}, {"MDIMC",16}, {"MWG",128}, {"NDIMB",32}, {"NDIMC",8}, {"NWG",128}, {"SA",1}, {"SB",1}, {"STRM",1}, {"STRN",0}, {"VWM",4}, {"VWN",1} } },
|
||||||
{ "GeForce GTX 480", { {"KWG",16}, {"KWI",2}, {"MDIMA",16}, {"MDIMC",8}, {"MWG",64}, {"NDIMB",32}, {"NDIMC",16}, {"NWG",64}, {"SA",1}, {"SB",1}, {"STRM",1}, {"STRN",1}, {"VWM",2}, {"VWN",2} } },
|
{ "GeForce GTX 480", { {"KWG",16}, {"KWI",2}, {"MDIMA",16}, {"MDIMC",8}, {"MWG",64}, {"NDIMB",32}, {"NDIMC",16}, {"NWG",64}, {"SA",1}, {"SB",1}, {"STRM",1}, {"STRN",1}, {"VWM",2}, {"VWN",2} } },
|
||||||
|
{ "GeForce GTX 670", { {"KWG",16}, {"KWI",2}, {"MDIMA",8}, {"MDIMC",8}, {"MWG",64}, {"NDIMB",16}, {"NDIMC",16}, {"NWG",64}, {"SA",1}, {"SB",1}, {"STRM",1}, {"STRN",0}, {"VWM",2}, {"VWN",4} } },
|
||||||
{ "GeForce GTX 680", { {"KWG",32}, {"KWI",8}, {"MDIMA",8}, {"MDIMC",16}, {"MWG",64}, {"NDIMB",32}, {"NDIMC",16}, {"NWG",128}, {"SA",1}, {"SB",1}, {"STRM",0}, {"STRN",0}, {"VWM",4}, {"VWN",2} } },
|
{ "GeForce GTX 680", { {"KWG",32}, {"KWI",8}, {"MDIMA",8}, {"MDIMC",16}, {"MWG",64}, {"NDIMB",32}, {"NDIMC",16}, {"NWG",128}, {"SA",1}, {"SB",1}, {"STRM",0}, {"STRN",0}, {"VWM",4}, {"VWN",2} } },
|
||||||
|
{ "GeForce GTX 750", { {"KWG",16}, {"KWI",2}, {"MDIMA",16}, {"MDIMC",16}, {"MWG",64}, {"NDIMB",32}, {"NDIMC",8}, {"NWG",128}, {"SA",1}, {"SB",1}, {"STRM",1}, {"STRN",1}, {"VWM",1}, {"VWN",2} } },
|
||||||
{ "GeForce GTX 750 Ti", { {"KWG",16}, {"KWI",2}, {"MDIMA",32}, {"MDIMC",16}, {"MWG",128}, {"NDIMB",16}, {"NDIMC",8}, {"NWG",128}, {"SA",1}, {"SB",1}, {"STRM",1}, {"STRN",1}, {"VWM",4}, {"VWN",4} } },
|
{ "GeForce GTX 750 Ti", { {"KWG",16}, {"KWI",2}, {"MDIMA",32}, {"MDIMC",16}, {"MWG",128}, {"NDIMB",16}, {"NDIMC",8}, {"NWG",128}, {"SA",1}, {"SB",1}, {"STRM",1}, {"STRN",1}, {"VWM",4}, {"VWN",4} } },
|
||||||
{ "GeForce GTX 980", { {"KWG",16}, {"KWI",2}, {"MDIMA",16}, {"MDIMC",16}, {"MWG",64}, {"NDIMB",16}, {"NDIMC",8}, {"NWG",128}, {"SA",1}, {"SB",1}, {"STRM",1}, {"STRN",0}, {"VWM",4}, {"VWN",8} } },
|
{ "GeForce GTX 980", { {"KWG",16}, {"KWI",2}, {"MDIMA",16}, {"MDIMC",16}, {"MWG",64}, {"NDIMB",16}, {"NDIMC",8}, {"NWG",128}, {"SA",1}, {"SB",1}, {"STRM",1}, {"STRN",0}, {"VWM",4}, {"VWN",8} } },
|
||||||
{ "GeForce GTX TITAN", { {"KWG",16}, {"KWI",8}, {"MDIMA",32}, {"MDIMC",16}, {"MWG",64}, {"NDIMB",8}, {"NDIMC",8}, {"NWG",64}, {"SA",1}, {"SB",1}, {"STRM",1}, {"STRN",0}, {"VWM",2}, {"VWN",2} } },
|
{ "GeForce GTX TITAN", { {"KWG",16}, {"KWI",8}, {"MDIMA",32}, {"MDIMC",16}, {"MWG",64}, {"NDIMB",8}, {"NDIMC",8}, {"NWG",64}, {"SA",1}, {"SB",1}, {"STRM",1}, {"STRN",0}, {"VWM",2}, {"VWN",2} } },
|
||||||
{ "GeForce GTX TITAN X", { {"KWG",16}, {"KWI",2}, {"MDIMA",8}, {"MDIMC",16}, {"MWG",128}, {"NDIMB",8}, {"NDIMC",8}, {"NWG",128}, {"SA",1}, {"SB",1}, {"STRM",1}, {"STRN",1}, {"VWM",4}, {"VWN",8} } },
|
{ "GeForce GTX TITAN X", { {"KWG",16}, {"KWI",2}, {"MDIMA",8}, {"MDIMC",16}, {"MWG",128}, {"NDIMB",8}, {"NDIMC",8}, {"NWG",128}, {"SA",1}, {"SB",1}, {"STRM",1}, {"STRN",1}, {"VWM",4}, {"VWN",8} } },
|
||||||
{ "Tesla K20m", { {"KWG",16}, {"KWI",2}, {"MDIMA",32}, {"MDIMC",16}, {"MWG",64}, {"NDIMB",16}, {"NDIMC",8}, {"NWG",64}, {"SA",1}, {"SB",1}, {"STRM",1}, {"STRN",0}, {"VWM",2}, {"VWN",4} } },
|
{ "Tesla K20m", { {"KWG",16}, {"KWI",2}, {"MDIMA",32}, {"MDIMC",16}, {"MWG",64}, {"NDIMB",16}, {"NDIMC",8}, {"NWG",64}, {"SA",1}, {"SB",1}, {"STRM",1}, {"STRN",0}, {"VWM",2}, {"VWN",4} } },
|
||||||
{ "Tesla K40m", { {"KWG",16}, {"KWI",8}, {"MDIMA",16}, {"MDIMC",8}, {"MWG",64}, {"NDIMB",16}, {"NDIMC",16}, {"NWG",128}, {"SA",1}, {"SB",1}, {"STRM",1}, {"STRN",0}, {"VWM",2}, {"VWN",4} } },
|
{ "Tesla K40m", { {"KWG",16}, {"KWI",8}, {"MDIMA",16}, {"MDIMC",8}, {"MWG",64}, {"NDIMB",16}, {"NDIMC",16}, {"NWG",128}, {"SA",1}, {"SB",1}, {"STRM",1}, {"STRN",0}, {"VWM",2}, {"VWN",4} } },
|
||||||
{ "default", { {"KWG",16}, {"KWI",2}, {"MDIMA",8}, {"MDIMC",8}, {"MWG",32}, {"NDIMB",8}, {"NDIMC",8}, {"NWG",64}, {"SA",1}, {"SB",1}, {"STRM",0}, {"STRN",0}, {"VWM",2}, {"VWN",2} } },
|
{ "default", { {"KWG",16}, {"KWI",2}, {"MDIMA",8}, {"MDIMC",8}, {"MWG",32}, {"NDIMB",8}, {"NDIMC",8}, {"NWG",64}, {"SA",1}, {"SB",1}, {"STRM",0}, {"STRN",0}, {"VWM",1}, {"VWN",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Default
|
{ // Default
|
||||||
kDeviceTypeAll, "default", {
|
kDeviceTypeAll, "default", {
|
||||||
{ "default", { {"KWG",16}, {"KWI",2}, {"MDIMA",8}, {"MDIMC",8}, {"MWG",32}, {"NDIMB",8}, {"NDIMC",8}, {"NWG",64}, {"SA",0}, {"SB",0}, {"STRM",0}, {"STRN",0}, {"VWM",1}, {"VWN",1} } },
|
{ "default", { {"KWG",16}, {"KWI",2}, {"MDIMA",8}, {"MDIMC",8}, {"MWG",32}, {"NDIMB",8}, {"NDIMC",8}, {"NWG",16}, {"SA",0}, {"SB",0}, {"STRM",0}, {"STRN",0}, {"VWM",1}, {"VWN",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
}
|
}
|
||||||
|
@ -96,6 +102,7 @@ const Database::DatabaseEntry Database::XgemmComplexSingle = {
|
||||||
kDeviceTypeGPU, "AMD", {
|
kDeviceTypeGPU, "AMD", {
|
||||||
{ "AMD Radeon R9 M370X Compute Engine", { {"KWG",32}, {"KWI",2}, {"MDIMA",32}, {"MDIMC",32}, {"MWG",64}, {"NDIMB",8}, {"NDIMC",8}, {"NWG",64}, {"SA",0}, {"SB",0}, {"STRM",1}, {"STRN",1}, {"VWM",2}, {"VWN",8} } },
|
{ "AMD Radeon R9 M370X Compute Engine", { {"KWG",32}, {"KWI",2}, {"MDIMA",32}, {"MDIMC",32}, {"MWG",64}, {"NDIMB",8}, {"NDIMC",8}, {"NWG",64}, {"SA",0}, {"SB",0}, {"STRM",1}, {"STRN",1}, {"VWM",2}, {"VWN",8} } },
|
||||||
{ "Hawaii", { {"KWG",32}, {"KWI",2}, {"MDIMA",32}, {"MDIMC",8}, {"MWG",32}, {"NDIMB",8}, {"NDIMC",16}, {"NWG",32}, {"SA",1}, {"SB",0}, {"STRM",1}, {"STRN",0}, {"VWM",1}, {"VWN",1} } },
|
{ "Hawaii", { {"KWG",32}, {"KWI",2}, {"MDIMA",32}, {"MDIMC",8}, {"MWG",32}, {"NDIMB",8}, {"NDIMC",16}, {"NWG",32}, {"SA",1}, {"SB",0}, {"STRM",1}, {"STRN",0}, {"VWM",1}, {"VWN",1} } },
|
||||||
|
{ "Oland", { {"KWG",32}, {"KWI",2}, {"MDIMA",16}, {"MDIMC",8}, {"MWG",32}, {"NDIMB",32}, {"NDIMC",32}, {"NWG",128}, {"SA",1}, {"SB",0}, {"STRM",0}, {"STRN",1}, {"VWM",2}, {"VWN",4} } },
|
||||||
{ "Pitcairn", { {"KWG",16}, {"KWI",2}, {"MDIMA",8}, {"MDIMC",8}, {"MWG",32}, {"NDIMB",8}, {"NDIMC",8}, {"NWG",32}, {"SA",0}, {"SB",1}, {"STRM",1}, {"STRN",1}, {"VWM",4}, {"VWN",2} } },
|
{ "Pitcairn", { {"KWG",16}, {"KWI",2}, {"MDIMA",8}, {"MDIMC",8}, {"MWG",32}, {"NDIMB",8}, {"NDIMC",8}, {"NWG",32}, {"SA",0}, {"SB",1}, {"STRM",1}, {"STRN",1}, {"VWM",4}, {"VWN",2} } },
|
||||||
{ "Tahiti", { {"KWG",16}, {"KWI",2}, {"MDIMA",8}, {"MDIMC",8}, {"MWG",32}, {"NDIMB",8}, {"NDIMC",16}, {"NWG",32}, {"SA",1}, {"SB",0}, {"STRM",0}, {"STRN",1}, {"VWM",2}, {"VWN",1} } },
|
{ "Tahiti", { {"KWG",16}, {"KWI",2}, {"MDIMA",8}, {"MDIMC",8}, {"MWG",32}, {"NDIMB",8}, {"NDIMC",16}, {"NWG",32}, {"SA",1}, {"SB",0}, {"STRM",0}, {"STRN",1}, {"VWM",2}, {"VWN",1} } },
|
||||||
{ "default", { {"KWG",16}, {"KWI",2}, {"MDIMA",8}, {"MDIMC",8}, {"MWG",32}, {"NDIMB",8}, {"NDIMC",8}, {"NWG",32}, {"SA",0}, {"SB",0}, {"STRM",0}, {"STRN",0}, {"VWM",1}, {"VWN",1} } },
|
{ "default", { {"KWG",16}, {"KWI",2}, {"MDIMA",8}, {"MDIMC",8}, {"MWG",32}, {"NDIMB",8}, {"NDIMC",8}, {"NWG",32}, {"SA",0}, {"SB",0}, {"STRM",0}, {"STRN",0}, {"VWM",1}, {"VWN",1} } },
|
||||||
|
@ -117,11 +124,13 @@ const Database::DatabaseEntry Database::XgemmComplexSingle = {
|
||||||
},
|
},
|
||||||
{ // Intel GPUs
|
{ // Intel GPUs
|
||||||
kDeviceTypeGPU, "Intel", {
|
kDeviceTypeGPU, "Intel", {
|
||||||
|
{ "Intel(R) HD Graphics 530", { {"KWG",16}, {"KWI",8}, {"MDIMA",8}, {"MDIMC",16}, {"MWG",64}, {"NDIMB",32}, {"NDIMC",8}, {"NWG",32}, {"SA",0}, {"SB",0}, {"STRM",0}, {"STRN",0}, {"VWM",2}, {"VWN",1} } },
|
||||||
|
{ "Intel(R) HD Graphics 5500 BroadWell U-Processor GT2", { {"KWG",16}, {"KWI",8}, {"MDIMA",8}, {"MDIMC",8}, {"MWG",32}, {"NDIMB",16}, {"NDIMC",16}, {"NWG",64}, {"SA",1}, {"SB",0}, {"STRM",0}, {"STRN",0}, {"VWM",4}, {"VWN",4} } },
|
||||||
{ "Intel(R) HD Graphics Haswell Ultrabook GT2 Mobile", { {"KWG",32}, {"KWI",8}, {"MDIMA",16}, {"MDIMC",16}, {"MWG",64}, {"NDIMB",16}, {"NDIMC",16}, {"NWG",64}, {"SA",1}, {"SB",1}, {"STRM",1}, {"STRN",1}, {"VWM",2}, {"VWN",1} } },
|
{ "Intel(R) HD Graphics Haswell Ultrabook GT2 Mobile", { {"KWG",32}, {"KWI",8}, {"MDIMA",16}, {"MDIMC",16}, {"MWG",64}, {"NDIMB",16}, {"NDIMC",16}, {"NWG",64}, {"SA",1}, {"SB",1}, {"STRM",1}, {"STRN",1}, {"VWM",2}, {"VWN",1} } },
|
||||||
{ "Intel(R) HD Graphics Skylake ULT GT2", { {"KWG",32}, {"KWI",8}, {"MDIMA",8}, {"MDIMC",8}, {"MWG",32}, {"NDIMB",32}, {"NDIMC",16}, {"NWG",32}, {"SA",1}, {"SB",0}, {"STRM",0}, {"STRN",1}, {"VWM",4}, {"VWN",1} } },
|
{ "Intel(R) HD Graphics Skylake ULT GT2", { {"KWG",32}, {"KWI",8}, {"MDIMA",8}, {"MDIMC",8}, {"MWG",32}, {"NDIMB",32}, {"NDIMC",16}, {"NWG",32}, {"SA",1}, {"SB",0}, {"STRM",0}, {"STRN",1}, {"VWM",4}, {"VWN",1} } },
|
||||||
{ "Iris", { {"KWG",32}, {"KWI",8}, {"MDIMA",32}, {"MDIMC",16}, {"MWG",64}, {"NDIMB",8}, {"NDIMC",16}, {"NWG",64}, {"SA",1}, {"SB",0}, {"STRM",1}, {"STRN",0}, {"VWM",1}, {"VWN",1} } },
|
{ "Iris", { {"KWG",32}, {"KWI",8}, {"MDIMA",32}, {"MDIMC",16}, {"MWG",64}, {"NDIMB",8}, {"NDIMC",16}, {"NWG",64}, {"SA",1}, {"SB",0}, {"STRM",1}, {"STRN",0}, {"VWM",1}, {"VWN",1} } },
|
||||||
{ "Iris Pro", { {"KWG",16}, {"KWI",2}, {"MDIMA",8}, {"MDIMC",8}, {"MWG",32}, {"NDIMB",32}, {"NDIMC",8}, {"NWG",32}, {"SA",1}, {"SB",1}, {"STRM",1}, {"STRN",1}, {"VWM",1}, {"VWN",1} } },
|
{ "Iris Pro", { {"KWG",16}, {"KWI",2}, {"MDIMA",8}, {"MDIMC",8}, {"MWG",32}, {"NDIMB",32}, {"NDIMC",8}, {"NWG",32}, {"SA",1}, {"SB",1}, {"STRM",1}, {"STRN",1}, {"VWM",1}, {"VWN",1} } },
|
||||||
{ "default", { {"KWG",16}, {"KWI",2}, {"MDIMA",8}, {"MDIMC",8}, {"MWG",32}, {"NDIMB",8}, {"NDIMC",8}, {"NWG",32}, {"SA",1}, {"SB",0}, {"STRM",0}, {"STRN",0}, {"VWM",1}, {"VWN",1} } },
|
{ "default", { {"KWG",16}, {"KWI",2}, {"MDIMA",8}, {"MDIMC",8}, {"MWG",32}, {"NDIMB",8}, {"NDIMC",8}, {"NWG",32}, {"SA",0}, {"SB",0}, {"STRM",0}, {"STRN",0}, {"VWM",1}, {"VWN",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Intel accelerators
|
{ // Intel accelerators
|
||||||
|
@ -133,8 +142,11 @@ const Database::DatabaseEntry Database::XgemmComplexSingle = {
|
||||||
{ // NVIDIA GPUs
|
{ // NVIDIA GPUs
|
||||||
kDeviceTypeGPU, "NVIDIA", {
|
kDeviceTypeGPU, "NVIDIA", {
|
||||||
{ "GRID K520", { {"KWG",16}, {"KWI",8}, {"MDIMA",32}, {"MDIMC",32}, {"MWG",64}, {"NDIMB",32}, {"NDIMC",16}, {"NWG",128}, {"SA",1}, {"SB",0}, {"STRM",1}, {"STRN",0}, {"VWM",1}, {"VWN",4} } },
|
{ "GRID K520", { {"KWG",16}, {"KWI",8}, {"MDIMA",32}, {"MDIMC",32}, {"MWG",64}, {"NDIMB",32}, {"NDIMC",16}, {"NWG",128}, {"SA",1}, {"SB",0}, {"STRM",1}, {"STRN",0}, {"VWM",1}, {"VWN",4} } },
|
||||||
|
{ "GeForce GTX 1070", { {"KWG",16}, {"KWI",2}, {"MDIMA",16}, {"MDIMC",16}, {"MWG",128}, {"NDIMB",16}, {"NDIMC",16}, {"NWG",64}, {"SA",1}, {"SB",1}, {"STRM",1}, {"STRN",1}, {"VWM",2}, {"VWN",4} } },
|
||||||
{ "GeForce GTX 480", { {"KWG",16}, {"KWI",2}, {"MDIMA",16}, {"MDIMC",16}, {"MWG",32}, {"NDIMB",32}, {"NDIMC",16}, {"NWG",128}, {"SA",0}, {"SB",1}, {"STRM",1}, {"STRN",1}, {"VWM",2}, {"VWN",2} } },
|
{ "GeForce GTX 480", { {"KWG",16}, {"KWI",2}, {"MDIMA",16}, {"MDIMC",16}, {"MWG",32}, {"NDIMB",32}, {"NDIMC",16}, {"NWG",128}, {"SA",0}, {"SB",1}, {"STRM",1}, {"STRN",1}, {"VWM",2}, {"VWN",2} } },
|
||||||
|
{ "GeForce GTX 670", { {"KWG",16}, {"KWI",2}, {"MDIMA",32}, {"MDIMC",32}, {"MWG",64}, {"NDIMB",32}, {"NDIMC",8}, {"NWG",32}, {"SA",1}, {"SB",1}, {"STRM",1}, {"STRN",1}, {"VWM",1}, {"VWN",1} } },
|
||||||
{ "GeForce GTX 680", { {"KWG",16}, {"KWI",2}, {"MDIMA",32}, {"MDIMC",16}, {"MWG",64}, {"NDIMB",32}, {"NDIMC",32}, {"NWG",128}, {"SA",1}, {"SB",0}, {"STRM",0}, {"STRN",0}, {"VWM",2}, {"VWN",2} } },
|
{ "GeForce GTX 680", { {"KWG",16}, {"KWI",2}, {"MDIMA",32}, {"MDIMC",16}, {"MWG",64}, {"NDIMB",32}, {"NDIMC",32}, {"NWG",128}, {"SA",1}, {"SB",0}, {"STRM",0}, {"STRN",0}, {"VWM",2}, {"VWN",2} } },
|
||||||
|
{ "GeForce GTX 750", { {"KWG",16}, {"KWI",8}, {"MDIMA",16}, {"MDIMC",16}, {"MWG",64}, {"NDIMB",16}, {"NDIMC",16}, {"NWG",64}, {"SA",1}, {"SB",1}, {"STRM",1}, {"STRN",0}, {"VWM",2}, {"VWN",2} } },
|
||||||
{ "GeForce GTX 750 Ti", { {"KWG",16}, {"KWI",2}, {"MDIMA",32}, {"MDIMC",8}, {"MWG",128}, {"NDIMB",16}, {"NDIMC",32}, {"NWG",128}, {"SA",1}, {"SB",1}, {"STRM",1}, {"STRN",0}, {"VWM",1}, {"VWN",4} } },
|
{ "GeForce GTX 750 Ti", { {"KWG",16}, {"KWI",2}, {"MDIMA",32}, {"MDIMC",8}, {"MWG",128}, {"NDIMB",16}, {"NDIMC",32}, {"NWG",128}, {"SA",1}, {"SB",1}, {"STRM",1}, {"STRN",0}, {"VWM",1}, {"VWN",4} } },
|
||||||
{ "GeForce GTX 980", { {"KWG",32}, {"KWI",8}, {"MDIMA",32}, {"MDIMC",32}, {"MWG",64}, {"NDIMB",16}, {"NDIMC",16}, {"NWG",64}, {"SA",1}, {"SB",1}, {"STRM",1}, {"STRN",0}, {"VWM",2}, {"VWN",1} } },
|
{ "GeForce GTX 980", { {"KWG",32}, {"KWI",8}, {"MDIMA",32}, {"MDIMC",32}, {"MWG",64}, {"NDIMB",16}, {"NDIMC",16}, {"NWG",64}, {"SA",1}, {"SB",1}, {"STRM",1}, {"STRN",0}, {"VWM",2}, {"VWN",1} } },
|
||||||
{ "GeForce GTX TITAN", { {"KWG",16}, {"KWI",8}, {"MDIMA",16}, {"MDIMC",16}, {"MWG",64}, {"NDIMB",32}, {"NDIMC",16}, {"NWG",64}, {"SA",1}, {"SB",1}, {"STRM",1}, {"STRN",0}, {"VWM",1}, {"VWN",1} } },
|
{ "GeForce GTX TITAN", { {"KWG",16}, {"KWI",8}, {"MDIMA",16}, {"MDIMC",16}, {"MWG",64}, {"NDIMB",32}, {"NDIMC",16}, {"NWG",64}, {"SA",1}, {"SB",1}, {"STRM",1}, {"STRN",0}, {"VWM",1}, {"VWN",1} } },
|
||||||
|
@ -158,11 +170,12 @@ const Database::DatabaseEntry Database::XgemmDouble = {
|
||||||
"Xgemm", Precision::kDouble, {
|
"Xgemm", Precision::kDouble, {
|
||||||
{ // AMD GPUs
|
{ // AMD GPUs
|
||||||
kDeviceTypeGPU, "AMD", {
|
kDeviceTypeGPU, "AMD", {
|
||||||
{ "AMD Radeon R9 M370X Compute Engine", { {"KWG",32}, {"KWI",2}, {"MDIMA",32}, {"MDIMC",32}, {"MWG",64}, {"NDIMB",8}, {"NDIMC",8}, {"NWG",64}, {"SA",0}, {"SB",0}, {"STRM",1}, {"STRN",1}, {"VWM",2}, {"VWN",8} } },
|
{ "AMD Radeon R9 M370X Compute Engine", { {"KWG",32}, {"KWI",2}, {"MDIMA",16}, {"MDIMC",16}, {"MWG",64}, {"NDIMB",8}, {"NDIMC",8}, {"NWG",32}, {"SA",0}, {"SB",0}, {"STRM",0}, {"STRN",0}, {"VWM",4}, {"VWN",4} } },
|
||||||
{ "Hawaii", { {"KWG",16}, {"KWI",8}, {"MDIMA",32}, {"MDIMC",8}, {"MWG",128}, {"NDIMB",8}, {"NDIMC",8}, {"NWG",32}, {"SA",0}, {"SB",1}, {"STRM",0}, {"STRN",0}, {"VWM",1}, {"VWN",4} } },
|
{ "Hawaii", { {"KWG",16}, {"KWI",8}, {"MDIMA",32}, {"MDIMC",8}, {"MWG",128}, {"NDIMB",8}, {"NDIMC",8}, {"NWG",32}, {"SA",0}, {"SB",1}, {"STRM",0}, {"STRN",0}, {"VWM",1}, {"VWN",4} } },
|
||||||
|
{ "Oland", { {"KWG",16}, {"KWI",2}, {"MDIMA",8}, {"MDIMC",16}, {"MWG",64}, {"NDIMB",16}, {"NDIMC",8}, {"NWG",16}, {"SA",0}, {"SB",0}, {"STRM",1}, {"STRN",1}, {"VWM",1}, {"VWN",1} } },
|
||||||
{ "Pitcairn", { {"KWG",32}, {"KWI",2}, {"MDIMA",32}, {"MDIMC",16}, {"MWG",64}, {"NDIMB",8}, {"NDIMC",16}, {"NWG",32}, {"SA",0}, {"SB",0}, {"STRM",0}, {"STRN",0}, {"VWM",1}, {"VWN",2} } },
|
{ "Pitcairn", { {"KWG",32}, {"KWI",2}, {"MDIMA",32}, {"MDIMC",16}, {"MWG",64}, {"NDIMB",8}, {"NDIMC",16}, {"NWG",32}, {"SA",0}, {"SB",0}, {"STRM",0}, {"STRN",0}, {"VWM",1}, {"VWN",2} } },
|
||||||
{ "Tahiti", { {"KWG",32}, {"KWI",2}, {"MDIMA",16}, {"MDIMC",8}, {"MWG",16}, {"NDIMB",8}, {"NDIMC",8}, {"NWG",32}, {"SA",0}, {"SB",0}, {"STRM",0}, {"STRN",1}, {"VWM",1}, {"VWN",4} } },
|
{ "Tahiti", { {"KWG",32}, {"KWI",2}, {"MDIMA",16}, {"MDIMC",8}, {"MWG",16}, {"NDIMB",8}, {"NDIMC",8}, {"NWG",32}, {"SA",0}, {"SB",0}, {"STRM",0}, {"STRN",1}, {"VWM",1}, {"VWN",4} } },
|
||||||
{ "default", { {"KWG",16}, {"KWI",2}, {"MDIMA",16}, {"MDIMC",8}, {"MWG",16}, {"NDIMB",8}, {"NDIMC",8}, {"NWG",32}, {"SA",0}, {"SB",0}, {"STRM",0}, {"STRN",0}, {"VWM",1}, {"VWN",2} } },
|
{ "default", { {"KWG",16}, {"KWI",2}, {"MDIMA",8}, {"MDIMC",8}, {"MWG",16}, {"NDIMB",8}, {"NDIMC",8}, {"NWG",16}, {"SA",0}, {"SB",0}, {"STRM",0}, {"STRN",0}, {"VWM",1}, {"VWN",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // ARM GPUs
|
{ // ARM GPUs
|
||||||
|
@ -188,8 +201,11 @@ const Database::DatabaseEntry Database::XgemmDouble = {
|
||||||
{ // NVIDIA GPUs
|
{ // NVIDIA GPUs
|
||||||
kDeviceTypeGPU, "NVIDIA", {
|
kDeviceTypeGPU, "NVIDIA", {
|
||||||
{ "GRID K520", { {"KWG",16}, {"KWI",2}, {"MDIMA",8}, {"MDIMC",8}, {"MWG",16}, {"NDIMB",8}, {"NDIMC",8}, {"NWG",32}, {"SA",1}, {"SB",0}, {"STRM",0}, {"STRN",1}, {"VWM",2}, {"VWN",2} } },
|
{ "GRID K520", { {"KWG",16}, {"KWI",2}, {"MDIMA",8}, {"MDIMC",8}, {"MWG",16}, {"NDIMB",8}, {"NDIMC",8}, {"NWG",32}, {"SA",1}, {"SB",0}, {"STRM",0}, {"STRN",1}, {"VWM",2}, {"VWN",2} } },
|
||||||
|
{ "GeForce GTX 1070", { {"KWG",16}, {"KWI",2}, {"MDIMA",8}, {"MDIMC",16}, {"MWG",32}, {"NDIMB",8}, {"NDIMC",8}, {"NWG",64}, {"SA",0}, {"SB",0}, {"STRM",1}, {"STRN",1}, {"VWM",2}, {"VWN",8} } },
|
||||||
{ "GeForce GTX 480", { {"KWG",16}, {"KWI",2}, {"MDIMA",8}, {"MDIMC",16}, {"MWG",32}, {"NDIMB",32}, {"NDIMC",8}, {"NWG",64}, {"SA",1}, {"SB",1}, {"STRM",1}, {"STRN",0}, {"VWM",1}, {"VWN",2} } },
|
{ "GeForce GTX 480", { {"KWG",16}, {"KWI",2}, {"MDIMA",8}, {"MDIMC",16}, {"MWG",32}, {"NDIMB",32}, {"NDIMC",8}, {"NWG",64}, {"SA",1}, {"SB",1}, {"STRM",1}, {"STRN",0}, {"VWM",1}, {"VWN",2} } },
|
||||||
|
{ "GeForce GTX 670", { {"KWG",32}, {"KWI",8}, {"MDIMA",16}, {"MDIMC",32}, {"MWG",128}, {"NDIMB",16}, {"NDIMC",8}, {"NWG",32}, {"SA",0}, {"SB",1}, {"STRM",1}, {"STRN",0}, {"VWM",1}, {"VWN",1} } },
|
||||||
{ "GeForce GTX 680", { {"KWG",32}, {"KWI",8}, {"MDIMA",8}, {"MDIMC",8}, {"MWG",32}, {"NDIMB",16}, {"NDIMC",32}, {"NWG",128}, {"SA",1}, {"SB",0}, {"STRM",0}, {"STRN",1}, {"VWM",2}, {"VWN",4} } },
|
{ "GeForce GTX 680", { {"KWG",32}, {"KWI",8}, {"MDIMA",8}, {"MDIMC",8}, {"MWG",32}, {"NDIMB",16}, {"NDIMC",32}, {"NWG",128}, {"SA",1}, {"SB",0}, {"STRM",0}, {"STRN",1}, {"VWM",2}, {"VWN",4} } },
|
||||||
|
{ "GeForce GTX 750", { {"KWG",32}, {"KWI",8}, {"MDIMA",16}, {"MDIMC",32}, {"MWG",64}, {"NDIMB",16}, {"NDIMC",8}, {"NWG",128}, {"SA",0}, {"SB",0}, {"STRM",0}, {"STRN",1}, {"VWM",2}, {"VWN",1} } },
|
||||||
{ "GeForce GTX 750 Ti", { {"KWG",16}, {"KWI",2}, {"MDIMA",16}, {"MDIMC",8}, {"MWG",32}, {"NDIMB",16}, {"NDIMC",32}, {"NWG",32}, {"SA",0}, {"SB",0}, {"STRM",1}, {"STRN",1}, {"VWM",2}, {"VWN",1} } },
|
{ "GeForce GTX 750 Ti", { {"KWG",16}, {"KWI",2}, {"MDIMA",16}, {"MDIMC",8}, {"MWG",32}, {"NDIMB",16}, {"NDIMC",32}, {"NWG",32}, {"SA",0}, {"SB",0}, {"STRM",1}, {"STRN",1}, {"VWM",2}, {"VWN",1} } },
|
||||||
{ "GeForce GTX 980", { {"KWG",32}, {"KWI",8}, {"MDIMA",16}, {"MDIMC",8}, {"MWG",64}, {"NDIMB",32}, {"NDIMC",32}, {"NWG",128}, {"SA",0}, {"SB",0}, {"STRM",1}, {"STRN",0}, {"VWM",2}, {"VWN",4} } },
|
{ "GeForce GTX 980", { {"KWG",32}, {"KWI",8}, {"MDIMA",16}, {"MDIMC",8}, {"MWG",64}, {"NDIMB",32}, {"NDIMC",32}, {"NWG",128}, {"SA",0}, {"SB",0}, {"STRM",1}, {"STRN",0}, {"VWM",2}, {"VWN",4} } },
|
||||||
{ "GeForce GTX TITAN", { {"KWG",16}, {"KWI",8}, {"MDIMA",16}, {"MDIMC",8}, {"MWG",32}, {"NDIMB",16}, {"NDIMC",32}, {"NWG",128}, {"SA",1}, {"SB",1}, {"STRM",1}, {"STRN",1}, {"VWM",2}, {"VWN",2} } },
|
{ "GeForce GTX TITAN", { {"KWG",16}, {"KWI",8}, {"MDIMA",16}, {"MDIMC",8}, {"MWG",32}, {"NDIMB",16}, {"NDIMC",32}, {"NWG",128}, {"SA",1}, {"SB",1}, {"STRM",1}, {"STRN",1}, {"VWM",2}, {"VWN",2} } },
|
||||||
|
@ -215,6 +231,7 @@ const Database::DatabaseEntry Database::XgemmComplexDouble = {
|
||||||
kDeviceTypeGPU, "AMD", {
|
kDeviceTypeGPU, "AMD", {
|
||||||
{ "AMD Radeon R9 M370X Compute Engine", { {"KWG",32}, {"KWI",8}, {"MDIMA",8}, {"MDIMC",16}, {"MWG",32}, {"NDIMB",16}, {"NDIMC",16}, {"NWG",32}, {"SA",0}, {"SB",0}, {"STRM",1}, {"STRN",1}, {"VWM",2}, {"VWN",2} } },
|
{ "AMD Radeon R9 M370X Compute Engine", { {"KWG",32}, {"KWI",8}, {"MDIMA",8}, {"MDIMC",16}, {"MWG",32}, {"NDIMB",16}, {"NDIMC",16}, {"NWG",32}, {"SA",0}, {"SB",0}, {"STRM",1}, {"STRN",1}, {"VWM",2}, {"VWN",2} } },
|
||||||
{ "Hawaii", { {"KWG",16}, {"KWI",2}, {"MDIMA",16}, {"MDIMC",16}, {"MWG",16}, {"NDIMB",16}, {"NDIMC",16}, {"NWG",32}, {"SA",1}, {"SB",0}, {"STRM",0}, {"STRN",0}, {"VWM",1}, {"VWN",2} } },
|
{ "Hawaii", { {"KWG",16}, {"KWI",2}, {"MDIMA",16}, {"MDIMC",16}, {"MWG",16}, {"NDIMB",16}, {"NDIMC",16}, {"NWG",32}, {"SA",1}, {"SB",0}, {"STRM",0}, {"STRN",0}, {"VWM",1}, {"VWN",2} } },
|
||||||
|
{ "Oland", { {"KWG",16}, {"KWI",2}, {"MDIMA",16}, {"MDIMC",8}, {"MWG",16}, {"NDIMB",16}, {"NDIMC",32}, {"NWG",128}, {"SA",0}, {"SB",0}, {"STRM",0}, {"STRN",0}, {"VWM",1}, {"VWN",4} } },
|
||||||
{ "Pitcairn", { {"KWG",32}, {"KWI",2}, {"MDIMA",16}, {"MDIMC",8}, {"MWG",32}, {"NDIMB",8}, {"NDIMC",32}, {"NWG",32}, {"SA",0}, {"SB",1}, {"STRM",1}, {"STRN",0}, {"VWM",1}, {"VWN",1} } },
|
{ "Pitcairn", { {"KWG",32}, {"KWI",2}, {"MDIMA",16}, {"MDIMC",8}, {"MWG",32}, {"NDIMB",8}, {"NDIMC",32}, {"NWG",32}, {"SA",0}, {"SB",1}, {"STRM",1}, {"STRN",0}, {"VWM",1}, {"VWN",1} } },
|
||||||
{ "Tahiti", { {"KWG",16}, {"KWI",2}, {"MDIMA",16}, {"MDIMC",8}, {"MWG",16}, {"NDIMB",8}, {"NDIMC",8}, {"NWG",16}, {"SA",0}, {"SB",0}, {"STRM",1}, {"STRN",0}, {"VWM",1}, {"VWN",1} } },
|
{ "Tahiti", { {"KWG",16}, {"KWI",2}, {"MDIMA",16}, {"MDIMC",8}, {"MWG",16}, {"NDIMB",8}, {"NDIMC",8}, {"NWG",16}, {"SA",0}, {"SB",0}, {"STRM",1}, {"STRN",0}, {"VWM",1}, {"VWN",1} } },
|
||||||
{ "default", { {"KWG",16}, {"KWI",2}, {"MDIMA",8}, {"MDIMC",8}, {"MWG",16}, {"NDIMB",8}, {"NDIMC",8}, {"NWG",16}, {"SA",0}, {"SB",0}, {"STRM",0}, {"STRN",0}, {"VWM",1}, {"VWN",1} } },
|
{ "default", { {"KWG",16}, {"KWI",2}, {"MDIMA",8}, {"MDIMC",8}, {"MWG",16}, {"NDIMB",8}, {"NDIMC",8}, {"NWG",16}, {"SA",0}, {"SB",0}, {"STRM",0}, {"STRN",0}, {"VWM",1}, {"VWN",1} } },
|
||||||
|
@ -243,8 +260,11 @@ const Database::DatabaseEntry Database::XgemmComplexDouble = {
|
||||||
{ // NVIDIA GPUs
|
{ // NVIDIA GPUs
|
||||||
kDeviceTypeGPU, "NVIDIA", {
|
kDeviceTypeGPU, "NVIDIA", {
|
||||||
{ "GRID K520", { {"KWG",32}, {"KWI",8}, {"MDIMA",16}, {"MDIMC",16}, {"MWG",16}, {"NDIMB",8}, {"NDIMC",16}, {"NWG",64}, {"SA",1}, {"SB",0}, {"STRM",1}, {"STRN",1}, {"VWM",1}, {"VWN",1} } },
|
{ "GRID K520", { {"KWG",32}, {"KWI",8}, {"MDIMA",16}, {"MDIMC",16}, {"MWG",16}, {"NDIMB",8}, {"NDIMC",16}, {"NWG",64}, {"SA",1}, {"SB",0}, {"STRM",1}, {"STRN",1}, {"VWM",1}, {"VWN",1} } },
|
||||||
|
{ "GeForce GTX 1070", { {"KWG",32}, {"KWI",8}, {"MDIMA",32}, {"MDIMC",16}, {"MWG",32}, {"NDIMB",8}, {"NDIMC",8}, {"NWG",32}, {"SA",0}, {"SB",0}, {"STRM",0}, {"STRN",1}, {"VWM",1}, {"VWN",4} } },
|
||||||
{ "GeForce GTX 480", { {"KWG",16}, {"KWI",2}, {"MDIMA",32}, {"MDIMC",32}, {"MWG",32}, {"NDIMB",32}, {"NDIMC",8}, {"NWG",32}, {"SA",0}, {"SB",0}, {"STRM",1}, {"STRN",0}, {"VWM",1}, {"VWN",1} } },
|
{ "GeForce GTX 480", { {"KWG",16}, {"KWI",2}, {"MDIMA",32}, {"MDIMC",32}, {"MWG",32}, {"NDIMB",32}, {"NDIMC",8}, {"NWG",32}, {"SA",0}, {"SB",0}, {"STRM",1}, {"STRN",0}, {"VWM",1}, {"VWN",1} } },
|
||||||
|
{ "GeForce GTX 670", { {"KWG",32}, {"KWI",8}, {"MDIMA",16}, {"MDIMC",8}, {"MWG",16}, {"NDIMB",16}, {"NDIMC",32}, {"NWG",64}, {"SA",1}, {"SB",0}, {"STRM",0}, {"STRN",1}, {"VWM",1}, {"VWN",2} } },
|
||||||
{ "GeForce GTX 680", { {"KWG",16}, {"KWI",8}, {"MDIMA",16}, {"MDIMC",8}, {"MWG",64}, {"NDIMB",16}, {"NDIMC",32}, {"NWG",32}, {"SA",0}, {"SB",1}, {"STRM",1}, {"STRN",0}, {"VWM",1}, {"VWN",1} } },
|
{ "GeForce GTX 680", { {"KWG",16}, {"KWI",8}, {"MDIMA",16}, {"MDIMC",8}, {"MWG",64}, {"NDIMB",16}, {"NDIMC",32}, {"NWG",32}, {"SA",0}, {"SB",1}, {"STRM",1}, {"STRN",0}, {"VWM",1}, {"VWN",1} } },
|
||||||
|
{ "GeForce GTX 750", { {"KWG",32}, {"KWI",2}, {"MDIMA",8}, {"MDIMC",32}, {"MWG",32}, {"NDIMB",8}, {"NDIMC",8}, {"NWG",64}, {"SA",0}, {"SB",0}, {"STRM",1}, {"STRN",0}, {"VWM",1}, {"VWN",4} } },
|
||||||
{ "GeForce GTX 750 Ti", { {"KWG",16}, {"KWI",2}, {"MDIMA",16}, {"MDIMC",16}, {"MWG",16}, {"NDIMB",8}, {"NDIMC",8}, {"NWG",32}, {"SA",0}, {"SB",0}, {"STRM",0}, {"STRN",0}, {"VWM",1}, {"VWN",4} } },
|
{ "GeForce GTX 750 Ti", { {"KWG",16}, {"KWI",2}, {"MDIMA",16}, {"MDIMC",16}, {"MWG",16}, {"NDIMB",8}, {"NDIMC",8}, {"NWG",32}, {"SA",0}, {"SB",0}, {"STRM",0}, {"STRN",0}, {"VWM",1}, {"VWN",4} } },
|
||||||
{ "GeForce GTX 980", { {"KWG",16}, {"KWI",2}, {"MDIMA",16}, {"MDIMC",8}, {"MWG",32}, {"NDIMB",8}, {"NDIMC",16}, {"NWG",128}, {"SA",0}, {"SB",0}, {"STRM",1}, {"STRN",1}, {"VWM",2}, {"VWN",2} } },
|
{ "GeForce GTX 980", { {"KWG",16}, {"KWI",2}, {"MDIMA",16}, {"MDIMC",8}, {"MWG",32}, {"NDIMB",8}, {"NDIMC",16}, {"NWG",128}, {"SA",0}, {"SB",0}, {"STRM",1}, {"STRN",1}, {"VWM",2}, {"VWN",2} } },
|
||||||
{ "GeForce GTX TITAN X", { {"KWG",32}, {"KWI",8}, {"MDIMA",16}, {"MDIMC",16}, {"MWG",128}, {"NDIMB",16}, {"NDIMC",16}, {"NWG",32}, {"SA",0}, {"SB",0}, {"STRM",1}, {"STRN",0}, {"VWM",1}, {"VWN",1} } },
|
{ "GeForce GTX TITAN X", { {"KWG",32}, {"KWI",8}, {"MDIMA",16}, {"MDIMC",16}, {"MWG",128}, {"NDIMB",16}, {"NDIMC",16}, {"NWG",32}, {"SA",0}, {"SB",0}, {"STRM",1}, {"STRN",0}, {"VWM",1}, {"VWN",1} } },
|
||||||
|
|
|
@ -18,13 +18,14 @@ const Database::DatabaseEntry Database::XgemvHalf = {
|
||||||
"Xgemv", Precision::kHalf, {
|
"Xgemv", Precision::kHalf, {
|
||||||
{ // Intel GPUs
|
{ // Intel GPUs
|
||||||
kDeviceTypeGPU, "Intel", {
|
kDeviceTypeGPU, "Intel", {
|
||||||
{ "Intel(R) HD Graphics Skylake ULT GT2", { {"WGS1",128}, {"WPT1",1}, {"VW2",2}, {"WGS2",128}, {"WPT2",2}, {"VW3",1}, {"WGS3",64}, {"WPT3",1} } },
|
{ "Intel(R) HD Graphics 5500 BroadWell U-Processor GT2", { {"WGS1",64}, {"WPT1",1} } },
|
||||||
{ "default", { {"WGS1",128}, {"WPT1",1}, {"VW2",2}, {"WGS2",128}, {"WPT2",2}, {"VW3",1}, {"WGS3",64}, {"WPT3",1} } },
|
{ "Intel(R) HD Graphics Skylake ULT GT2", { {"WGS1",128}, {"WPT1",1} } },
|
||||||
|
{ "default", { {"WGS1",64}, {"WPT1",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Default
|
{ // Default
|
||||||
kDeviceTypeAll, "default", {
|
kDeviceTypeAll, "default", {
|
||||||
{ "default", { {"WGS1",128}, {"WPT1",1}, {"VW2",2}, {"WGS2",128}, {"WPT2",2}, {"VW3",1}, {"WGS3",64}, {"WPT3",1} } },
|
{ "default", { {"WGS1",64}, {"WPT1",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
}
|
}
|
||||||
|
@ -36,52 +37,58 @@ const Database::DatabaseEntry Database::XgemvSingle = {
|
||||||
"Xgemv", Precision::kSingle, {
|
"Xgemv", Precision::kSingle, {
|
||||||
{ // AMD GPUs
|
{ // AMD GPUs
|
||||||
kDeviceTypeGPU, "AMD", {
|
kDeviceTypeGPU, "AMD", {
|
||||||
{ "AMD Radeon R9 M370X Compute Engine", { {"WGS1",128}, {"WPT1",1}, {"VW2",1}, {"WGS2",128}, {"WPT2",1}, {"VW3",1}, {"WGS3",64}, {"WPT3",1} } },
|
{ "AMD Radeon R9 M370X Compute Engine", { {"WGS1",128}, {"WPT1",1} } },
|
||||||
{ "Hawaii", { {"WGS1",128}, {"WPT1",1}, {"VW2",1}, {"WGS2",64}, {"WPT2",1}, {"VW3",1}, {"WGS3",64}, {"WPT3",1} } },
|
{ "Hawaii", { {"WGS1",128}, {"WPT1",1} } },
|
||||||
{ "Pitcairn", { {"WGS1",256}, {"WPT1",1}, {"VW2",1}, {"WGS2",64}, {"WPT2",1}, {"VW3",1}, {"WGS3",64}, {"WPT3",1} } },
|
{ "Oland", { {"WGS1",128}, {"WPT1",1} } },
|
||||||
{ "Tahiti", { {"WGS1",256}, {"WPT1",1}, {"VW2",1}, {"WGS2",64}, {"WPT2",1}, {"VW3",1}, {"WGS3",64}, {"WPT3",1} } },
|
{ "Pitcairn", { {"WGS1",256}, {"WPT1",1} } },
|
||||||
{ "default", { {"WGS1",128}, {"WPT1",1}, {"VW2",1}, {"WGS2",64}, {"WPT2",1}, {"VW3",1}, {"WGS3",64}, {"WPT3",1} } },
|
{ "Tahiti", { {"WGS1",256}, {"WPT1",1} } },
|
||||||
|
{ "default", { {"WGS1",128}, {"WPT1",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Intel CPUs
|
{ // Intel CPUs
|
||||||
kDeviceTypeCPU, "Intel", {
|
kDeviceTypeCPU, "Intel", {
|
||||||
{ "Intel(R) Core(TM) i5-6200U CPU @ 2.30GHz", { {"WGS1",64}, {"WPT1",1}, {"VW2",4}, {"WGS2",128}, {"WPT2",4}, {"VW3",1}, {"WGS3",64}, {"WPT3",1} } },
|
{ "Intel(R) Core(TM) i5-6200U CPU @ 2.30GHz", { {"WGS1",64}, {"WPT1",1} } },
|
||||||
{ "Intel(R) Core(TM) i7-3770 CPU @ 3.40GHz", { {"WGS1",64}, {"WPT1",4}, {"VW2",1}, {"WGS2",64}, {"WPT2",4}, {"VW3",2}, {"WGS3",64}, {"WPT3",4} } },
|
{ "Intel(R) Core(TM) i7-3770 CPU @ 3.40GHz", { {"WGS1",64}, {"WPT1",4} } },
|
||||||
{ "default", { {"WGS1",64}, {"WPT1",1}, {"VW2",1}, {"WGS2",64}, {"WPT2",4}, {"VW3",1}, {"WGS3",64}, {"WPT3",1} } },
|
{ "default", { {"WGS1",64}, {"WPT1",4} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Intel GPUs
|
{ // Intel GPUs
|
||||||
kDeviceTypeGPU, "Intel", {
|
kDeviceTypeGPU, "Intel", {
|
||||||
{ "Intel(R) HD Graphics Haswell Ultrabook GT2 Mobile", { {"WGS1",256}, {"WPT1",1}, {"VW2",4}, {"WGS2",128}, {"WPT2",4}, {"VW3",4}, {"WGS3",256}, {"WPT3",4} } },
|
{ "Intel(R) HD Graphics 530", { {"WGS1",256}, {"WPT1",1} } },
|
||||||
{ "Intel(R) HD Graphics Skylake ULT GT2", { {"WGS1",64}, {"WPT1",1}, {"VW2",1}, {"WGS2",256}, {"WPT2",1}, {"VW3",4}, {"WGS3",64}, {"WPT3",4} } },
|
{ "Intel(R) HD Graphics 5500 BroadWell U-Processor GT2", { {"WGS1",64}, {"WPT1",1} } },
|
||||||
{ "Iris", { {"WGS1",64}, {"WPT1",2}, {"VW2",1}, {"WGS2",128}, {"WPT2",2}, {"VW3",4}, {"WGS3",64}, {"WPT3",8} } },
|
{ "Intel(R) HD Graphics Haswell Ultrabook GT2 Mobile", { {"WGS1",64}, {"WPT1",1} } },
|
||||||
{ "Iris Pro", { {"WGS1",256}, {"WPT1",2}, {"VW2",1}, {"WGS2",128}, {"WPT2",2}, {"VW3",4}, {"WGS3",64}, {"WPT3",4} } },
|
{ "Intel(R) HD Graphics Skylake ULT GT2", { {"WGS1",64}, {"WPT1",1} } },
|
||||||
{ "default", { {"WGS1",64}, {"WPT1",1}, {"VW2",1}, {"WGS2",128}, {"WPT2",1}, {"VW3",4}, {"WGS3",64}, {"WPT3",4} } },
|
{ "Iris", { {"WGS1",64}, {"WPT1",2} } },
|
||||||
|
{ "Iris Pro", { {"WGS1",256}, {"WPT1",2} } },
|
||||||
|
{ "default", { {"WGS1",64}, {"WPT1",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Intel accelerators
|
{ // Intel accelerators
|
||||||
kDeviceTypeAccelerator, "Intel", {
|
kDeviceTypeAccelerator, "Intel", {
|
||||||
{ "Intel(R) Many Integrated Core Acceleration Card", { {"WGS1",64}, {"WPT1",1}, {"VW2",1}, {"WGS2",64}, {"WPT2",1}, {"VW3",1}, {"WGS3",64}, {"WPT3",1} } },
|
{ "Intel(R) Many Integrated Core Acceleration Card", { {"WGS1",64}, {"WPT1",1} } },
|
||||||
{ "default", { {"WGS1",64}, {"WPT1",1}, {"VW2",1}, {"WGS2",64}, {"WPT2",1}, {"VW3",1}, {"WGS3",64}, {"WPT3",1} } },
|
{ "default", { {"WGS1",64}, {"WPT1",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // NVIDIA GPUs
|
{ // NVIDIA GPUs
|
||||||
kDeviceTypeGPU, "NVIDIA", {
|
kDeviceTypeGPU, "NVIDIA", {
|
||||||
{ "GRID K520", { {"WGS1",256}, {"WPT1",1}, {"VW2",2}, {"WGS2",256}, {"WPT2",2}, {"VW3",2}, {"WGS3",64}, {"WPT3",2} } },
|
{ "GRID K520", { {"WGS1",256}, {"WPT1",1} } },
|
||||||
{ "GeForce GTX 480", { {"WGS1",64}, {"WPT1",1}, {"VW2",1}, {"WGS2",128}, {"WPT2",1}, {"VW3",2}, {"WGS3",64}, {"WPT3",2} } },
|
{ "GeForce GTX 1070", { {"WGS1",128}, {"WPT1",1} } },
|
||||||
{ "GeForce GTX 680", { {"WGS1",256}, {"WPT1",1}, {"VW2",1}, {"WGS2",128}, {"WPT2",1}, {"VW3",2}, {"WGS3",128}, {"WPT3",2} } },
|
{ "GeForce GTX 480", { {"WGS1",64}, {"WPT1",1} } },
|
||||||
{ "GeForce GTX 750 Ti", { {"WGS1",256}, {"WPT1",1}, {"VW2",1}, {"WGS2",256}, {"WPT2",1}, {"VW3",4}, {"WGS3",128}, {"WPT3",4} } },
|
{ "GeForce GTX 670", { {"WGS1",64}, {"WPT1",1} } },
|
||||||
{ "GeForce GTX 980", { {"WGS1",128}, {"WPT1",1}, {"VW2",1}, {"WGS2",256}, {"WPT2",1}, {"VW3",1}, {"WGS3",128}, {"WPT3",1} } },
|
{ "GeForce GTX 680", { {"WGS1",256}, {"WPT1",1} } },
|
||||||
{ "GeForce GTX TITAN", { {"WGS1",256}, {"WPT1",1}, {"VW2",1}, {"WGS2",256}, {"WPT2",1}, {"VW3",1}, {"WGS3",256}, {"WPT3",1} } },
|
{ "GeForce GTX 750", { {"WGS1",256}, {"WPT1",1} } },
|
||||||
{ "GeForce GTX TITAN X", { {"WGS1",256}, {"WPT1",1}, {"VW2",1}, {"WGS2",64}, {"WPT2",1}, {"VW3",1}, {"WGS3",128}, {"WPT3",1} } },
|
{ "GeForce GTX 750 Ti", { {"WGS1",256}, {"WPT1",1} } },
|
||||||
{ "Tesla K20m", { {"WGS1",128}, {"WPT1",1}, {"VW2",1}, {"WGS2",256}, {"WPT2",1}, {"VW3",1}, {"WGS3",256}, {"WPT3",1} } },
|
{ "GeForce GTX 980", { {"WGS1",128}, {"WPT1",1} } },
|
||||||
{ "Tesla K40m", { {"WGS1",256}, {"WPT1",1}, {"VW2",1}, {"WGS2",256}, {"WPT2",1}, {"VW3",1}, {"WGS3",128}, {"WPT3",1} } },
|
{ "GeForce GTX TITAN", { {"WGS1",256}, {"WPT1",1} } },
|
||||||
{ "default", { {"WGS1",64}, {"WPT1",1}, {"VW2",1}, {"WGS2",64}, {"WPT2",1}, {"VW3",1}, {"WGS3",64}, {"WPT3",1} } },
|
{ "GeForce GTX TITAN X", { {"WGS1",256}, {"WPT1",1} } },
|
||||||
|
{ "Tesla K20m", { {"WGS1",128}, {"WPT1",1} } },
|
||||||
|
{ "Tesla K40m", { {"WGS1",256}, {"WPT1",1} } },
|
||||||
|
{ "default", { {"WGS1",256}, {"WPT1",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Default
|
{ // Default
|
||||||
kDeviceTypeAll, "default", {
|
kDeviceTypeAll, "default", {
|
||||||
{ "default", { {"WGS1",64}, {"WPT1",1}, {"VW2",1}, {"WGS2",64}, {"WPT2",1}, {"VW3",1}, {"WGS3",64}, {"WPT3",1} } },
|
{ "default", { {"WGS1",64}, {"WPT1",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
}
|
}
|
||||||
|
@ -93,48 +100,54 @@ const Database::DatabaseEntry Database::XgemvComplexSingle = {
|
||||||
"Xgemv", Precision::kComplexSingle, {
|
"Xgemv", Precision::kComplexSingle, {
|
||||||
{ // AMD GPUs
|
{ // AMD GPUs
|
||||||
kDeviceTypeGPU, "AMD", {
|
kDeviceTypeGPU, "AMD", {
|
||||||
{ "AMD Radeon R9 M370X Compute Engine", { {"WGS1",64}, {"WPT1",1}, {"VW2",2}, {"WGS2",256}, {"WPT2",2}, {"VW3",1}, {"WGS3",128}, {"WPT3",1} } },
|
{ "AMD Radeon R9 M370X Compute Engine", { {"WGS1",64}, {"WPT1",1} } },
|
||||||
{ "Hawaii", { {"WGS1",64}, {"WPT1",1}, {"VW2",1}, {"WGS2",64}, {"WPT2",1}, {"VW3",1}, {"WGS3",64}, {"WPT3",1} } },
|
{ "Hawaii", { {"WGS1",64}, {"WPT1",1} } },
|
||||||
{ "Pitcairn", { {"WGS1",64}, {"WPT1",1}, {"VW2",1}, {"WGS2",64}, {"WPT2",1}, {"VW3",2}, {"WGS3",64}, {"WPT3",2} } },
|
{ "Oland", { {"WGS1",64}, {"WPT1",1} } },
|
||||||
{ "Tahiti", { {"WGS1",64}, {"WPT1",1}, {"VW2",1}, {"WGS2",128}, {"WPT2",1}, {"VW3",1}, {"WGS3",64}, {"WPT3",1} } },
|
{ "Pitcairn", { {"WGS1",64}, {"WPT1",1} } },
|
||||||
{ "default", { {"WGS1",64}, {"WPT1",1}, {"VW2",1}, {"WGS2",64}, {"WPT2",1}, {"VW3",1}, {"WGS3",64}, {"WPT3",1} } },
|
{ "Tahiti", { {"WGS1",64}, {"WPT1",1} } },
|
||||||
|
{ "default", { {"WGS1",64}, {"WPT1",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Intel CPUs
|
{ // Intel CPUs
|
||||||
kDeviceTypeCPU, "Intel", {
|
kDeviceTypeCPU, "Intel", {
|
||||||
{ "Intel(R) Core(TM) i5-6200U CPU @ 2.30GHz", { {"WGS1",128}, {"WPT1",1}, {"VW2",1}, {"WGS2",128}, {"WPT2",2}, {"VW3",1}, {"WGS3",64}, {"WPT3",1} } },
|
{ "Intel(R) Core(TM) i5-6200U CPU @ 2.30GHz", { {"WGS1",128}, {"WPT1",1} } },
|
||||||
{ "Intel(R) Core(TM) i7-3770 CPU @ 3.40GHz", { {"WGS1",64}, {"WPT1",4}, {"VW2",4}, {"WGS2",64}, {"WPT2",4}, {"VW3",2}, {"WGS3",64}, {"WPT3",2} } },
|
{ "Intel(R) Core(TM) i7-3770 CPU @ 3.40GHz", { {"WGS1",64}, {"WPT1",4} } },
|
||||||
{ "default", { {"WGS1",64}, {"WPT1",1}, {"VW2",1}, {"WGS2",64}, {"WPT2",2}, {"VW3",1}, {"WGS3",64}, {"WPT3",1} } },
|
{ "default", { {"WGS1",64}, {"WPT1",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Intel GPUs
|
{ // Intel GPUs
|
||||||
kDeviceTypeGPU, "Intel", {
|
kDeviceTypeGPU, "Intel", {
|
||||||
{ "Intel(R) HD Graphics Haswell Ultrabook GT2 Mobile", { {"WGS1",128}, {"WPT1",1}, {"VW2",2}, {"WGS2",128}, {"WPT2",2}, {"VW3",4}, {"WGS3",128}, {"WPT3",4} } },
|
{ "Intel(R) HD Graphics 530", { {"WGS1",64}, {"WPT1",1} } },
|
||||||
{ "Intel(R) HD Graphics Skylake ULT GT2", { {"WGS1",64}, {"WPT1",1}, {"VW2",1}, {"WGS2",64}, {"WPT2",1}, {"VW3",4}, {"WGS3",64}, {"WPT3",4} } },
|
{ "Intel(R) HD Graphics 5500 BroadWell U-Processor GT2", { {"WGS1",64}, {"WPT1",1} } },
|
||||||
{ "Iris", { {"WGS1",256}, {"WPT1",1}, {"VW2",1}, {"WGS2",64}, {"WPT2",1}, {"VW3",1}, {"WGS3",64}, {"WPT3",1} } },
|
{ "Intel(R) HD Graphics Haswell Ultrabook GT2 Mobile", { {"WGS1",128}, {"WPT1",1} } },
|
||||||
{ "Iris Pro", { {"WGS1",64}, {"WPT1",1}, {"VW2",4}, {"WGS2",128}, {"WPT2",4}, {"VW3",2}, {"WGS3",64}, {"WPT3",2} } },
|
{ "Intel(R) HD Graphics Skylake ULT GT2", { {"WGS1",64}, {"WPT1",1} } },
|
||||||
{ "default", { {"WGS1",64}, {"WPT1",1}, {"VW2",1}, {"WGS2",64}, {"WPT2",1}, {"VW3",1}, {"WGS3",64}, {"WPT3",1} } },
|
{ "Iris", { {"WGS1",256}, {"WPT1",1} } },
|
||||||
|
{ "Iris Pro", { {"WGS1",64}, {"WPT1",1} } },
|
||||||
|
{ "default", { {"WGS1",64}, {"WPT1",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Intel accelerators
|
{ // Intel accelerators
|
||||||
kDeviceTypeAccelerator, "Intel", {
|
kDeviceTypeAccelerator, "Intel", {
|
||||||
{ "Intel(R) Many Integrated Core Acceleration Card", { {"WGS1",64}, {"WPT1",1}, {"VW2",1}, {"WGS2",64}, {"WPT2",1}, {"VW3",1}, {"WGS3",64}, {"WPT3",1} } },
|
{ "Intel(R) Many Integrated Core Acceleration Card", { {"WGS1",64}, {"WPT1",1} } },
|
||||||
{ "default", { {"WGS1",64}, {"WPT1",1}, {"VW2",1}, {"WGS2",64}, {"WPT2",1}, {"VW3",1}, {"WGS3",64}, {"WPT3",1} } },
|
{ "default", { {"WGS1",64}, {"WPT1",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // NVIDIA GPUs
|
{ // NVIDIA GPUs
|
||||||
kDeviceTypeGPU, "NVIDIA", {
|
kDeviceTypeGPU, "NVIDIA", {
|
||||||
{ "GRID K520", { {"WGS1",256}, {"WPT1",1}, {"VW2",1}, {"WGS2",256}, {"WPT2",1}, {"VW3",1}, {"WGS3",64}, {"WPT3",1} } },
|
{ "GRID K520", { {"WGS1",256}, {"WPT1",1} } },
|
||||||
{ "GeForce GTX 480", { {"WGS1",64}, {"WPT1",1}, {"VW2",1}, {"WGS2",64}, {"WPT2",1}, {"VW3",1}, {"WGS3",64}, {"WPT3",1} } },
|
{ "GeForce GTX 1070", { {"WGS1",64}, {"WPT1",1} } },
|
||||||
{ "GeForce GTX 680", { {"WGS1",64}, {"WPT1",1}, {"VW2",1}, {"WGS2",64}, {"WPT2",1}, {"VW3",1}, {"WGS3",64}, {"WPT3",1} } },
|
{ "GeForce GTX 480", { {"WGS1",64}, {"WPT1",1} } },
|
||||||
{ "GeForce GTX 750 Ti", { {"WGS1",64}, {"WPT1",1}, {"VW2",1}, {"WGS2",64}, {"WPT2",1} } },
|
{ "GeForce GTX 670", { {"WGS1",64}, {"WPT1",1} } },
|
||||||
|
{ "GeForce GTX 680", { {"WGS1",64}, {"WPT1",1} } },
|
||||||
|
{ "GeForce GTX 750", { {"WGS1",128}, {"WPT1",1} } },
|
||||||
|
{ "GeForce GTX 750 Ti", { {"WGS1",64}, {"WPT1",1} } },
|
||||||
{ "GeForce GTX TITAN", { {"WGS1",256}, {"WPT1",1} } },
|
{ "GeForce GTX TITAN", { {"WGS1",256}, {"WPT1",1} } },
|
||||||
{ "default", { {"WGS1",64}, {"WPT1",1}, {"VW2",1}, {"WGS2",64}, {"WPT2",1}, {"VW3",1}, {"WGS3",64}, {"WPT3",1} } },
|
{ "default", { {"WGS1",64}, {"WPT1",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Default
|
{ // Default
|
||||||
kDeviceTypeAll, "default", {
|
kDeviceTypeAll, "default", {
|
||||||
{ "default", { {"WGS1",64}, {"WPT1",1}, {"VW2",1}, {"WGS2",64}, {"WPT2",1}, {"VW3",1}, {"WGS3",64}, {"WPT3",1} } },
|
{ "default", { {"WGS1",64}, {"WPT1",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
}
|
}
|
||||||
|
@ -146,43 +159,47 @@ const Database::DatabaseEntry Database::XgemvDouble = {
|
||||||
"Xgemv", Precision::kDouble, {
|
"Xgemv", Precision::kDouble, {
|
||||||
{ // AMD GPUs
|
{ // AMD GPUs
|
||||||
kDeviceTypeGPU, "AMD", {
|
kDeviceTypeGPU, "AMD", {
|
||||||
{ "AMD Radeon R9 M370X Compute Engine", { {"WGS1",64}, {"WPT1",1}, {"VW2",1}, {"WGS2",256}, {"WPT2",1}, {"VW3",1}, {"WGS3",128}, {"WPT3",1} } },
|
{ "AMD Radeon R9 M370X Compute Engine", { {"WGS1",64}, {"WPT1",1} } },
|
||||||
{ "Hawaii", { {"WGS1",128}, {"WPT1",1}, {"VW2",1}, {"WGS2",64}, {"WPT2",1}, {"VW3",1}, {"WGS3",64}, {"WPT3",1} } },
|
{ "Hawaii", { {"WGS1",128}, {"WPT1",1} } },
|
||||||
{ "Pitcairn", { {"WGS1",256}, {"WPT1",1}, {"VW2",1}, {"WGS2",64}, {"WPT2",1}, {"VW3",2}, {"WGS3",64}, {"WPT3",2} } },
|
{ "Oland", { {"WGS1",256}, {"WPT1",1} } },
|
||||||
{ "Tahiti", { {"WGS1",256}, {"WPT1",1}, {"VW2",1}, {"WGS2",64}, {"WPT2",1}, {"VW3",2}, {"WGS3",64}, {"WPT3",2} } },
|
{ "Pitcairn", { {"WGS1",256}, {"WPT1",1} } },
|
||||||
{ "default", { {"WGS1",64}, {"WPT1",1}, {"VW2",1}, {"WGS2",64}, {"WPT2",1}, {"VW3",1}, {"WGS3",64}, {"WPT3",1} } },
|
{ "Tahiti", { {"WGS1",256}, {"WPT1",1} } },
|
||||||
|
{ "default", { {"WGS1",256}, {"WPT1",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Intel CPUs
|
{ // Intel CPUs
|
||||||
kDeviceTypeCPU, "Intel", {
|
kDeviceTypeCPU, "Intel", {
|
||||||
{ "Intel(R) Core(TM) i5-6200U CPU @ 2.30GHz", { {"WGS1",64}, {"WPT1",2}, {"VW2",4}, {"WGS2",128}, {"WPT2",4}, {"VW3",1}, {"WGS3",64}, {"WPT3",1} } },
|
{ "Intel(R) Core(TM) i5-6200U CPU @ 2.30GHz", { {"WGS1",64}, {"WPT1",2} } },
|
||||||
{ "Intel(R) Core(TM) i7-3770 CPU @ 3.40GHz", { {"WGS1",64}, {"WPT1",4}, {"VW2",1}, {"WGS2",64}, {"WPT2",4}, {"VW3",1}, {"WGS3",64}, {"WPT3",2} } },
|
{ "Intel(R) Core(TM) i7-3770 CPU @ 3.40GHz", { {"WGS1",64}, {"WPT1",4} } },
|
||||||
{ "default", { {"WGS1",64}, {"WPT1",2}, {"VW2",1}, {"WGS2",64}, {"WPT2",4}, {"VW3",1}, {"WGS3",64}, {"WPT3",1} } },
|
{ "default", { {"WGS1",64}, {"WPT1",4} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Intel accelerators
|
{ // Intel accelerators
|
||||||
kDeviceTypeAccelerator, "Intel", {
|
kDeviceTypeAccelerator, "Intel", {
|
||||||
{ "Intel(R) Many Integrated Core Acceleration Card", { {"WGS1",64}, {"WPT1",1}, {"VW2",1}, {"WGS2",64}, {"WPT2",1}, {"VW3",1}, {"WGS3",64}, {"WPT3",1} } },
|
{ "Intel(R) Many Integrated Core Acceleration Card", { {"WGS1",64}, {"WPT1",1} } },
|
||||||
{ "default", { {"WGS1",64}, {"WPT1",1}, {"VW2",1}, {"WGS2",64}, {"WPT2",1}, {"VW3",1}, {"WGS3",64}, {"WPT3",1} } },
|
{ "default", { {"WGS1",64}, {"WPT1",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // NVIDIA GPUs
|
{ // NVIDIA GPUs
|
||||||
kDeviceTypeGPU, "NVIDIA", {
|
kDeviceTypeGPU, "NVIDIA", {
|
||||||
{ "GRID K520", { {"WGS1",128}, {"WPT1",1}, {"VW2",1}, {"WGS2",256}, {"WPT2",1}, {"VW3",1}, {"WGS3",64}, {"WPT3",1} } },
|
{ "GRID K520", { {"WGS1",128}, {"WPT1",1} } },
|
||||||
{ "GeForce GTX 480", { {"WGS1",256}, {"WPT1",1}, {"VW2",1}, {"WGS2",64}, {"WPT2",1}, {"VW3",1}, {"WGS3",64}, {"WPT3",1} } },
|
{ "GeForce GTX 1070", { {"WGS1",64}, {"WPT1",1} } },
|
||||||
{ "GeForce GTX 680", { {"WGS1",128}, {"WPT1",1}, {"VW2",1}, {"WGS2",128}, {"WPT2",1}, {"VW3",2}, {"WGS3",128}, {"WPT3",2} } },
|
{ "GeForce GTX 480", { {"WGS1",256}, {"WPT1",1} } },
|
||||||
{ "GeForce GTX 750 Ti", { {"WGS1",64}, {"WPT1",1}, {"VW2",1}, {"WGS2",256}, {"WPT2",1}, {"VW3",2}, {"WGS3",256}, {"WPT3",2} } },
|
{ "GeForce GTX 670", { {"WGS1",128}, {"WPT1",1} } },
|
||||||
{ "GeForce GTX 980", { {"WGS1",64}, {"WPT1",1}, {"VW2",1}, {"WGS2",64}, {"WPT2",1}, {"VW3",1}, {"WGS3",64}, {"WPT3",1} } },
|
{ "GeForce GTX 680", { {"WGS1",128}, {"WPT1",1} } },
|
||||||
{ "GeForce GTX TITAN", { {"WGS1",256}, {"WPT1",1}, {"VW2",1}, {"WGS2",256}, {"WPT2",1}, {"VW3",1}, {"WGS3",256}, {"WPT3",1} } },
|
{ "GeForce GTX 750", { {"WGS1",64}, {"WPT1",1} } },
|
||||||
{ "GeForce GTX TITAN X", { {"WGS1",64}, {"WPT1",1}, {"VW2",1}, {"WGS2",128}, {"WPT2",1}, {"VW3",1}, {"WGS3",128}, {"WPT3",1} } },
|
{ "GeForce GTX 750 Ti", { {"WGS1",64}, {"WPT1",1} } },
|
||||||
{ "Tesla K20m", { {"WGS1",256}, {"WPT1",1}, {"VW2",1}, {"WGS2",128}, {"WPT2",1}, {"VW3",1}, {"WGS3",64}, {"WPT3",1} } },
|
{ "GeForce GTX 980", { {"WGS1",64}, {"WPT1",1} } },
|
||||||
{ "Tesla K40m", { {"WGS1",256}, {"WPT1",1}, {"VW2",1}, {"WGS2",256}, {"WPT2",1}, {"VW3",1}, {"WGS3",256}, {"WPT3",1} } },
|
{ "GeForce GTX TITAN", { {"WGS1",256}, {"WPT1",1} } },
|
||||||
{ "default", { {"WGS1",64}, {"WPT1",1}, {"VW2",1}, {"WGS2",64}, {"WPT2",1}, {"VW3",1}, {"WGS3",64}, {"WPT3",1} } },
|
{ "GeForce GTX TITAN X", { {"WGS1",64}, {"WPT1",1} } },
|
||||||
|
{ "Tesla K20m", { {"WGS1",256}, {"WPT1",1} } },
|
||||||
|
{ "Tesla K40m", { {"WGS1",256}, {"WPT1",1} } },
|
||||||
|
{ "default", { {"WGS1",128}, {"WPT1",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Default
|
{ // Default
|
||||||
kDeviceTypeAll, "default", {
|
kDeviceTypeAll, "default", {
|
||||||
{ "default", { {"WGS1",64}, {"WPT1",1}, {"VW2",1}, {"WGS2",64}, {"WPT2",1}, {"VW3",1}, {"WGS3",64}, {"WPT3",1} } },
|
{ "default", { {"WGS1",128}, {"WPT1",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
}
|
}
|
||||||
|
@ -194,36 +211,38 @@ const Database::DatabaseEntry Database::XgemvComplexDouble = {
|
||||||
"Xgemv", Precision::kComplexDouble, {
|
"Xgemv", Precision::kComplexDouble, {
|
||||||
{ // AMD GPUs
|
{ // AMD GPUs
|
||||||
kDeviceTypeGPU, "AMD", {
|
kDeviceTypeGPU, "AMD", {
|
||||||
{ "AMD Radeon R9 M370X Compute Engine", { {"WGS1",64}, {"WPT1",1}, {"VW2",1}, {"WGS2",256}, {"WPT2",1}, {"VW3",1}, {"WGS3",128}, {"WPT3",1} } },
|
{ "AMD Radeon R9 M370X Compute Engine", { {"WGS1",64}, {"WPT1",1} } },
|
||||||
{ "Hawaii", { {"WGS1",64}, {"WPT1",1}, {"VW2",1}, {"WGS2",64}, {"WPT2",1}, {"VW3",1}, {"WGS3",64}, {"WPT3",1} } },
|
{ "Hawaii", { {"WGS1",64}, {"WPT1",1} } },
|
||||||
{ "Pitcairn", { {"WGS1",256}, {"WPT1",1}, {"VW2",1}, {"WGS2",64}, {"WPT2",1}, {"VW3",1}, {"WGS3",64}, {"WPT3",1} } },
|
{ "Oland", { {"WGS1",256}, {"WPT1",1} } },
|
||||||
{ "Tahiti", { {"WGS1",256}, {"WPT1",1}, {"VW2",1}, {"WGS2",64}, {"WPT2",1}, {"VW3",1}, {"WGS3",64}, {"WPT3",1} } },
|
{ "Pitcairn", { {"WGS1",256}, {"WPT1",1} } },
|
||||||
{ "default", { {"WGS1",64}, {"WPT1",1}, {"VW2",1}, {"WGS2",64}, {"WPT2",1}, {"VW3",1}, {"WGS3",64}, {"WPT3",1} } },
|
{ "Tahiti", { {"WGS1",256}, {"WPT1",1} } },
|
||||||
|
{ "default", { {"WGS1",64}, {"WPT1",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Intel CPUs
|
{ // Intel CPUs
|
||||||
kDeviceTypeCPU, "Intel", {
|
kDeviceTypeCPU, "Intel", {
|
||||||
{ "Intel(R) Core(TM) i5-6200U CPU @ 2.30GHz", { {"WGS1",64}, {"WPT1",1}, {"VW2",2}, {"WGS2",64}, {"WPT2",4}, {"VW3",1}, {"WGS3",256}, {"WPT3",1} } },
|
{ "Intel(R) Core(TM) i5-6200U CPU @ 2.30GHz", { {"WGS1",64}, {"WPT1",1} } },
|
||||||
{ "Intel(R) Core(TM) i7-3770 CPU @ 3.40GHz", { {"WGS1",64}, {"WPT1",4}, {"VW2",4}, {"WGS2",64}, {"WPT2",4}, {"VW3",2}, {"WGS3",256}, {"WPT3",2} } },
|
{ "Intel(R) Core(TM) i7-3770 CPU @ 3.40GHz", { {"WGS1",64}, {"WPT1",4} } },
|
||||||
{ "default", { {"WGS1",64}, {"WPT1",1}, {"VW2",2}, {"WGS2",64}, {"WPT2",4}, {"VW3",1}, {"WGS3",256}, {"WPT3",1} } },
|
{ "default", { {"WGS1",64}, {"WPT1",4} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Intel accelerators
|
{ // Intel accelerators
|
||||||
kDeviceTypeAccelerator, "Intel", {
|
kDeviceTypeAccelerator, "Intel", {
|
||||||
{ "Intel(R) Many Integrated Core Acceleration Card", { {"WGS1",64}, {"WPT1",1}, {"VW2",1}, {"WGS2",64}, {"WPT2",1}, {"VW3",1}, {"WGS3",64}, {"WPT3",1} } },
|
{ "Intel(R) Many Integrated Core Acceleration Card", { {"WGS1",64}, {"WPT1",1} } },
|
||||||
{ "default", { {"WGS1",64}, {"WPT1",1}, {"VW2",1}, {"WGS2",64}, {"WPT2",1}, {"VW3",1}, {"WGS3",64}, {"WPT3",1} } },
|
{ "default", { {"WGS1",64}, {"WPT1",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // NVIDIA GPUs
|
{ // NVIDIA GPUs
|
||||||
kDeviceTypeGPU, "NVIDIA", {
|
kDeviceTypeGPU, "NVIDIA", {
|
||||||
{ "GRID K520", { {"WGS1",128}, {"WPT1",1}, {"VW2",1}, {"WGS2",128}, {"WPT2",1}, {"VW3",1}, {"WGS3",256}, {"WPT3",1} } },
|
{ "GRID K520", { {"WGS1",128}, {"WPT1",1} } },
|
||||||
{ "GeForce GTX 480", { {"WGS1",64}, {"WPT1",1}, {"VW2",1}, {"WGS2",64}, {"WPT2",1}, {"VW3",1}, {"WGS3",64}, {"WPT3",1} } },
|
{ "GeForce GTX 480", { {"WGS1",64}, {"WPT1",1} } },
|
||||||
{ "default", { {"WGS1",64}, {"WPT1",1}, {"VW2",1}, {"WGS2",64}, {"WPT2",1}, {"VW3",1}, {"WGS3",64}, {"WPT3",1} } },
|
{ "GeForce GTX 670", { {"WGS1",128}, {"WPT1",1} } },
|
||||||
|
{ "default", { {"WGS1",128}, {"WPT1",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Default
|
{ // Default
|
||||||
kDeviceTypeAll, "default", {
|
kDeviceTypeAll, "default", {
|
||||||
{ "default", { {"WGS1",64}, {"WPT1",1}, {"VW2",1}, {"WGS2",64}, {"WPT2",1}, {"VW3",1}, {"WGS3",64}, {"WPT3",1} } },
|
{ "default", { {"WGS1",64}, {"WPT1",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
}
|
}
|
||||||
|
|
250
src/database/kernels/xgemv_fast.hpp
Normal file
250
src/database/kernels/xgemv_fast.hpp
Normal file
|
@ -0,0 +1,250 @@
|
||||||
|
|
||||||
|
// =================================================================================================
|
||||||
|
// This file is part of the CLBlast project. The project is licensed under Apache Version 2.0. This
|
||||||
|
// project loosely follows the Google C++ styleguide and uses a tab-size of two spaces and a max-
|
||||||
|
// width of 100 characters per line.
|
||||||
|
//
|
||||||
|
// Author(s):
|
||||||
|
// Database generator <database.py>
|
||||||
|
//
|
||||||
|
// This file populates the database with best-found tuning parameters for the 'Xgemv_Fast' kernels.
|
||||||
|
//
|
||||||
|
// =================================================================================================
|
||||||
|
|
||||||
|
namespace clblast {
|
||||||
|
// =================================================================================================
|
||||||
|
|
||||||
|
const Database::DatabaseEntry Database::XgemvFastHalf = {
|
||||||
|
"XgemvFast", Precision::kHalf, {
|
||||||
|
{ // Intel GPUs
|
||||||
|
kDeviceTypeGPU, "Intel", {
|
||||||
|
{ "Intel(R) HD Graphics 5500 BroadWell U-Processor GT2", { {"VW2",1}, {"WGS2",16}, {"WPT2",1} } },
|
||||||
|
{ "Intel(R) HD Graphics Skylake ULT GT2", { {"VW2",2}, {"WGS2",128}, {"WPT2",2} } },
|
||||||
|
{ "default", { {"VW2",1}, {"WGS2",16}, {"WPT2",1} } },
|
||||||
|
}
|
||||||
|
},
|
||||||
|
{ // Default
|
||||||
|
kDeviceTypeAll, "default", {
|
||||||
|
{ "default", { {"VW2",1}, {"WGS2",16}, {"WPT2",1} } },
|
||||||
|
}
|
||||||
|
},
|
||||||
|
}
|
||||||
|
};
|
||||||
|
|
||||||
|
// =================================================================================================
|
||||||
|
|
||||||
|
const Database::DatabaseEntry Database::XgemvFastSingle = {
|
||||||
|
"XgemvFast", Precision::kSingle, {
|
||||||
|
{ // AMD GPUs
|
||||||
|
kDeviceTypeGPU, "AMD", {
|
||||||
|
{ "AMD Radeon R9 M370X Compute Engine", { {"VW2",1}, {"WGS2",128}, {"WPT2",1} } },
|
||||||
|
{ "Hawaii", { {"VW2",1}, {"WGS2",64}, {"WPT2",1} } },
|
||||||
|
{ "Oland", { {"VW2",1}, {"WGS2",64}, {"WPT2",1} } },
|
||||||
|
{ "Pitcairn", { {"VW2",1}, {"WGS2",64}, {"WPT2",1} } },
|
||||||
|
{ "Tahiti", { {"VW2",1}, {"WGS2",64}, {"WPT2",1} } },
|
||||||
|
{ "default", { {"VW2",1}, {"WGS2",64}, {"WPT2",1} } },
|
||||||
|
}
|
||||||
|
},
|
||||||
|
{ // Intel CPUs
|
||||||
|
kDeviceTypeCPU, "Intel", {
|
||||||
|
{ "Intel(R) Core(TM) i5-6200U CPU @ 2.30GHz", { {"VW2",4}, {"WGS2",128}, {"WPT2",4} } },
|
||||||
|
{ "Intel(R) Core(TM) i7-3770 CPU @ 3.40GHz", { {"VW2",1}, {"WGS2",64}, {"WPT2",4} } },
|
||||||
|
{ "default", { {"VW2",4}, {"WGS2",64}, {"WPT2",4} } },
|
||||||
|
}
|
||||||
|
},
|
||||||
|
{ // Intel GPUs
|
||||||
|
kDeviceTypeGPU, "Intel", {
|
||||||
|
{ "Intel(R) HD Graphics 530", { {"VW2",1}, {"WGS2",256}, {"WPT2",1} } },
|
||||||
|
{ "Intel(R) HD Graphics 5500 BroadWell U-Processor GT2", { {"VW2",2}, {"WGS2",32}, {"WPT2",2} } },
|
||||||
|
{ "Intel(R) HD Graphics Haswell Ultrabook GT2 Mobile", { {"VW2",4}, {"WGS2",128}, {"WPT2",4} } },
|
||||||
|
{ "Intel(R) HD Graphics Skylake ULT GT2", { {"VW2",1}, {"WGS2",256}, {"WPT2",1} } },
|
||||||
|
{ "Iris", { {"VW2",1}, {"WGS2",128}, {"WPT2",2} } },
|
||||||
|
{ "Iris Pro", { {"VW2",1}, {"WGS2",128}, {"WPT2",2} } },
|
||||||
|
{ "default", { {"VW2",2}, {"WGS2",64}, {"WPT2",2} } },
|
||||||
|
}
|
||||||
|
},
|
||||||
|
{ // Intel accelerators
|
||||||
|
kDeviceTypeAccelerator, "Intel", {
|
||||||
|
{ "Intel(R) Many Integrated Core Acceleration Card", { {"VW2",1}, {"WGS2",64}, {"WPT2",1} } },
|
||||||
|
{ "default", { {"VW2",1}, {"WGS2",64}, {"WPT2",1} } },
|
||||||
|
}
|
||||||
|
},
|
||||||
|
{ // NVIDIA GPUs
|
||||||
|
kDeviceTypeGPU, "NVIDIA", {
|
||||||
|
{ "GRID K520", { {"VW2",2}, {"WGS2",256}, {"WPT2",2} } },
|
||||||
|
{ "GeForce GTX 1070", { {"VW2",1}, {"WGS2",256}, {"WPT2",1} } },
|
||||||
|
{ "GeForce GTX 480", { {"VW2",1}, {"WGS2",128}, {"WPT2",1} } },
|
||||||
|
{ "GeForce GTX 670", { {"VW2",2}, {"WGS2",256}, {"WPT2",2} } },
|
||||||
|
{ "GeForce GTX 680", { {"VW2",1}, {"WGS2",128}, {"WPT2",1} } },
|
||||||
|
{ "GeForce GTX 750", { {"VW2",1}, {"WGS2",256}, {"WPT2",1} } },
|
||||||
|
{ "GeForce GTX 750 Ti", { {"VW2",1}, {"WGS2",256}, {"WPT2",1} } },
|
||||||
|
{ "GeForce GTX 980", { {"VW2",1}, {"WGS2",256}, {"WPT2",1} } },
|
||||||
|
{ "GeForce GTX TITAN", { {"VW2",1}, {"WGS2",256}, {"WPT2",1} } },
|
||||||
|
{ "GeForce GTX TITAN X", { {"VW2",1}, {"WGS2",64}, {"WPT2",1} } },
|
||||||
|
{ "Tesla K20m", { {"VW2",1}, {"WGS2",256}, {"WPT2",1} } },
|
||||||
|
{ "Tesla K40m", { {"VW2",1}, {"WGS2",256}, {"WPT2",1} } },
|
||||||
|
{ "default", { {"VW2",1}, {"WGS2",256}, {"WPT2",1} } },
|
||||||
|
}
|
||||||
|
},
|
||||||
|
{ // Default
|
||||||
|
kDeviceTypeAll, "default", {
|
||||||
|
{ "default", { {"VW2",1}, {"WGS2",64}, {"WPT2",1} } },
|
||||||
|
}
|
||||||
|
},
|
||||||
|
}
|
||||||
|
};
|
||||||
|
|
||||||
|
// =================================================================================================
|
||||||
|
|
||||||
|
const Database::DatabaseEntry Database::XgemvFastComplexSingle = {
|
||||||
|
"XgemvFast", Precision::kComplexSingle, {
|
||||||
|
{ // AMD GPUs
|
||||||
|
kDeviceTypeGPU, "AMD", {
|
||||||
|
{ "AMD Radeon R9 M370X Compute Engine", { {"VW2",2}, {"WGS2",256}, {"WPT2",2} } },
|
||||||
|
{ "Hawaii", { {"VW2",1}, {"WGS2",64}, {"WPT2",1} } },
|
||||||
|
{ "Oland", { {"VW2",1}, {"WGS2",64}, {"WPT2",1} } },
|
||||||
|
{ "Pitcairn", { {"VW2",1}, {"WGS2",64}, {"WPT2",1} } },
|
||||||
|
{ "Tahiti", { {"VW2",1}, {"WGS2",128}, {"WPT2",1} } },
|
||||||
|
{ "default", { {"VW2",1}, {"WGS2",64}, {"WPT2",1} } },
|
||||||
|
}
|
||||||
|
},
|
||||||
|
{ // Intel CPUs
|
||||||
|
kDeviceTypeCPU, "Intel", {
|
||||||
|
{ "Intel(R) Core(TM) i5-6200U CPU @ 2.30GHz", { {"VW2",1}, {"WGS2",128}, {"WPT2",2} } },
|
||||||
|
{ "Intel(R) Core(TM) i7-3770 CPU @ 3.40GHz", { {"VW2",4}, {"WGS2",64}, {"WPT2",4} } },
|
||||||
|
{ "default", { {"VW2",1}, {"WGS2",64}, {"WPT2",2} } },
|
||||||
|
}
|
||||||
|
},
|
||||||
|
{ // Intel GPUs
|
||||||
|
kDeviceTypeGPU, "Intel", {
|
||||||
|
{ "Intel(R) HD Graphics 530", { {"VW2",2}, {"WGS2",128}, {"WPT2",2} } },
|
||||||
|
{ "Intel(R) HD Graphics 5500 BroadWell U-Processor GT2", { {"VW2",1}, {"WGS2",32}, {"WPT2",2} } },
|
||||||
|
{ "Intel(R) HD Graphics Haswell Ultrabook GT2 Mobile", { {"VW2",2}, {"WGS2",128}, {"WPT2",2} } },
|
||||||
|
{ "Intel(R) HD Graphics Skylake ULT GT2", { {"VW2",1}, {"WGS2",64}, {"WPT2",1} } },
|
||||||
|
{ "Iris", { {"VW2",1}, {"WGS2",64}, {"WPT2",1} } },
|
||||||
|
{ "Iris Pro", { {"VW2",4}, {"WGS2",128}, {"WPT2",4} } },
|
||||||
|
{ "default", { {"VW2",1}, {"WGS2",64}, {"WPT2",1} } },
|
||||||
|
}
|
||||||
|
},
|
||||||
|
{ // Intel accelerators
|
||||||
|
kDeviceTypeAccelerator, "Intel", {
|
||||||
|
{ "Intel(R) Many Integrated Core Acceleration Card", { {"VW2",1}, {"WGS2",64}, {"WPT2",1} } },
|
||||||
|
{ "default", { {"VW2",1}, {"WGS2",64}, {"WPT2",1} } },
|
||||||
|
}
|
||||||
|
},
|
||||||
|
{ // NVIDIA GPUs
|
||||||
|
kDeviceTypeGPU, "NVIDIA", {
|
||||||
|
{ "GRID K520", { {"VW2",1}, {"WGS2",256}, {"WPT2",1} } },
|
||||||
|
{ "GeForce GTX 1070", { {"VW2",1}, {"WGS2",64}, {"WPT2",1} } },
|
||||||
|
{ "GeForce GTX 480", { {"VW2",1}, {"WGS2",64}, {"WPT2",1} } },
|
||||||
|
{ "GeForce GTX 670", { {"VW2",1}, {"WGS2",64}, {"WPT2",1} } },
|
||||||
|
{ "GeForce GTX 680", { {"VW2",1}, {"WGS2",64}, {"WPT2",1} } },
|
||||||
|
{ "GeForce GTX 750 Ti", { {"VW2",1}, {"WGS2",64}, {"WPT2",1} } },
|
||||||
|
{ "default", { {"VW2",1}, {"WGS2",64}, {"WPT2",1} } },
|
||||||
|
}
|
||||||
|
},
|
||||||
|
{ // Default
|
||||||
|
kDeviceTypeAll, "default", {
|
||||||
|
{ "default", { {"VW2",1}, {"WGS2",64}, {"WPT2",1} } },
|
||||||
|
}
|
||||||
|
},
|
||||||
|
}
|
||||||
|
};
|
||||||
|
|
||||||
|
// =================================================================================================
|
||||||
|
|
||||||
|
const Database::DatabaseEntry Database::XgemvFastDouble = {
|
||||||
|
"XgemvFast", Precision::kDouble, {
|
||||||
|
{ // AMD GPUs
|
||||||
|
kDeviceTypeGPU, "AMD", {
|
||||||
|
{ "AMD Radeon R9 M370X Compute Engine", { {"VW2",1}, {"WGS2",256}, {"WPT2",1} } },
|
||||||
|
{ "Hawaii", { {"VW2",1}, {"WGS2",64}, {"WPT2",1} } },
|
||||||
|
{ "Oland", { {"VW2",1}, {"WGS2",64}, {"WPT2",1} } },
|
||||||
|
{ "Pitcairn", { {"VW2",1}, {"WGS2",64}, {"WPT2",1} } },
|
||||||
|
{ "Tahiti", { {"VW2",1}, {"WGS2",64}, {"WPT2",1} } },
|
||||||
|
{ "default", { {"VW2",1}, {"WGS2",64}, {"WPT2",1} } },
|
||||||
|
}
|
||||||
|
},
|
||||||
|
{ // Intel CPUs
|
||||||
|
kDeviceTypeCPU, "Intel", {
|
||||||
|
{ "Intel(R) Core(TM) i5-6200U CPU @ 2.30GHz", { {"VW2",4}, {"WGS2",128}, {"WPT2",4} } },
|
||||||
|
{ "Intel(R) Core(TM) i7-3770 CPU @ 3.40GHz", { {"VW2",1}, {"WGS2",64}, {"WPT2",4} } },
|
||||||
|
{ "default", { {"VW2",1}, {"WGS2",64}, {"WPT2",4} } },
|
||||||
|
}
|
||||||
|
},
|
||||||
|
{ // Intel accelerators
|
||||||
|
kDeviceTypeAccelerator, "Intel", {
|
||||||
|
{ "Intel(R) Many Integrated Core Acceleration Card", { {"VW2",1}, {"WGS2",64}, {"WPT2",1} } },
|
||||||
|
{ "default", { {"VW2",1}, {"WGS2",64}, {"WPT2",1} } },
|
||||||
|
}
|
||||||
|
},
|
||||||
|
{ // NVIDIA GPUs
|
||||||
|
kDeviceTypeGPU, "NVIDIA", {
|
||||||
|
{ "GRID K520", { {"VW2",1}, {"WGS2",256}, {"WPT2",1} } },
|
||||||
|
{ "GeForce GTX 1070", { {"VW2",1}, {"WGS2",256}, {"WPT2",1} } },
|
||||||
|
{ "GeForce GTX 480", { {"VW2",1}, {"WGS2",64}, {"WPT2",1} } },
|
||||||
|
{ "GeForce GTX 670", { {"VW2",1}, {"WGS2",128}, {"WPT2",1} } },
|
||||||
|
{ "GeForce GTX 680", { {"VW2",1}, {"WGS2",128}, {"WPT2",1} } },
|
||||||
|
{ "GeForce GTX 750", { {"VW2",2}, {"WGS2",256}, {"WPT2",2} } },
|
||||||
|
{ "GeForce GTX 750 Ti", { {"VW2",1}, {"WGS2",256}, {"WPT2",1} } },
|
||||||
|
{ "GeForce GTX 980", { {"VW2",1}, {"WGS2",64}, {"WPT2",1} } },
|
||||||
|
{ "GeForce GTX TITAN", { {"VW2",1}, {"WGS2",256}, {"WPT2",1} } },
|
||||||
|
{ "GeForce GTX TITAN X", { {"VW2",1}, {"WGS2",128}, {"WPT2",1} } },
|
||||||
|
{ "Tesla K20m", { {"VW2",1}, {"WGS2",128}, {"WPT2",1} } },
|
||||||
|
{ "Tesla K40m", { {"VW2",1}, {"WGS2",256}, {"WPT2",1} } },
|
||||||
|
{ "default", { {"VW2",1}, {"WGS2",256}, {"WPT2",1} } },
|
||||||
|
}
|
||||||
|
},
|
||||||
|
{ // Default
|
||||||
|
kDeviceTypeAll, "default", {
|
||||||
|
{ "default", { {"VW2",1}, {"WGS2",64}, {"WPT2",1} } },
|
||||||
|
}
|
||||||
|
},
|
||||||
|
}
|
||||||
|
};
|
||||||
|
|
||||||
|
// =================================================================================================
|
||||||
|
|
||||||
|
const Database::DatabaseEntry Database::XgemvFastComplexDouble = {
|
||||||
|
"XgemvFast", Precision::kComplexDouble, {
|
||||||
|
{ // AMD GPUs
|
||||||
|
kDeviceTypeGPU, "AMD", {
|
||||||
|
{ "AMD Radeon R9 M370X Compute Engine", { {"VW2",1}, {"WGS2",256}, {"WPT2",1} } },
|
||||||
|
{ "Hawaii", { {"VW2",1}, {"WGS2",64}, {"WPT2",1} } },
|
||||||
|
{ "Oland", { {"VW2",1}, {"WGS2",256}, {"WPT2",1} } },
|
||||||
|
{ "Pitcairn", { {"VW2",1}, {"WGS2",64}, {"WPT2",1} } },
|
||||||
|
{ "Tahiti", { {"VW2",1}, {"WGS2",64}, {"WPT2",1} } },
|
||||||
|
{ "default", { {"VW2",1}, {"WGS2",64}, {"WPT2",1} } },
|
||||||
|
}
|
||||||
|
},
|
||||||
|
{ // Intel CPUs
|
||||||
|
kDeviceTypeCPU, "Intel", {
|
||||||
|
{ "Intel(R) Core(TM) i5-6200U CPU @ 2.30GHz", { {"VW2",2}, {"WGS2",64}, {"WPT2",4} } },
|
||||||
|
{ "Intel(R) Core(TM) i7-3770 CPU @ 3.40GHz", { {"VW2",4}, {"WGS2",64}, {"WPT2",4} } },
|
||||||
|
{ "default", { {"VW2",2}, {"WGS2",64}, {"WPT2",4} } },
|
||||||
|
}
|
||||||
|
},
|
||||||
|
{ // Intel accelerators
|
||||||
|
kDeviceTypeAccelerator, "Intel", {
|
||||||
|
{ "Intel(R) Many Integrated Core Acceleration Card", { {"VW2",1}, {"WGS2",64}, {"WPT2",1} } },
|
||||||
|
{ "default", { {"VW2",1}, {"WGS2",64}, {"WPT2",1} } },
|
||||||
|
}
|
||||||
|
},
|
||||||
|
{ // NVIDIA GPUs
|
||||||
|
kDeviceTypeGPU, "NVIDIA", {
|
||||||
|
{ "GRID K520", { {"VW2",1}, {"WGS2",128}, {"WPT2",1} } },
|
||||||
|
{ "GeForce GTX 480", { {"VW2",1}, {"WGS2",64}, {"WPT2",1} } },
|
||||||
|
{ "GeForce GTX 670", { {"VW2",1}, {"WGS2",64}, {"WPT2",1} } },
|
||||||
|
{ "default", { {"VW2",1}, {"WGS2",64}, {"WPT2",1} } },
|
||||||
|
}
|
||||||
|
},
|
||||||
|
{ // Default
|
||||||
|
kDeviceTypeAll, "default", {
|
||||||
|
{ "default", { {"VW2",1}, {"WGS2",64}, {"WPT2",1} } },
|
||||||
|
}
|
||||||
|
},
|
||||||
|
}
|
||||||
|
};
|
||||||
|
|
||||||
|
// =================================================================================================
|
||||||
|
} // namespace clblast
|
154
src/database/kernels/xgemv_fast_rot.hpp
Normal file
154
src/database/kernels/xgemv_fast_rot.hpp
Normal file
|
@ -0,0 +1,154 @@
|
||||||
|
|
||||||
|
// =================================================================================================
|
||||||
|
// This file is part of the CLBlast project. The project is licensed under Apache Version 2.0. This
|
||||||
|
// project loosely follows the Google C++ styleguide and uses a tab-size of two spaces and a max-
|
||||||
|
// width of 100 characters per line.
|
||||||
|
//
|
||||||
|
// Author(s):
|
||||||
|
// Database generator <database.py>
|
||||||
|
//
|
||||||
|
// This file populates the database with best-found tuning parameters for the 'Xgemv_Fast_Rot' kernels.
|
||||||
|
//
|
||||||
|
// =================================================================================================
|
||||||
|
|
||||||
|
namespace clblast {
|
||||||
|
// =================================================================================================
|
||||||
|
|
||||||
|
const Database::DatabaseEntry Database::XgemvFastRotHalf = {
|
||||||
|
"XgemvFastRot", Precision::kHalf, {
|
||||||
|
{ // Default
|
||||||
|
kDeviceTypeAll, "default", {
|
||||||
|
{ "default", { {"VW3",8}, {"WGS3",32}, {"WPT3",32} } },
|
||||||
|
}
|
||||||
|
},
|
||||||
|
}
|
||||||
|
};
|
||||||
|
|
||||||
|
// =================================================================================================
|
||||||
|
|
||||||
|
const Database::DatabaseEntry Database::XgemvFastRotSingle = {
|
||||||
|
"XgemvFastRot", Precision::kSingle, {
|
||||||
|
{ // AMD GPUs
|
||||||
|
kDeviceTypeGPU, "AMD", {
|
||||||
|
{ "AMD Radeon R9 M370X Compute Engine", { {"VW3",8}, {"WGS3",64}, {"WPT3",32} } },
|
||||||
|
{ "default", { {"VW3",8}, {"WGS3",64}, {"WPT3",32} } },
|
||||||
|
}
|
||||||
|
},
|
||||||
|
{ // Intel CPUs
|
||||||
|
kDeviceTypeCPU, "Intel", {
|
||||||
|
{ "Intel(R) Core(TM) i7-5930K CPU @ 3.50GHz", { {"VW3",8}, {"WGS3",16}, {"WPT3",8} } },
|
||||||
|
{ "default", { {"VW3",8}, {"WGS3",16}, {"WPT3",8} } },
|
||||||
|
}
|
||||||
|
},
|
||||||
|
{ // Intel GPUs
|
||||||
|
kDeviceTypeGPU, "Intel", {
|
||||||
|
{ "Intel(R) HD Graphics 5500 BroadWell U-Processor GT2", { {"VW3",8}, {"WGS3",64}, {"WPT3",32} } },
|
||||||
|
{ "Intel(R) HD Graphics Haswell Ultrabook GT2 Mobile", { {"VW3",4}, {"WGS3",64}, {"WPT3",16} } },
|
||||||
|
{ "Intel(R) HD Graphics Skylake ULT GT2", { {"VW3",4}, {"WGS3",128}, {"WPT3",16} } },
|
||||||
|
{ "Iris Pro", { {"VW3",4}, {"WGS3",32}, {"WPT3",16} } },
|
||||||
|
{ "default", { {"VW3",8}, {"WGS3",32}, {"WPT3",32} } },
|
||||||
|
}
|
||||||
|
},
|
||||||
|
{ // NVIDIA GPUs
|
||||||
|
kDeviceTypeGPU, "NVIDIA", {
|
||||||
|
{ "GeForce GTX TITAN", { {"VW3",1}, {"WGS3",16}, {"WPT3",16} } },
|
||||||
|
{ "default", { {"VW3",1}, {"WGS3",16}, {"WPT3",16} } },
|
||||||
|
}
|
||||||
|
},
|
||||||
|
{ // Default
|
||||||
|
kDeviceTypeAll, "default", {
|
||||||
|
{ "default", { {"VW3",8}, {"WGS3",32}, {"WPT3",32} } },
|
||||||
|
}
|
||||||
|
},
|
||||||
|
}
|
||||||
|
};
|
||||||
|
|
||||||
|
// =================================================================================================
|
||||||
|
|
||||||
|
const Database::DatabaseEntry Database::XgemvFastRotComplexSingle = {
|
||||||
|
"XgemvFastRot", Precision::kComplexSingle, {
|
||||||
|
{ // AMD GPUs
|
||||||
|
kDeviceTypeGPU, "AMD", {
|
||||||
|
{ "AMD Radeon R9 M370X Compute Engine", { {"VW3",8}, {"WGS3",16}, {"WPT3",16} } },
|
||||||
|
{ "default", { {"VW3",8}, {"WGS3",16}, {"WPT3",16} } },
|
||||||
|
}
|
||||||
|
},
|
||||||
|
{ // Intel CPUs
|
||||||
|
kDeviceTypeCPU, "Intel", {
|
||||||
|
{ "Intel(R) Core(TM) i7-5930K CPU @ 3.50GHz", { {"VW3",4}, {"WGS3",16}, {"WPT3",16} } },
|
||||||
|
{ "default", { {"VW3",4}, {"WGS3",16}, {"WPT3",16} } },
|
||||||
|
}
|
||||||
|
},
|
||||||
|
{ // Intel GPUs
|
||||||
|
kDeviceTypeGPU, "Intel", {
|
||||||
|
{ "Intel(R) HD Graphics 5500 BroadWell U-Processor GT2", { {"VW3",2}, {"WGS3",16}, {"WPT3",16} } },
|
||||||
|
{ "Intel(R) HD Graphics Haswell Ultrabook GT2 Mobile", { {"VW3",4}, {"WGS3",128}, {"WPT3",8} } },
|
||||||
|
{ "Intel(R) HD Graphics Skylake ULT GT2", { {"VW3",2}, {"WGS3",32}, {"WPT3",16} } },
|
||||||
|
{ "Iris Pro", { {"VW3",4}, {"WGS3",16}, {"WPT3",16} } },
|
||||||
|
{ "default", { {"VW3",2}, {"WGS3",32}, {"WPT3",8} } },
|
||||||
|
}
|
||||||
|
},
|
||||||
|
{ // Default
|
||||||
|
kDeviceTypeAll, "default", {
|
||||||
|
{ "default", { {"VW3",2}, {"WGS3",32}, {"WPT3",16} } },
|
||||||
|
}
|
||||||
|
},
|
||||||
|
}
|
||||||
|
};
|
||||||
|
|
||||||
|
// =================================================================================================
|
||||||
|
|
||||||
|
const Database::DatabaseEntry Database::XgemvFastRotDouble = {
|
||||||
|
"XgemvFastRot", Precision::kDouble, {
|
||||||
|
{ // AMD GPUs
|
||||||
|
kDeviceTypeGPU, "AMD", {
|
||||||
|
{ "AMD Radeon R9 M370X Compute Engine", { {"VW3",4}, {"WGS3",16}, {"WPT3",16} } },
|
||||||
|
{ "default", { {"VW3",4}, {"WGS3",16}, {"WPT3",16} } },
|
||||||
|
}
|
||||||
|
},
|
||||||
|
{ // Intel CPUs
|
||||||
|
kDeviceTypeCPU, "Intel", {
|
||||||
|
{ "Intel(R) Core(TM) i7-5930K CPU @ 3.50GHz", { {"VW3",8}, {"WGS3",16}, {"WPT3",8} } },
|
||||||
|
{ "default", { {"VW3",8}, {"WGS3",16}, {"WPT3",8} } },
|
||||||
|
}
|
||||||
|
},
|
||||||
|
{ // NVIDIA GPUs
|
||||||
|
kDeviceTypeGPU, "NVIDIA", {
|
||||||
|
{ "GeForce GTX TITAN", { {"VW3",1}, {"WGS3",16}, {"WPT3",16} } },
|
||||||
|
{ "default", { {"VW3",1}, {"WGS3",16}, {"WPT3",16} } },
|
||||||
|
}
|
||||||
|
},
|
||||||
|
{ // Default
|
||||||
|
kDeviceTypeAll, "default", {
|
||||||
|
{ "default", { {"VW3",4}, {"WGS3",16}, {"WPT3",16} } },
|
||||||
|
}
|
||||||
|
},
|
||||||
|
}
|
||||||
|
};
|
||||||
|
|
||||||
|
// =================================================================================================
|
||||||
|
|
||||||
|
const Database::DatabaseEntry Database::XgemvFastRotComplexDouble = {
|
||||||
|
"XgemvFastRot", Precision::kComplexDouble, {
|
||||||
|
{ // AMD GPUs
|
||||||
|
kDeviceTypeGPU, "AMD", {
|
||||||
|
{ "AMD Radeon R9 M370X Compute Engine", { {"VW3",4}, {"WGS3",32}, {"WPT3",16} } },
|
||||||
|
{ "default", { {"VW3",4}, {"WGS3",32}, {"WPT3",16} } },
|
||||||
|
}
|
||||||
|
},
|
||||||
|
{ // Intel CPUs
|
||||||
|
kDeviceTypeCPU, "Intel", {
|
||||||
|
{ "Intel(R) Core(TM) i7-5930K CPU @ 3.50GHz", { {"VW3",8}, {"WGS3",16}, {"WPT3",16} } },
|
||||||
|
{ "default", { {"VW3",8}, {"WGS3",16}, {"WPT3",16} } },
|
||||||
|
}
|
||||||
|
},
|
||||||
|
{ // Default
|
||||||
|
kDeviceTypeAll, "default", {
|
||||||
|
{ "default", { {"VW3",8}, {"WGS3",32}, {"WPT3",16} } },
|
||||||
|
}
|
||||||
|
},
|
||||||
|
}
|
||||||
|
};
|
||||||
|
|
||||||
|
// =================================================================================================
|
||||||
|
} // namespace clblast
|
|
@ -18,6 +18,7 @@ const Database::DatabaseEntry Database::XgerHalf = {
|
||||||
"Xger", Precision::kHalf, {
|
"Xger", Precision::kHalf, {
|
||||||
{ // Intel GPUs
|
{ // Intel GPUs
|
||||||
kDeviceTypeGPU, "Intel", {
|
kDeviceTypeGPU, "Intel", {
|
||||||
|
{ "Intel(R) HD Graphics 5500 BroadWell U-Processor GT2", { {"WGS1",256}, {"WGS2",1}, {"WPT",2} } },
|
||||||
{ "Intel(R) HD Graphics Skylake ULT GT2", { {"WGS1",64}, {"WGS2",1}, {"WPT",1} } },
|
{ "Intel(R) HD Graphics Skylake ULT GT2", { {"WGS1",64}, {"WGS2",1}, {"WPT",1} } },
|
||||||
{ "default", { {"WGS1",64}, {"WGS2",1}, {"WPT",1} } },
|
{ "default", { {"WGS1",64}, {"WGS2",1}, {"WPT",1} } },
|
||||||
}
|
}
|
||||||
|
@ -38,9 +39,10 @@ const Database::DatabaseEntry Database::XgerSingle = {
|
||||||
kDeviceTypeGPU, "AMD", {
|
kDeviceTypeGPU, "AMD", {
|
||||||
{ "AMD Radeon R9 M370X Compute Engine", { {"WGS1",256}, {"WGS2",1}, {"WPT",1} } },
|
{ "AMD Radeon R9 M370X Compute Engine", { {"WGS1",256}, {"WGS2",1}, {"WPT",1} } },
|
||||||
{ "Hawaii", { {"WGS1",64}, {"WGS2",2}, {"WPT",1} } },
|
{ "Hawaii", { {"WGS1",64}, {"WGS2",2}, {"WPT",1} } },
|
||||||
|
{ "Oland", { {"WGS1",32}, {"WGS2",4}, {"WPT",2} } },
|
||||||
{ "Pitcairn", { {"WGS1",64}, {"WGS2",1}, {"WPT",1} } },
|
{ "Pitcairn", { {"WGS1",64}, {"WGS2",1}, {"WPT",1} } },
|
||||||
{ "Tahiti", { {"WGS1",256}, {"WGS2",1}, {"WPT",1} } },
|
{ "Tahiti", { {"WGS1",256}, {"WGS2",1}, {"WPT",1} } },
|
||||||
{ "default", { {"WGS1",64}, {"WGS2",1}, {"WPT",1} } },
|
{ "default", { {"WGS1",32}, {"WGS2",4}, {"WPT",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // ARM GPUs
|
{ // ARM GPUs
|
||||||
|
@ -53,29 +55,34 @@ const Database::DatabaseEntry Database::XgerSingle = {
|
||||||
kDeviceTypeCPU, "Intel", {
|
kDeviceTypeCPU, "Intel", {
|
||||||
{ "Intel(R) Core(TM) i5-6200U CPU @ 2.30GHz", { {"WGS1",128}, {"WGS2",2}, {"WPT",4} } },
|
{ "Intel(R) Core(TM) i5-6200U CPU @ 2.30GHz", { {"WGS1",128}, {"WGS2",2}, {"WPT",4} } },
|
||||||
{ "Intel(R) Core(TM) i7-5930K CPU @ 3.50GHz", { {"WGS1",128}, {"WGS2",1}, {"WPT",4} } },
|
{ "Intel(R) Core(TM) i7-5930K CPU @ 3.50GHz", { {"WGS1",128}, {"WGS2",1}, {"WPT",4} } },
|
||||||
{ "default", { {"WGS1",128}, {"WGS2",1}, {"WPT",4} } },
|
{ "default", { {"WGS1",128}, {"WGS2",8}, {"WPT",4} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Intel GPUs
|
{ // Intel GPUs
|
||||||
kDeviceTypeGPU, "Intel", {
|
kDeviceTypeGPU, "Intel", {
|
||||||
{ "Intel(R) HD Graphics Haswell Ultrabook GT2 Mobile", { {"WGS1",256}, {"WGS2",2}, {"WPT",2} } },
|
{ "Intel(R) HD Graphics 530", { {"WGS1",32}, {"WGS2",1}, {"WPT",2} } },
|
||||||
|
{ "Intel(R) HD Graphics 5500 BroadWell U-Processor GT2", { {"WGS1",256}, {"WGS2",2}, {"WPT",2} } },
|
||||||
|
{ "Intel(R) HD Graphics Haswell Ultrabook GT2 Mobile", { {"WGS1",128}, {"WGS2",1}, {"WPT",2} } },
|
||||||
{ "Intel(R) HD Graphics Skylake ULT GT2", { {"WGS1",8}, {"WGS2",8}, {"WPT",4} } },
|
{ "Intel(R) HD Graphics Skylake ULT GT2", { {"WGS1",8}, {"WGS2",8}, {"WPT",4} } },
|
||||||
{ "Iris Pro", { {"WGS1",64}, {"WGS2",1}, {"WPT",4} } },
|
{ "Iris Pro", { {"WGS1",64}, {"WGS2",1}, {"WPT",4} } },
|
||||||
{ "default", { {"WGS1",8}, {"WGS2",1}, {"WPT",2} } },
|
{ "default", { {"WGS1",32}, {"WGS2",4}, {"WPT",2} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // NVIDIA GPUs
|
{ // NVIDIA GPUs
|
||||||
kDeviceTypeGPU, "NVIDIA", {
|
kDeviceTypeGPU, "NVIDIA", {
|
||||||
{ "GRID K520", { {"WGS1",128}, {"WGS2",1}, {"WPT",2} } },
|
{ "GRID K520", { {"WGS1",128}, {"WGS2",1}, {"WPT",2} } },
|
||||||
|
{ "GeForce GTX 1070", { {"WGS1",512}, {"WGS2",1}, {"WPT",1} } },
|
||||||
{ "GeForce GTX 480", { {"WGS1",256}, {"WGS2",1}, {"WPT",4} } },
|
{ "GeForce GTX 480", { {"WGS1",256}, {"WGS2",1}, {"WPT",4} } },
|
||||||
|
{ "GeForce GTX 670", { {"WGS1",32}, {"WGS2",8}, {"WPT",2} } },
|
||||||
{ "GeForce GTX 680", { {"WGS1",128}, {"WGS2",1}, {"WPT",4} } },
|
{ "GeForce GTX 680", { {"WGS1",128}, {"WGS2",1}, {"WPT",4} } },
|
||||||
|
{ "GeForce GTX 750", { {"WGS1",64}, {"WGS2",16}, {"WPT",4} } },
|
||||||
{ "GeForce GTX TITAN", { {"WGS1",32}, {"WGS2",4}, {"WPT",2} } },
|
{ "GeForce GTX TITAN", { {"WGS1",32}, {"WGS2",4}, {"WPT",2} } },
|
||||||
{ "default", { {"WGS1",32}, {"WGS2",1}, {"WPT",2} } },
|
{ "default", { {"WGS1",256}, {"WGS2",1}, {"WPT",4} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Default
|
{ // Default
|
||||||
kDeviceTypeAll, "default", {
|
kDeviceTypeAll, "default", {
|
||||||
{ "default", { {"WGS1",8}, {"WGS2",1}, {"WPT",1} } },
|
{ "default", { {"WGS1",32}, {"WGS2",4}, {"WPT",2} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
}
|
}
|
||||||
|
@ -89,9 +96,10 @@ const Database::DatabaseEntry Database::XgerComplexSingle = {
|
||||||
kDeviceTypeGPU, "AMD", {
|
kDeviceTypeGPU, "AMD", {
|
||||||
{ "AMD Radeon R9 M370X Compute Engine", { {"WGS1",64}, {"WGS2",4}, {"WPT",1} } },
|
{ "AMD Radeon R9 M370X Compute Engine", { {"WGS1",64}, {"WGS2",4}, {"WPT",1} } },
|
||||||
{ "Hawaii", { {"WGS1",64}, {"WGS2",1}, {"WPT",2} } },
|
{ "Hawaii", { {"WGS1",64}, {"WGS2",1}, {"WPT",2} } },
|
||||||
|
{ "Oland", { {"WGS1",4}, {"WGS2",8}, {"WPT",1} } },
|
||||||
{ "Pitcairn", { {"WGS1",128}, {"WGS2",2}, {"WPT",1} } },
|
{ "Pitcairn", { {"WGS1",128}, {"WGS2",2}, {"WPT",1} } },
|
||||||
{ "Tahiti", { {"WGS1",64}, {"WGS2",2}, {"WPT",1} } },
|
{ "Tahiti", { {"WGS1",64}, {"WGS2",2}, {"WPT",1} } },
|
||||||
{ "default", { {"WGS1",64}, {"WGS2",1}, {"WPT",1} } },
|
{ "default", { {"WGS1",256}, {"WGS2",1}, {"WPT",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // ARM GPUs
|
{ // ARM GPUs
|
||||||
|
@ -104,29 +112,34 @@ const Database::DatabaseEntry Database::XgerComplexSingle = {
|
||||||
kDeviceTypeCPU, "Intel", {
|
kDeviceTypeCPU, "Intel", {
|
||||||
{ "Intel(R) Core(TM) i5-6200U CPU @ 2.30GHz", { {"WGS1",256}, {"WGS2",1}, {"WPT",4} } },
|
{ "Intel(R) Core(TM) i5-6200U CPU @ 2.30GHz", { {"WGS1",256}, {"WGS2",1}, {"WPT",4} } },
|
||||||
{ "Intel(R) Core(TM) i7-5930K CPU @ 3.50GHz", { {"WGS1",512}, {"WGS2",4}, {"WPT",2} } },
|
{ "Intel(R) Core(TM) i7-5930K CPU @ 3.50GHz", { {"WGS1",512}, {"WGS2",4}, {"WPT",2} } },
|
||||||
{ "default", { {"WGS1",256}, {"WGS2",1}, {"WPT",2} } },
|
{ "default", { {"WGS1",512}, {"WGS2",4}, {"WPT",2} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Intel GPUs
|
{ // Intel GPUs
|
||||||
kDeviceTypeGPU, "Intel", {
|
kDeviceTypeGPU, "Intel", {
|
||||||
{ "Intel(R) HD Graphics Haswell Ultrabook GT2 Mobile", { {"WGS1",128}, {"WGS2",4}, {"WPT",1} } },
|
{ "Intel(R) HD Graphics 530", { {"WGS1",32}, {"WGS2",1}, {"WPT",2} } },
|
||||||
|
{ "Intel(R) HD Graphics 5500 BroadWell U-Processor GT2", { {"WGS1",128}, {"WGS2",2}, {"WPT",1} } },
|
||||||
|
{ "Intel(R) HD Graphics Haswell Ultrabook GT2 Mobile", { {"WGS1",512}, {"WGS2",1}, {"WPT",1} } },
|
||||||
{ "Intel(R) HD Graphics Skylake ULT GT2", { {"WGS1",128}, {"WGS2",4}, {"WPT",2} } },
|
{ "Intel(R) HD Graphics Skylake ULT GT2", { {"WGS1",128}, {"WGS2",4}, {"WPT",2} } },
|
||||||
{ "Iris Pro", { {"WGS1",16}, {"WGS2",2}, {"WPT",4} } },
|
{ "Iris Pro", { {"WGS1",16}, {"WGS2",2}, {"WPT",4} } },
|
||||||
{ "default", { {"WGS1",16}, {"WGS2",2}, {"WPT",1} } },
|
{ "default", { {"WGS1",64}, {"WGS2",1}, {"WPT",2} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // NVIDIA GPUs
|
{ // NVIDIA GPUs
|
||||||
kDeviceTypeGPU, "NVIDIA", {
|
kDeviceTypeGPU, "NVIDIA", {
|
||||||
{ "GRID K520", { {"WGS1",64}, {"WGS2",4}, {"WPT",2} } },
|
{ "GRID K520", { {"WGS1",64}, {"WGS2",4}, {"WPT",2} } },
|
||||||
|
{ "GeForce GTX 1070", { {"WGS1",16}, {"WGS2",64}, {"WPT",2} } },
|
||||||
{ "GeForce GTX 480", { {"WGS1",128}, {"WGS2",2}, {"WPT",2} } },
|
{ "GeForce GTX 480", { {"WGS1",128}, {"WGS2",2}, {"WPT",2} } },
|
||||||
|
{ "GeForce GTX 670", { {"WGS1",16}, {"WGS2",32}, {"WPT",2} } },
|
||||||
{ "GeForce GTX 680", { {"WGS1",32}, {"WGS2",4}, {"WPT",2} } },
|
{ "GeForce GTX 680", { {"WGS1",32}, {"WGS2",4}, {"WPT",2} } },
|
||||||
|
{ "GeForce GTX 750", { {"WGS1",32}, {"WGS2",16}, {"WPT",4} } },
|
||||||
{ "GeForce GTX TITAN", { {"WGS1",16}, {"WGS2",16}, {"WPT",2} } },
|
{ "GeForce GTX TITAN", { {"WGS1",16}, {"WGS2",16}, {"WPT",2} } },
|
||||||
{ "default", { {"WGS1",16}, {"WGS2",2}, {"WPT",2} } },
|
{ "default", { {"WGS1",64}, {"WGS2",2}, {"WPT",2} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Default
|
{ // Default
|
||||||
kDeviceTypeAll, "default", {
|
kDeviceTypeAll, "default", {
|
||||||
{ "default", { {"WGS1",16}, {"WGS2",1}, {"WPT",1} } },
|
{ "default", { {"WGS1",64}, {"WGS2",4}, {"WPT",2} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
}
|
}
|
||||||
|
@ -140,9 +153,10 @@ const Database::DatabaseEntry Database::XgerDouble = {
|
||||||
kDeviceTypeGPU, "AMD", {
|
kDeviceTypeGPU, "AMD", {
|
||||||
{ "AMD Radeon R9 M370X Compute Engine", { {"WGS1",32}, {"WGS2",4}, {"WPT",1} } },
|
{ "AMD Radeon R9 M370X Compute Engine", { {"WGS1",32}, {"WGS2",4}, {"WPT",1} } },
|
||||||
{ "Hawaii", { {"WGS1",32}, {"WGS2",4}, {"WPT",2} } },
|
{ "Hawaii", { {"WGS1",32}, {"WGS2",4}, {"WPT",2} } },
|
||||||
|
{ "Oland", { {"WGS1",128}, {"WGS2",1}, {"WPT",2} } },
|
||||||
{ "Pitcairn", { {"WGS1",64}, {"WGS2",1}, {"WPT",1} } },
|
{ "Pitcairn", { {"WGS1",64}, {"WGS2",1}, {"WPT",1} } },
|
||||||
{ "Tahiti", { {"WGS1",64}, {"WGS2",2}, {"WPT",1} } },
|
{ "Tahiti", { {"WGS1",64}, {"WGS2",2}, {"WPT",1} } },
|
||||||
{ "default", { {"WGS1",32}, {"WGS2",1}, {"WPT",1} } },
|
{ "default", { {"WGS1",64}, {"WGS2",2}, {"WPT",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // ARM GPUs
|
{ // ARM GPUs
|
||||||
|
@ -155,21 +169,24 @@ const Database::DatabaseEntry Database::XgerDouble = {
|
||||||
kDeviceTypeCPU, "Intel", {
|
kDeviceTypeCPU, "Intel", {
|
||||||
{ "Intel(R) Core(TM) i5-6200U CPU @ 2.30GHz", { {"WGS1",512}, {"WGS2",16}, {"WPT",1} } },
|
{ "Intel(R) Core(TM) i5-6200U CPU @ 2.30GHz", { {"WGS1",512}, {"WGS2",16}, {"WPT",1} } },
|
||||||
{ "Intel(R) Core(TM) i7-5930K CPU @ 3.50GHz", { {"WGS1",512}, {"WGS2",8}, {"WPT",2} } },
|
{ "Intel(R) Core(TM) i7-5930K CPU @ 3.50GHz", { {"WGS1",512}, {"WGS2",8}, {"WPT",2} } },
|
||||||
{ "default", { {"WGS1",512}, {"WGS2",8}, {"WPT",1} } },
|
{ "default", { {"WGS1",512}, {"WGS2",8}, {"WPT",2} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // NVIDIA GPUs
|
{ // NVIDIA GPUs
|
||||||
kDeviceTypeGPU, "NVIDIA", {
|
kDeviceTypeGPU, "NVIDIA", {
|
||||||
{ "GRID K520", { {"WGS1",128}, {"WGS2",8}, {"WPT",2} } },
|
{ "GRID K520", { {"WGS1",128}, {"WGS2",8}, {"WPT",2} } },
|
||||||
|
{ "GeForce GTX 1070", { {"WGS1",32}, {"WGS2",8}, {"WPT",1} } },
|
||||||
{ "GeForce GTX 480", { {"WGS1",32}, {"WGS2",4}, {"WPT",2} } },
|
{ "GeForce GTX 480", { {"WGS1",32}, {"WGS2",4}, {"WPT",2} } },
|
||||||
|
{ "GeForce GTX 670", { {"WGS1",32}, {"WGS2",32}, {"WPT",2} } },
|
||||||
{ "GeForce GTX 680", { {"WGS1",128}, {"WGS2",4}, {"WPT",2} } },
|
{ "GeForce GTX 680", { {"WGS1",128}, {"WGS2",4}, {"WPT",2} } },
|
||||||
|
{ "GeForce GTX 750", { {"WGS1",256}, {"WGS2",2}, {"WPT",2} } },
|
||||||
{ "GeForce GTX TITAN", { {"WGS1",16}, {"WGS2",8}, {"WPT",2} } },
|
{ "GeForce GTX TITAN", { {"WGS1",16}, {"WGS2",8}, {"WPT",2} } },
|
||||||
{ "default", { {"WGS1",16}, {"WGS2",4}, {"WPT",2} } },
|
{ "default", { {"WGS1",256}, {"WGS2",2}, {"WPT",2} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Default
|
{ // Default
|
||||||
kDeviceTypeAll, "default", {
|
kDeviceTypeAll, "default", {
|
||||||
{ "default", { {"WGS1",16}, {"WGS2",1}, {"WPT",1} } },
|
{ "default", { {"WGS1",128}, {"WGS2",1}, {"WPT",2} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
}
|
}
|
||||||
|
@ -183,9 +200,10 @@ const Database::DatabaseEntry Database::XgerComplexDouble = {
|
||||||
kDeviceTypeGPU, "AMD", {
|
kDeviceTypeGPU, "AMD", {
|
||||||
{ "AMD Radeon R9 M370X Compute Engine", { {"WGS1",64}, {"WGS2",1}, {"WPT",1} } },
|
{ "AMD Radeon R9 M370X Compute Engine", { {"WGS1",64}, {"WGS2",1}, {"WPT",1} } },
|
||||||
{ "Hawaii", { {"WGS1",128}, {"WGS2",1}, {"WPT",1} } },
|
{ "Hawaii", { {"WGS1",128}, {"WGS2",1}, {"WPT",1} } },
|
||||||
|
{ "Oland", { {"WGS1",16}, {"WGS2",16}, {"WPT",2} } },
|
||||||
{ "Pitcairn", { {"WGS1",64}, {"WGS2",4}, {"WPT",1} } },
|
{ "Pitcairn", { {"WGS1",64}, {"WGS2",4}, {"WPT",1} } },
|
||||||
{ "Tahiti", { {"WGS1",32}, {"WGS2",4}, {"WPT",1} } },
|
{ "Tahiti", { {"WGS1",32}, {"WGS2",4}, {"WPT",1} } },
|
||||||
{ "default", { {"WGS1",32}, {"WGS2",1}, {"WPT",1} } },
|
{ "default", { {"WGS1",32}, {"WGS2",4}, {"WPT",1} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // ARM GPUs
|
{ // ARM GPUs
|
||||||
|
@ -204,15 +222,18 @@ const Database::DatabaseEntry Database::XgerComplexDouble = {
|
||||||
{ // NVIDIA GPUs
|
{ // NVIDIA GPUs
|
||||||
kDeviceTypeGPU, "NVIDIA", {
|
kDeviceTypeGPU, "NVIDIA", {
|
||||||
{ "GRID K520", { {"WGS1",16}, {"WGS2",8}, {"WPT",2} } },
|
{ "GRID K520", { {"WGS1",16}, {"WGS2",8}, {"WPT",2} } },
|
||||||
|
{ "GeForce GTX 1070", { {"WGS1",8}, {"WGS2",128}, {"WPT",1} } },
|
||||||
{ "GeForce GTX 480", { {"WGS1",64}, {"WGS2",2}, {"WPT",2} } },
|
{ "GeForce GTX 480", { {"WGS1",64}, {"WGS2",2}, {"WPT",2} } },
|
||||||
|
{ "GeForce GTX 670", { {"WGS1",8}, {"WGS2",16}, {"WPT",2} } },
|
||||||
{ "GeForce GTX 680", { {"WGS1",8}, {"WGS2",16}, {"WPT",1} } },
|
{ "GeForce GTX 680", { {"WGS1",8}, {"WGS2",16}, {"WPT",1} } },
|
||||||
|
{ "GeForce GTX 750", { {"WGS1",8}, {"WGS2",32}, {"WPT",4} } },
|
||||||
{ "GeForce GTX TITAN", { {"WGS1",32}, {"WGS2",4}, {"WPT",2} } },
|
{ "GeForce GTX TITAN", { {"WGS1",32}, {"WGS2",4}, {"WPT",2} } },
|
||||||
{ "default", { {"WGS1",8}, {"WGS2",2}, {"WPT",1} } },
|
{ "default", { {"WGS1",16}, {"WGS2",8}, {"WPT",2} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
{ // Default
|
{ // Default
|
||||||
kDeviceTypeAll, "default", {
|
kDeviceTypeAll, "default", {
|
||||||
{ "default", { {"WGS1",8}, {"WGS2",1}, {"WPT",1} } },
|
{ "default", { {"WGS1",64}, {"WGS2",2}, {"WPT",2} } },
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
}
|
}
|
||||||
|
|
|
@ -109,6 +109,16 @@ R"(
|
||||||
typedef real singlereal;
|
typedef real singlereal;
|
||||||
#endif
|
#endif
|
||||||
|
|
||||||
|
// Converts a 'real argument' value to a 'real' value as passed to the kernel. Normally there is no
|
||||||
|
// conversion, but half-precision is not supported as kernel argument so it is converted from float.
|
||||||
|
#if PRECISION == 16
|
||||||
|
typedef float real_arg;
|
||||||
|
#define GetRealArg(x) (half)x
|
||||||
|
#else
|
||||||
|
typedef real real_arg;
|
||||||
|
#define GetRealArg(x) x
|
||||||
|
#endif
|
||||||
|
|
||||||
// =================================================================================================
|
// =================================================================================================
|
||||||
|
|
||||||
// Don't use the non-IEEE754 compliant OpenCL built-in mad() instruction per default. For specific
|
// Don't use the non-IEEE754 compliant OpenCL built-in mad() instruction per default. For specific
|
||||||
|
@ -138,6 +148,13 @@ R"(
|
||||||
#define SetToOne(a) a = ONE
|
#define SetToOne(a) a = ONE
|
||||||
#endif
|
#endif
|
||||||
|
|
||||||
|
// Determines whether a variable is zero
|
||||||
|
#if PRECISION == 3232 || PRECISION == 6464
|
||||||
|
#define IsZero(a) ((a.x == ZERO) && (a.y == ZERO))
|
||||||
|
#else
|
||||||
|
#define IsZero(a) (a == ZERO)
|
||||||
|
#endif
|
||||||
|
|
||||||
// The absolute value (component-wise)
|
// The absolute value (component-wise)
|
||||||
#if PRECISION == 3232 || PRECISION == 6464
|
#if PRECISION == 3232 || PRECISION == 6464
|
||||||
#define AbsoluteValue(value) value.x = fabs(value.x); value.y = fabs(value.y)
|
#define AbsoluteValue(value) value.x = fabs(value.x); value.y = fabs(value.y)
|
||||||
|
|
|
@ -30,8 +30,8 @@ R"(
|
||||||
// =================================================================================================
|
// =================================================================================================
|
||||||
|
|
||||||
// The main reduction kernel, performing the loading and the majority of the operation
|
// The main reduction kernel, performing the loading and the majority of the operation
|
||||||
__attribute__((reqd_work_group_size(WGS1, 1, 1)))
|
__kernel __attribute__((reqd_work_group_size(WGS1, 1, 1)))
|
||||||
__kernel void Xamax(const int n,
|
void Xamax(const int n,
|
||||||
const __global real* restrict xgm, const int x_offset, const int x_inc,
|
const __global real* restrict xgm, const int x_offset, const int x_inc,
|
||||||
__global singlereal* maxgm, __global unsigned int* imaxgm) {
|
__global singlereal* maxgm, __global unsigned int* imaxgm) {
|
||||||
__local singlereal maxlm[WGS1];
|
__local singlereal maxlm[WGS1];
|
||||||
|
@ -95,8 +95,8 @@ __kernel void Xamax(const int n,
|
||||||
|
|
||||||
// The epilogue reduction kernel, performing the final bit of the operation. This kernel has to
|
// The epilogue reduction kernel, performing the final bit of the operation. This kernel has to
|
||||||
// be launched with a single workgroup only.
|
// be launched with a single workgroup only.
|
||||||
__attribute__((reqd_work_group_size(WGS2, 1, 1)))
|
__kernel __attribute__((reqd_work_group_size(WGS2, 1, 1)))
|
||||||
__kernel void XamaxEpilogue(const __global singlereal* restrict maxgm,
|
void XamaxEpilogue(const __global singlereal* restrict maxgm,
|
||||||
const __global unsigned int* restrict imaxgm,
|
const __global unsigned int* restrict imaxgm,
|
||||||
__global unsigned int* imax, const int imax_offset) {
|
__global unsigned int* imax, const int imax_offset) {
|
||||||
__local singlereal maxlm[WGS2];
|
__local singlereal maxlm[WGS2];
|
||||||
|
|
|
@ -30,8 +30,8 @@ R"(
|
||||||
// =================================================================================================
|
// =================================================================================================
|
||||||
|
|
||||||
// The main reduction kernel, performing the loading and the majority of the operation
|
// The main reduction kernel, performing the loading and the majority of the operation
|
||||||
__attribute__((reqd_work_group_size(WGS1, 1, 1)))
|
__kernel __attribute__((reqd_work_group_size(WGS1, 1, 1)))
|
||||||
__kernel void Xasum(const int n,
|
void Xasum(const int n,
|
||||||
const __global real* restrict xgm, const int x_offset, const int x_inc,
|
const __global real* restrict xgm, const int x_offset, const int x_inc,
|
||||||
__global real* output) {
|
__global real* output) {
|
||||||
__local real lm[WGS1];
|
__local real lm[WGS1];
|
||||||
|
@ -74,8 +74,8 @@ __kernel void Xasum(const int n,
|
||||||
|
|
||||||
// The epilogue reduction kernel, performing the final bit of the operation. This kernel has to
|
// The epilogue reduction kernel, performing the final bit of the operation. This kernel has to
|
||||||
// be launched with a single workgroup only.
|
// be launched with a single workgroup only.
|
||||||
__attribute__((reqd_work_group_size(WGS2, 1, 1)))
|
__kernel __attribute__((reqd_work_group_size(WGS2, 1, 1)))
|
||||||
__kernel void XasumEpilogue(const __global real* restrict input,
|
void XasumEpilogue(const __global real* restrict input,
|
||||||
__global real* asum, const int asum_offset) {
|
__global real* asum, const int asum_offset) {
|
||||||
__local real lm[WGS2];
|
__local real lm[WGS2];
|
||||||
const int lid = get_local_id(0);
|
const int lid = get_local_id(0);
|
||||||
|
|
|
@ -22,11 +22,11 @@ R"(
|
||||||
// =================================================================================================
|
// =================================================================================================
|
||||||
|
|
||||||
// Full version of the kernel with offsets and strided accesses
|
// Full version of the kernel with offsets and strided accesses
|
||||||
__attribute__((reqd_work_group_size(WGS, 1, 1)))
|
__kernel __attribute__((reqd_work_group_size(WGS, 1, 1)))
|
||||||
__kernel void Xaxpy(const int n, const __constant real* restrict arg_alpha,
|
void Xaxpy(const int n, const real_arg arg_alpha,
|
||||||
const __global real* restrict xgm, const int x_offset, const int x_inc,
|
const __global real* restrict xgm, const int x_offset, const int x_inc,
|
||||||
__global real* ygm, const int y_offset, const int y_inc) {
|
__global real* ygm, const int y_offset, const int y_inc) {
|
||||||
const real alpha = arg_alpha[0];
|
const real alpha = GetRealArg(arg_alpha);
|
||||||
|
|
||||||
// Loops over the work that needs to be done (allows for an arbitrary number of threads)
|
// Loops over the work that needs to be done (allows for an arbitrary number of threads)
|
||||||
#pragma unroll
|
#pragma unroll
|
||||||
|
@ -40,11 +40,11 @@ __kernel void Xaxpy(const int n, const __constant real* restrict arg_alpha,
|
||||||
|
|
||||||
// Faster version of the kernel without offsets and strided accesses. Also assumes that 'n' is
|
// Faster version of the kernel without offsets and strided accesses. Also assumes that 'n' is
|
||||||
// dividable by 'VW', 'WGS' and 'WPT'.
|
// dividable by 'VW', 'WGS' and 'WPT'.
|
||||||
__attribute__((reqd_work_group_size(WGS, 1, 1)))
|
__kernel __attribute__((reqd_work_group_size(WGS, 1, 1)))
|
||||||
__kernel void XaxpyFast(const int n, const __constant real* restrict arg_alpha,
|
void XaxpyFast(const int n, const real_arg arg_alpha,
|
||||||
const __global realV* restrict xgm,
|
const __global realV* restrict xgm,
|
||||||
__global realV* ygm) {
|
__global realV* ygm) {
|
||||||
const real alpha = arg_alpha[0];
|
const real alpha = GetRealArg(arg_alpha);
|
||||||
|
|
||||||
#pragma unroll
|
#pragma unroll
|
||||||
for (int w=0; w<WPT; ++w) {
|
for (int w=0; w<WPT; ++w) {
|
||||||
|
|
|
@ -22,8 +22,8 @@ R"(
|
||||||
// =================================================================================================
|
// =================================================================================================
|
||||||
|
|
||||||
// Full version of the kernel with offsets and strided accesses
|
// Full version of the kernel with offsets and strided accesses
|
||||||
__attribute__((reqd_work_group_size(WGS, 1, 1)))
|
__kernel __attribute__((reqd_work_group_size(WGS, 1, 1)))
|
||||||
__kernel void Xcopy(const int n,
|
void Xcopy(const int n,
|
||||||
const __global real* restrict xgm, const int x_offset, const int x_inc,
|
const __global real* restrict xgm, const int x_offset, const int x_inc,
|
||||||
__global real* ygm, const int y_offset, const int y_inc) {
|
__global real* ygm, const int y_offset, const int y_inc) {
|
||||||
|
|
||||||
|
@ -38,8 +38,8 @@ __kernel void Xcopy(const int n,
|
||||||
|
|
||||||
// Faster version of the kernel without offsets and strided accesses. Also assumes that 'n' is
|
// Faster version of the kernel without offsets and strided accesses. Also assumes that 'n' is
|
||||||
// dividable by 'VW', 'WGS' and 'WPT'.
|
// dividable by 'VW', 'WGS' and 'WPT'.
|
||||||
__attribute__((reqd_work_group_size(WGS, 1, 1)))
|
__kernel __attribute__((reqd_work_group_size(WGS, 1, 1)))
|
||||||
__kernel void XcopyFast(const int n,
|
void XcopyFast(const int n,
|
||||||
const __global realV* restrict xgm,
|
const __global realV* restrict xgm,
|
||||||
__global realV* ygm) {
|
__global realV* ygm) {
|
||||||
#pragma unroll
|
#pragma unroll
|
||||||
|
|
|
@ -30,8 +30,8 @@ R"(
|
||||||
// =================================================================================================
|
// =================================================================================================
|
||||||
|
|
||||||
// The main reduction kernel, performing the multiplication and the majority of the sum operation
|
// The main reduction kernel, performing the multiplication and the majority of the sum operation
|
||||||
__attribute__((reqd_work_group_size(WGS1, 1, 1)))
|
__kernel __attribute__((reqd_work_group_size(WGS1, 1, 1)))
|
||||||
__kernel void Xdot(const int n,
|
void Xdot(const int n,
|
||||||
const __global real* restrict xgm, const int x_offset, const int x_inc,
|
const __global real* restrict xgm, const int x_offset, const int x_inc,
|
||||||
const __global real* restrict ygm, const int y_offset, const int y_inc,
|
const __global real* restrict ygm, const int y_offset, const int y_inc,
|
||||||
__global real* output, const int do_conjugate) {
|
__global real* output, const int do_conjugate) {
|
||||||
|
@ -73,8 +73,8 @@ __kernel void Xdot(const int n,
|
||||||
|
|
||||||
// The epilogue reduction kernel, performing the final bit of the sum operation. This kernel has to
|
// The epilogue reduction kernel, performing the final bit of the sum operation. This kernel has to
|
||||||
// be launched with a single workgroup only.
|
// be launched with a single workgroup only.
|
||||||
__attribute__((reqd_work_group_size(WGS2, 1, 1)))
|
__kernel __attribute__((reqd_work_group_size(WGS2, 1, 1)))
|
||||||
__kernel void XdotEpilogue(const __global real* restrict input,
|
void XdotEpilogue(const __global real* restrict input,
|
||||||
__global real* dot, const int dot_offset) {
|
__global real* dot, const int dot_offset) {
|
||||||
__local real lm[WGS2];
|
__local real lm[WGS2];
|
||||||
const int lid = get_local_id(0);
|
const int lid = get_local_id(0);
|
||||||
|
|
|
@ -30,8 +30,8 @@ R"(
|
||||||
// =================================================================================================
|
// =================================================================================================
|
||||||
|
|
||||||
// The main reduction kernel, performing the multiplication and the majority of the operation
|
// The main reduction kernel, performing the multiplication and the majority of the operation
|
||||||
__attribute__((reqd_work_group_size(WGS1, 1, 1)))
|
__kernel __attribute__((reqd_work_group_size(WGS1, 1, 1)))
|
||||||
__kernel void Xnrm2(const int n,
|
void Xnrm2(const int n,
|
||||||
const __global real* restrict xgm, const int x_offset, const int x_inc,
|
const __global real* restrict xgm, const int x_offset, const int x_inc,
|
||||||
__global real* output) {
|
__global real* output) {
|
||||||
__local real lm[WGS1];
|
__local real lm[WGS1];
|
||||||
|
@ -72,8 +72,8 @@ __kernel void Xnrm2(const int n,
|
||||||
|
|
||||||
// The epilogue reduction kernel, performing the final bit of the operation. This kernel has to
|
// The epilogue reduction kernel, performing the final bit of the operation. This kernel has to
|
||||||
// be launched with a single workgroup only.
|
// be launched with a single workgroup only.
|
||||||
__attribute__((reqd_work_group_size(WGS2, 1, 1)))
|
__kernel __attribute__((reqd_work_group_size(WGS2, 1, 1)))
|
||||||
__kernel void Xnrm2Epilogue(const __global real* restrict input,
|
void Xnrm2Epilogue(const __global real* restrict input,
|
||||||
__global real* nrm2, const int nrm2_offset) {
|
__global real* nrm2, const int nrm2_offset) {
|
||||||
__local real lm[WGS2];
|
__local real lm[WGS2];
|
||||||
const int lid = get_local_id(0);
|
const int lid = get_local_id(0);
|
||||||
|
|
|
@ -22,9 +22,10 @@ R"(
|
||||||
// =================================================================================================
|
// =================================================================================================
|
||||||
|
|
||||||
// Full version of the kernel with offsets and strided accesses
|
// Full version of the kernel with offsets and strided accesses
|
||||||
__attribute__((reqd_work_group_size(WGS, 1, 1)))
|
__kernel __attribute__((reqd_work_group_size(WGS, 1, 1)))
|
||||||
__kernel void Xscal(const int n, const real alpha,
|
void Xscal(const int n, const real_arg arg_alpha,
|
||||||
__global real* xgm, const int x_offset, const int x_inc) {
|
__global real* xgm, const int x_offset, const int x_inc) {
|
||||||
|
const real alpha = GetRealArg(arg_alpha);
|
||||||
|
|
||||||
// Loops over the work that needs to be done (allows for an arbitrary number of threads)
|
// Loops over the work that needs to be done (allows for an arbitrary number of threads)
|
||||||
#pragma unroll
|
#pragma unroll
|
||||||
|
@ -40,9 +41,11 @@ __kernel void Xscal(const int n, const real alpha,
|
||||||
|
|
||||||
// Faster version of the kernel without offsets and strided accesses. Also assumes that 'n' is
|
// Faster version of the kernel without offsets and strided accesses. Also assumes that 'n' is
|
||||||
// dividable by 'VW', 'WGS' and 'WPT'.
|
// dividable by 'VW', 'WGS' and 'WPT'.
|
||||||
__attribute__((reqd_work_group_size(WGS, 1, 1)))
|
__kernel __attribute__((reqd_work_group_size(WGS, 1, 1)))
|
||||||
__kernel void XscalFast(const int n, const real alpha,
|
void XscalFast(const int n, const real_arg arg_alpha,
|
||||||
__global realV* xgm) {
|
__global realV* xgm) {
|
||||||
|
const real alpha = GetRealArg(arg_alpha);
|
||||||
|
|
||||||
#pragma unroll
|
#pragma unroll
|
||||||
for (int w=0; w<WPT; ++w) {
|
for (int w=0; w<WPT; ++w) {
|
||||||
const int id = w*get_global_size(0) + get_global_id(0);
|
const int id = w*get_global_size(0) + get_global_id(0);
|
||||||
|
|
|
@ -22,8 +22,8 @@ R"(
|
||||||
// =================================================================================================
|
// =================================================================================================
|
||||||
|
|
||||||
// Full version of the kernel with offsets and strided accesses
|
// Full version of the kernel with offsets and strided accesses
|
||||||
__attribute__((reqd_work_group_size(WGS, 1, 1)))
|
__kernel __attribute__((reqd_work_group_size(WGS, 1, 1)))
|
||||||
__kernel void Xswap(const int n,
|
void Xswap(const int n,
|
||||||
__global real* xgm, const int x_offset, const int x_inc,
|
__global real* xgm, const int x_offset, const int x_inc,
|
||||||
__global real* ygm, const int y_offset, const int y_inc) {
|
__global real* ygm, const int y_offset, const int y_inc) {
|
||||||
|
|
||||||
|
@ -40,8 +40,8 @@ __kernel void Xswap(const int n,
|
||||||
|
|
||||||
// Faster version of the kernel without offsets and strided accesses. Also assumes that 'n' is
|
// Faster version of the kernel without offsets and strided accesses. Also assumes that 'n' is
|
||||||
// dividable by 'VW', 'WGS' and 'WPT'.
|
// dividable by 'VW', 'WGS' and 'WPT'.
|
||||||
__attribute__((reqd_work_group_size(WGS, 1, 1)))
|
__kernel __attribute__((reqd_work_group_size(WGS, 1, 1)))
|
||||||
__kernel void XswapFast(const int n,
|
void XswapFast(const int n,
|
||||||
__global realV* xgm,
|
__global realV* xgm,
|
||||||
__global realV* ygm) {
|
__global realV* ygm) {
|
||||||
#pragma unroll
|
#pragma unroll
|
||||||
|
|
|
@ -210,18 +210,18 @@ inline real LoadMatrixA(const __global real* restrict agm, const int x, const in
|
||||||
// =================================================================================================
|
// =================================================================================================
|
||||||
|
|
||||||
// Full version of the kernel
|
// Full version of the kernel
|
||||||
__attribute__((reqd_work_group_size(WGS1, 1, 1)))
|
__kernel __attribute__((reqd_work_group_size(WGS1, 1, 1)))
|
||||||
__kernel void Xgemv(const int m, const int n,
|
void Xgemv(const int m, const int n,
|
||||||
const __constant real* restrict arg_alpha,
|
const real_arg arg_alpha,
|
||||||
const __constant real* restrict arg_beta,
|
const real_arg arg_beta,
|
||||||
const int a_rotated,
|
const int a_rotated,
|
||||||
const __global real* restrict agm, const int a_offset, const int a_ld,
|
const __global real* restrict agm, const int a_offset, const int a_ld,
|
||||||
const __global real* restrict xgm, const int x_offset, const int x_inc,
|
const __global real* restrict xgm, const int x_offset, const int x_inc,
|
||||||
__global real* ygm, const int y_offset, const int y_inc,
|
__global real* ygm, const int y_offset, const int y_inc,
|
||||||
const int do_conjugate, const int parameter,
|
const int do_conjugate, const int parameter,
|
||||||
const int kl, const int ku) {
|
const int kl, const int ku) {
|
||||||
const real alpha = arg_alpha[0];
|
const real alpha = GetRealArg(arg_alpha);
|
||||||
const real beta = arg_beta[0];
|
const real beta = GetRealArg(arg_beta);
|
||||||
|
|
||||||
// Local memory for the vector X
|
// Local memory for the vector X
|
||||||
__local real xlm[WGS1];
|
__local real xlm[WGS1];
|
||||||
|
|
|
@ -38,7 +38,7 @@ R"(
|
||||||
#define WGS3 64 // The local work-group size
|
#define WGS3 64 // The local work-group size
|
||||||
#endif
|
#endif
|
||||||
#ifndef WPT3
|
#ifndef WPT3
|
||||||
#define WPT3 1 // The amount of work-per-thread
|
#define WPT3 1 // The tile-size
|
||||||
#endif
|
#endif
|
||||||
#ifndef VW3
|
#ifndef VW3
|
||||||
#define VW3 1 // Vector width of matrix A loads
|
#define VW3 1 // Vector width of matrix A loads
|
||||||
|
@ -74,18 +74,12 @@ R"(
|
||||||
|
|
||||||
// =================================================================================================
|
// =================================================================================================
|
||||||
|
|
||||||
// Loads a vector input value (1/2)
|
// Loads a vector input value
|
||||||
inline realVF LoadMatrixAVF(const __global realVF* restrict agm, const int x, const int y,
|
inline realVF LoadMatrixAVF(const __global realVF* restrict agm, const int x, const int y,
|
||||||
const int a_ld) {
|
const int a_ld) {
|
||||||
return agm[a_ld*y + x];
|
return agm[a_ld*y + x];
|
||||||
}
|
}
|
||||||
|
|
||||||
// Loads a vector input value (2/2): as before, but different data-type
|
|
||||||
inline realVFR LoadMatrixAVFR(const __global realVFR* restrict agm, const int x, const int y,
|
|
||||||
const int a_ld) {
|
|
||||||
return agm[a_ld*y + x];
|
|
||||||
}
|
|
||||||
|
|
||||||
// =================================================================================================
|
// =================================================================================================
|
||||||
|
|
||||||
// Faster version of the kernel, assuming that:
|
// Faster version of the kernel, assuming that:
|
||||||
|
@ -94,23 +88,23 @@ inline realVFR LoadMatrixAVFR(const __global realVFR* restrict agm, const int x,
|
||||||
// --> 'a_ld' is a multiple of VW2
|
// --> 'a_ld' is a multiple of VW2
|
||||||
// --> 'a_rotated' is 0
|
// --> 'a_rotated' is 0
|
||||||
// --> 'do_conjugate' is 0
|
// --> 'do_conjugate' is 0
|
||||||
__attribute__((reqd_work_group_size(WGS2, 1, 1)))
|
__kernel __attribute__((reqd_work_group_size(WGS2, 1, 1)))
|
||||||
__kernel void XgemvFast(const int m, const int n,
|
void XgemvFast(const int m, const int n,
|
||||||
const __constant real* restrict arg_alpha,
|
const real_arg arg_alpha,
|
||||||
const __constant real* restrict arg_beta,
|
const real_arg arg_beta,
|
||||||
const int a_rotated,
|
const int a_rotated,
|
||||||
const __global realVF* restrict agm, const int a_offset, const int a_ld,
|
const __global realVF* restrict agm, const int a_offset, const int a_ld,
|
||||||
const __global real* restrict xgm, const int x_offset, const int x_inc,
|
const __global real* restrict xgm, const int x_offset, const int x_inc,
|
||||||
__global real* ygm, const int y_offset, const int y_inc,
|
__global real* ygm, const int y_offset, const int y_inc,
|
||||||
const int do_conjugate, const int parameter,
|
const int do_conjugate, const int parameter,
|
||||||
const int kl, const int ku) {
|
const int kl_unused, const int ku_unused) {
|
||||||
const real alpha = arg_alpha[0];
|
const real alpha = GetRealArg(arg_alpha);
|
||||||
const real beta = arg_beta[0];
|
const real beta = GetRealArg(arg_beta);
|
||||||
|
|
||||||
// Local memory for the vector X
|
// Local memory for the vector X
|
||||||
__local real xlm[WGS2];
|
__local real xlm[WGS2];
|
||||||
|
|
||||||
// Initializes the accumulation register
|
// Initializes the accumulation registers
|
||||||
real acc[WPT2];
|
real acc[WPT2];
|
||||||
#pragma unroll
|
#pragma unroll
|
||||||
for (int w=0; w<WPT2; ++w) {
|
for (int w=0; w<WPT2; ++w) {
|
||||||
|
@ -134,7 +128,7 @@ __kernel void XgemvFast(const int m, const int n,
|
||||||
#pragma unroll
|
#pragma unroll
|
||||||
for (int w=0; w<WPT2/VW2; ++w) {
|
for (int w=0; w<WPT2/VW2; ++w) {
|
||||||
const int gid = (WPT2/VW2)*get_global_id(0) + w;
|
const int gid = (WPT2/VW2)*get_global_id(0) + w;
|
||||||
realVF avec = LoadMatrixAVF(agm, gid, k, a_ld/VW2);
|
realVF avec = agm[(a_ld/VW2)*k + gid];
|
||||||
#if VW2 == 1
|
#if VW2 == 1
|
||||||
MultiplyAdd(acc[VW2*w+0], xlm[kl], avec);
|
MultiplyAdd(acc[VW2*w+0], xlm[kl], avec);
|
||||||
#elif VW2 == 2
|
#elif VW2 == 2
|
||||||
|
@ -196,84 +190,96 @@ __kernel void XgemvFast(const int m, const int n,
|
||||||
// --> 'a_ld' is a multiple of VW3
|
// --> 'a_ld' is a multiple of VW3
|
||||||
// --> 'a_rotated' is 1
|
// --> 'a_rotated' is 1
|
||||||
// --> 'do_conjugate' is 0
|
// --> 'do_conjugate' is 0
|
||||||
__attribute__((reqd_work_group_size(WGS3, 1, 1)))
|
__kernel __attribute__((reqd_work_group_size(WGS3, 1, 1)))
|
||||||
__kernel void XgemvFastRot(const int m, const int n,
|
void XgemvFastRot(const int m, const int n,
|
||||||
const __constant real* restrict arg_alpha,
|
const real_arg arg_alpha,
|
||||||
const __constant real* restrict arg_beta,
|
const real_arg arg_beta,
|
||||||
const int a_rotated,
|
const int a_rotated,
|
||||||
const __global realVFR* restrict agm, const int a_offset, const int a_ld,
|
const __global realVFR* restrict agm, const int a_offset, const int a_ld,
|
||||||
const __global real* restrict xgm, const int x_offset, const int x_inc,
|
const __global real* restrict xgm, const int x_offset, const int x_inc,
|
||||||
__global real* ygm, const int y_offset, const int y_inc,
|
__global real* ygm, const int y_offset, const int y_inc,
|
||||||
const int do_conjugate, const int parameter,
|
const int do_conjugate, const int parameter,
|
||||||
const int kl, const int ku) {
|
const int kl_unused, const int ku_unused) {
|
||||||
const real alpha = arg_alpha[0];
|
const real alpha = GetRealArg(arg_alpha);
|
||||||
const real beta = arg_beta[0];
|
const real beta = GetRealArg(arg_beta);
|
||||||
|
|
||||||
|
// Local memory to store a tile of the matrix (for coalescing)
|
||||||
|
__local real tile[WPT3][WGS3];
|
||||||
|
const int lid = get_local_id(0);
|
||||||
|
const int lid_mod = lid % (WPT3/VW3);
|
||||||
|
const int lid_div = lid / (WPT3/VW3);
|
||||||
|
|
||||||
// Local memory for the vector X
|
// Local memory for the vector X
|
||||||
__local real xlm[WGS3];
|
__local real xlm[WPT3];
|
||||||
|
|
||||||
// Initializes the accumulation register
|
// Initializes the accumulation register
|
||||||
real acc[WPT3];
|
real acc;
|
||||||
#pragma unroll
|
SetToZero(acc);
|
||||||
for (int w=0; w<WPT3; ++w) {
|
|
||||||
SetToZero(acc[w]);
|
|
||||||
}
|
|
||||||
|
|
||||||
// Loops over work-group sized portions of the work
|
// Loops over tile-sized portions of the work
|
||||||
for (int kwg=0; kwg<n; kwg+=WGS3) {
|
for (int kwg=0; kwg<n; kwg+=WPT3) {
|
||||||
|
|
||||||
// Loads the vector X into local memory
|
// Loads the vector X into local memory
|
||||||
const int lid = get_local_id(0);
|
if (lid < WPT3) {
|
||||||
xlm[lid] = xgm[(kwg + lid) * x_inc + x_offset];
|
xlm[lid] = xgm[(kwg + lid) * x_inc + x_offset];
|
||||||
|
}
|
||||||
|
|
||||||
|
// Loads the matrix A into local memory
|
||||||
|
#pragma unroll
|
||||||
|
for (int kl=0; kl<WPT3/VW3; ++kl) {
|
||||||
|
const int x = (kwg/VW3) + lid_mod;
|
||||||
|
const int y = get_group_id(0) * WGS3 + lid_div * (WPT3/VW3) + kl;
|
||||||
|
realVFR avec = agm[(a_ld/VW3) * y + x];
|
||||||
|
#if VW3 == 1
|
||||||
|
tile[kl*VW3 + 0][lid] = avec;
|
||||||
|
#elif VW3 == 2
|
||||||
|
tile[kl*VW3 + 0][lid] = avec.x;
|
||||||
|
tile[kl*VW3 + 1][lid] = avec.y;
|
||||||
|
#elif VW3 == 4
|
||||||
|
tile[kl*VW3 + 0][lid] = avec.x;
|
||||||
|
tile[kl*VW3 + 1][lid] = avec.y;
|
||||||
|
tile[kl*VW3 + 2][lid] = avec.z;
|
||||||
|
tile[kl*VW3 + 3][lid] = avec.w;
|
||||||
|
#elif VW3 == 8
|
||||||
|
tile[kl*VW3 + 0][lid] = avec.s0;
|
||||||
|
tile[kl*VW3 + 1][lid] = avec.s1;
|
||||||
|
tile[kl*VW3 + 2][lid] = avec.s2;
|
||||||
|
tile[kl*VW3 + 3][lid] = avec.s3;
|
||||||
|
tile[kl*VW3 + 4][lid] = avec.s4;
|
||||||
|
tile[kl*VW3 + 5][lid] = avec.s5;
|
||||||
|
tile[kl*VW3 + 6][lid] = avec.s6;
|
||||||
|
tile[kl*VW3 + 7][lid] = avec.s7;
|
||||||
|
#elif VW3 == 16
|
||||||
|
tile[kl*VW3 + 0][lid] = avec.s0;
|
||||||
|
tile[kl*VW3 + 1][lid] = avec.s1;
|
||||||
|
tile[kl*VW3 + 2][lid] = avec.s2;
|
||||||
|
tile[kl*VW3 + 3][lid] = avec.s3;
|
||||||
|
tile[kl*VW3 + 4][lid] = avec.s4;
|
||||||
|
tile[kl*VW3 + 5][lid] = avec.s5;
|
||||||
|
tile[kl*VW3 + 6][lid] = avec.s6;
|
||||||
|
tile[kl*VW3 + 7][lid] = avec.s7;
|
||||||
|
tile[kl*VW3 + 8][lid] = avec.s8;
|
||||||
|
tile[kl*VW3 + 9][lid] = avec.s9;
|
||||||
|
tile[kl*VW3 + 10][lid] = avec.sA;
|
||||||
|
tile[kl*VW3 + 11][lid] = avec.sB;
|
||||||
|
tile[kl*VW3 + 12][lid] = avec.sC;
|
||||||
|
tile[kl*VW3 + 13][lid] = avec.sD;
|
||||||
|
tile[kl*VW3 + 14][lid] = avec.sE;
|
||||||
|
tile[kl*VW3 + 15][lid] = avec.sF;
|
||||||
|
#endif
|
||||||
|
}
|
||||||
|
|
||||||
// Synchronizes all threads in a workgroup
|
// Synchronizes all threads in a workgroup
|
||||||
barrier(CLK_LOCAL_MEM_FENCE);
|
barrier(CLK_LOCAL_MEM_FENCE);
|
||||||
|
|
||||||
// The multiply-add function (rotated)
|
// The multiply-add function (rotated)
|
||||||
#pragma unroll
|
#pragma unroll
|
||||||
for (int kl=0; kl<WGS3/VW3; ++kl) {
|
for (int kl=0; kl<WPT3/VW3; ++kl) {
|
||||||
const int k = (kwg/VW3) + kl;
|
|
||||||
#pragma unroll
|
#pragma unroll
|
||||||
for (int w=0; w<WPT3; ++w) {
|
for (int v=0; v<VW3; ++v) {
|
||||||
const int gid = WPT3*get_global_id(0) + w;
|
real aval = tile[lid_mod*VW3 + v][lid_div * (WPT3/VW3) + kl];
|
||||||
realVFR avec = LoadMatrixAVFR(agm, k, gid, a_ld/VW3);
|
real xval = xlm[kl*VW3 + v];
|
||||||
#if VW3 == 1
|
MultiplyAdd(acc, xval, aval);
|
||||||
MultiplyAdd(acc[w], xlm[VW3*kl+0], avec);
|
|
||||||
#elif VW3 == 2
|
|
||||||
MultiplyAdd(acc[w], xlm[VW3*kl+0], avec.x);
|
|
||||||
MultiplyAdd(acc[w], xlm[VW3*kl+1], avec.y);
|
|
||||||
#elif VW3 == 4
|
|
||||||
MultiplyAdd(acc[w], xlm[VW3*kl+0], avec.x);
|
|
||||||
MultiplyAdd(acc[w], xlm[VW3*kl+1], avec.y);
|
|
||||||
MultiplyAdd(acc[w], xlm[VW3*kl+2], avec.z);
|
|
||||||
MultiplyAdd(acc[w], xlm[VW3*kl+3], avec.w);
|
|
||||||
#elif VW3 == 8
|
|
||||||
MultiplyAdd(acc[w], xlm[VW3*kl+0], avec.s0);
|
|
||||||
MultiplyAdd(acc[w], xlm[VW3*kl+1], avec.s1);
|
|
||||||
MultiplyAdd(acc[w], xlm[VW3*kl+2], avec.s2);
|
|
||||||
MultiplyAdd(acc[w], xlm[VW3*kl+3], avec.s3);
|
|
||||||
MultiplyAdd(acc[w], xlm[VW3*kl+4], avec.s4);
|
|
||||||
MultiplyAdd(acc[w], xlm[VW3*kl+5], avec.s5);
|
|
||||||
MultiplyAdd(acc[w], xlm[VW3*kl+6], avec.s6);
|
|
||||||
MultiplyAdd(acc[w], xlm[VW3*kl+7], avec.s7);
|
|
||||||
#elif VW3 == 16
|
|
||||||
MultiplyAdd(acc[w], xlm[VW3*kl+0], avec.s0);
|
|
||||||
MultiplyAdd(acc[w], xlm[VW3*kl+1], avec.s1);
|
|
||||||
MultiplyAdd(acc[w], xlm[VW3*kl+2], avec.s2);
|
|
||||||
MultiplyAdd(acc[w], xlm[VW3*kl+3], avec.s3);
|
|
||||||
MultiplyAdd(acc[w], xlm[VW3*kl+4], avec.s4);
|
|
||||||
MultiplyAdd(acc[w], xlm[VW3*kl+5], avec.s5);
|
|
||||||
MultiplyAdd(acc[w], xlm[VW3*kl+6], avec.s6);
|
|
||||||
MultiplyAdd(acc[w], xlm[VW3*kl+7], avec.s7);
|
|
||||||
MultiplyAdd(acc[w], xlm[VW3*kl+8], avec.s8);
|
|
||||||
MultiplyAdd(acc[w], xlm[VW3*kl+9], avec.s9);
|
|
||||||
MultiplyAdd(acc[w], xlm[VW3*kl+10], avec.sA);
|
|
||||||
MultiplyAdd(acc[w], xlm[VW3*kl+11], avec.sB);
|
|
||||||
MultiplyAdd(acc[w], xlm[VW3*kl+12], avec.sC);
|
|
||||||
MultiplyAdd(acc[w], xlm[VW3*kl+13], avec.sD);
|
|
||||||
MultiplyAdd(acc[w], xlm[VW3*kl+14], avec.sE);
|
|
||||||
MultiplyAdd(acc[w], xlm[VW3*kl+15], avec.sF);
|
|
||||||
#endif
|
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
|
|
||||||
|
@ -282,12 +288,9 @@ __kernel void XgemvFastRot(const int m, const int n,
|
||||||
}
|
}
|
||||||
|
|
||||||
// Stores the final result
|
// Stores the final result
|
||||||
#pragma unroll
|
const int gid = get_global_id(0);
|
||||||
for (int w=0; w<WPT3; ++w) {
|
|
||||||
const int gid = WPT3*get_global_id(0) + w;
|
|
||||||
real yval = ygm[gid * y_inc + y_offset];
|
real yval = ygm[gid * y_inc + y_offset];
|
||||||
AXPBY(ygm[gid*y_inc + y_offset], alpha, acc[w], beta, yval);
|
AXPBY(ygm[gid * y_inc + y_offset], alpha, acc, beta, yval);
|
||||||
}
|
|
||||||
}
|
}
|
||||||
|
|
||||||
// =================================================================================================
|
// =================================================================================================
|
||||||
|
|
|
@ -18,14 +18,14 @@ R"(
|
||||||
// =================================================================================================
|
// =================================================================================================
|
||||||
|
|
||||||
// Regular version of the rank-1 matrix update kernel (GER, GERU, GERC)
|
// Regular version of the rank-1 matrix update kernel (GER, GERU, GERC)
|
||||||
__attribute__((reqd_work_group_size(WGS1, WGS2, 1)))
|
__kernel __attribute__((reqd_work_group_size(WGS1, WGS2, 1)))
|
||||||
__kernel void Xger(const int max1, const int max2,
|
void Xger(const int max1, const int max2,
|
||||||
const __constant real* restrict arg_alpha,
|
const real_arg arg_alpha,
|
||||||
const __global real* restrict xgm, const int x_offset, const int x_inc,
|
const __global real* restrict xgm, const int x_offset, const int x_inc,
|
||||||
const __global real* ygm, const int y_offset, const int y_inc,
|
const __global real* ygm, const int y_offset, const int y_inc,
|
||||||
__global real* restrict agm, const int a_offset, const int a_ld,
|
__global real* restrict agm, const int a_offset, const int a_ld,
|
||||||
const int is_rowmajor) {
|
const int is_rowmajor) {
|
||||||
const real alpha = arg_alpha[0];
|
const real alpha = GetRealArg(arg_alpha);
|
||||||
|
|
||||||
// Register storage for X and Y
|
// Register storage for X and Y
|
||||||
real xvalues[WPT];
|
real xvalues[WPT];
|
||||||
|
|
|
@ -18,13 +18,13 @@ R"(
|
||||||
// =================================================================================================
|
// =================================================================================================
|
||||||
|
|
||||||
// Symmetric version of the rank-1 matrix update kernel (HER, HPR, SYR, SPR)
|
// Symmetric version of the rank-1 matrix update kernel (HER, HPR, SYR, SPR)
|
||||||
__attribute__((reqd_work_group_size(WGS1, WGS2, 1)))
|
__kernel __attribute__((reqd_work_group_size(WGS1, WGS2, 1)))
|
||||||
__kernel void Xher(const int n,
|
void Xher(const int n,
|
||||||
const __constant real* restrict arg_alpha,
|
const real_arg arg_alpha,
|
||||||
const __global real* restrict xgm, const int x_offset, const int x_inc,
|
const __global real* restrict xgm, const int x_offset, const int x_inc,
|
||||||
__global real* restrict agm, const int a_offset, const int a_ld,
|
__global real* restrict agm, const int a_offset, const int a_ld,
|
||||||
const int is_upper, const int is_rowmajor) {
|
const int is_upper, const int is_rowmajor) {
|
||||||
const real alpha = arg_alpha[0];
|
const real alpha = GetRealArg(arg_alpha);
|
||||||
|
|
||||||
// Register storage for X and XT
|
// Register storage for X and XT
|
||||||
real xvalues[WPT];
|
real xvalues[WPT];
|
||||||
|
|
|
@ -18,14 +18,14 @@ R"(
|
||||||
// =================================================================================================
|
// =================================================================================================
|
||||||
|
|
||||||
// Symmetric version of the rank-2 matrix update kernel (HER2, HPR2, SYR2, SPR2)
|
// Symmetric version of the rank-2 matrix update kernel (HER2, HPR2, SYR2, SPR2)
|
||||||
__attribute__((reqd_work_group_size(WGS1, WGS2, 1)))
|
__kernel __attribute__((reqd_work_group_size(WGS1, WGS2, 1)))
|
||||||
__kernel void Xher2(const int n,
|
void Xher2(const int n,
|
||||||
const __constant real* restrict arg_alpha,
|
const real_arg arg_alpha,
|
||||||
const __global real* restrict xgm, const int x_offset, const int x_inc,
|
const __global real* restrict xgm, const int x_offset, const int x_inc,
|
||||||
const __global real* restrict ygm, const int y_offset, const int y_inc,
|
const __global real* restrict ygm, const int y_offset, const int y_inc,
|
||||||
__global real* restrict agm, const int a_offset, const int a_ld,
|
__global real* restrict agm, const int a_offset, const int a_ld,
|
||||||
const int is_upper, const int is_rowmajor) {
|
const int is_upper, const int is_rowmajor) {
|
||||||
const real alpha = arg_alpha[0];
|
const real alpha = GetRealArg(arg_alpha);
|
||||||
|
|
||||||
// Register storage for X and Y
|
// Register storage for X and Y
|
||||||
real xvalues[WPT];
|
real xvalues[WPT];
|
||||||
|
|
|
@ -20,8 +20,8 @@ R"(
|
||||||
|
|
||||||
// Kernel to populate a squared hermitian matrix, given that the triangle which holds the data is
|
// Kernel to populate a squared hermitian matrix, given that the triangle which holds the data is
|
||||||
// stored as the lower-triangle of the input matrix. This uses the padding kernel's parameters.
|
// stored as the lower-triangle of the input matrix. This uses the padding kernel's parameters.
|
||||||
__attribute__((reqd_work_group_size(PAD_DIMX, PAD_DIMY, 1)))
|
__kernel __attribute__((reqd_work_group_size(PAD_DIMX, PAD_DIMY, 1)))
|
||||||
__kernel void HermLowerToSquared(const int src_dim,
|
void HermLowerToSquared(const int src_dim,
|
||||||
const int src_ld, const int src_offset,
|
const int src_ld, const int src_offset,
|
||||||
__global const real* restrict src,
|
__global const real* restrict src,
|
||||||
const int dest_dim,
|
const int dest_dim,
|
||||||
|
@ -59,8 +59,8 @@ __kernel void HermLowerToSquared(const int src_dim,
|
||||||
}
|
}
|
||||||
|
|
||||||
// Same as above, but now the matrix' data is stored in the upper-triangle
|
// Same as above, but now the matrix' data is stored in the upper-triangle
|
||||||
__attribute__((reqd_work_group_size(PAD_DIMX, PAD_DIMY, 1)))
|
__kernel __attribute__((reqd_work_group_size(PAD_DIMX, PAD_DIMY, 1)))
|
||||||
__kernel void HermUpperToSquared(const int src_dim,
|
void HermUpperToSquared(const int src_dim,
|
||||||
const int src_ld, const int src_offset,
|
const int src_ld, const int src_offset,
|
||||||
__global const real* restrict src,
|
__global const real* restrict src,
|
||||||
const int dest_dim,
|
const int dest_dim,
|
||||||
|
|
|
@ -20,8 +20,8 @@ R"(
|
||||||
|
|
||||||
// Kernel to populate a squared symmetric matrix, given that the triangle which holds the data is
|
// Kernel to populate a squared symmetric matrix, given that the triangle which holds the data is
|
||||||
// stored as the lower-triangle of the input matrix. This uses the padding kernel's parameters.
|
// stored as the lower-triangle of the input matrix. This uses the padding kernel's parameters.
|
||||||
__attribute__((reqd_work_group_size(PAD_DIMX, PAD_DIMY, 1)))
|
__kernel __attribute__((reqd_work_group_size(PAD_DIMX, PAD_DIMY, 1)))
|
||||||
__kernel void SymmLowerToSquared(const int src_dim,
|
void SymmLowerToSquared(const int src_dim,
|
||||||
const int src_ld, const int src_offset,
|
const int src_ld, const int src_offset,
|
||||||
__global const real* restrict src,
|
__global const real* restrict src,
|
||||||
const int dest_dim,
|
const int dest_dim,
|
||||||
|
@ -53,8 +53,8 @@ __kernel void SymmLowerToSquared(const int src_dim,
|
||||||
}
|
}
|
||||||
|
|
||||||
// Same as above, but now the matrix' data is stored in the upper-triangle
|
// Same as above, but now the matrix' data is stored in the upper-triangle
|
||||||
__attribute__((reqd_work_group_size(PAD_DIMX, PAD_DIMY, 1)))
|
__kernel __attribute__((reqd_work_group_size(PAD_DIMX, PAD_DIMY, 1)))
|
||||||
__kernel void SymmUpperToSquared(const int src_dim,
|
void SymmUpperToSquared(const int src_dim,
|
||||||
const int src_ld, const int src_offset,
|
const int src_ld, const int src_offset,
|
||||||
__global const real* restrict src,
|
__global const real* restrict src,
|
||||||
const int dest_dim,
|
const int dest_dim,
|
||||||
|
|
|
@ -20,8 +20,8 @@ R"(
|
||||||
|
|
||||||
// Kernel to populate a squared triangular matrix, given that the triangle which holds the data is
|
// Kernel to populate a squared triangular matrix, given that the triangle which holds the data is
|
||||||
// stored as the lower-triangle of the input matrix. This uses the padding kernel's parameters.
|
// stored as the lower-triangle of the input matrix. This uses the padding kernel's parameters.
|
||||||
__attribute__((reqd_work_group_size(PAD_DIMX, PAD_DIMY, 1)))
|
__kernel __attribute__((reqd_work_group_size(PAD_DIMX, PAD_DIMY, 1)))
|
||||||
__kernel void TriaLowerToSquared(const int src_dim,
|
void TriaLowerToSquared(const int src_dim,
|
||||||
const int src_ld, const int src_offset,
|
const int src_ld, const int src_offset,
|
||||||
__global const real* restrict src,
|
__global const real* restrict src,
|
||||||
const int dest_dim,
|
const int dest_dim,
|
||||||
|
@ -55,8 +55,8 @@ __kernel void TriaLowerToSquared(const int src_dim,
|
||||||
}
|
}
|
||||||
|
|
||||||
// Same as above, but now the matrix' data is stored in the upper-triangle
|
// Same as above, but now the matrix' data is stored in the upper-triangle
|
||||||
__attribute__((reqd_work_group_size(PAD_DIMX, PAD_DIMY, 1)))
|
__kernel __attribute__((reqd_work_group_size(PAD_DIMX, PAD_DIMY, 1)))
|
||||||
__kernel void TriaUpperToSquared(const int src_dim,
|
void TriaUpperToSquared(const int src_dim,
|
||||||
const int src_ld, const int src_offset,
|
const int src_ld, const int src_offset,
|
||||||
__global const real* restrict src,
|
__global const real* restrict src,
|
||||||
const int dest_dim,
|
const int dest_dim,
|
||||||
|
|
|
@ -35,12 +35,12 @@ R"(
|
||||||
|
|
||||||
// Fast copy kernel. Requires 'ld' and the number of threads in dimension 0 to be a multiple of
|
// Fast copy kernel. Requires 'ld' and the number of threads in dimension 0 to be a multiple of
|
||||||
// COPY_VW. Also requires both matrices to be of the same dimensions and without offset.
|
// COPY_VW. Also requires both matrices to be of the same dimensions and without offset.
|
||||||
__attribute__((reqd_work_group_size(COPY_DIMX, COPY_DIMY, 1)))
|
__kernel __attribute__((reqd_work_group_size(COPY_DIMX, COPY_DIMY, 1)))
|
||||||
__kernel void CopyMatrixFast(const int ld,
|
void CopyMatrixFast(const int ld,
|
||||||
__global const realC* restrict src,
|
__global const realC* restrict src,
|
||||||
__global realC* dest,
|
__global realC* dest,
|
||||||
const __constant real* restrict arg_alpha) {
|
const real_arg arg_alpha) {
|
||||||
const real alpha = arg_alpha[0];
|
const real alpha = GetRealArg(arg_alpha);
|
||||||
#pragma unroll
|
#pragma unroll
|
||||||
for (int w_one=0; w_one<COPY_WPT; ++w_one) {
|
for (int w_one=0; w_one<COPY_WPT; ++w_one) {
|
||||||
const int id_one = get_global_id(0);
|
const int id_one = get_global_id(0);
|
||||||
|
|
|
@ -24,16 +24,16 @@ R"(
|
||||||
// Copies a matrix from source to destination. The output is padded with zero values in case the
|
// Copies a matrix from source to destination. The output is padded with zero values in case the
|
||||||
// destination matrix dimensions are larger than the source matrix dimensions. Additionally, the ld
|
// destination matrix dimensions are larger than the source matrix dimensions. Additionally, the ld
|
||||||
// value and offset can be different.
|
// value and offset can be different.
|
||||||
__attribute__((reqd_work_group_size(PAD_DIMX, PAD_DIMY, 1)))
|
__kernel __attribute__((reqd_work_group_size(PAD_DIMX, PAD_DIMY, 1)))
|
||||||
__kernel void CopyPadMatrix(const int src_one, const int src_two,
|
void CopyPadMatrix(const int src_one, const int src_two,
|
||||||
const int src_ld, const int src_offset,
|
const int src_ld, const int src_offset,
|
||||||
__global const real* restrict src,
|
__global const real* restrict src,
|
||||||
const int dest_one, const int dest_two,
|
const int dest_one, const int dest_two,
|
||||||
const int dest_ld, const int dest_offset,
|
const int dest_ld, const int dest_offset,
|
||||||
__global real* dest,
|
__global real* dest,
|
||||||
const __constant real* restrict arg_alpha,
|
const real_arg arg_alpha,
|
||||||
const int do_conjugate) {
|
const int do_conjugate) {
|
||||||
const real alpha = arg_alpha[0];
|
const real alpha = GetRealArg(arg_alpha);
|
||||||
|
|
||||||
// Loops over the work per thread in both dimensions
|
// Loops over the work per thread in both dimensions
|
||||||
#pragma unroll
|
#pragma unroll
|
||||||
|
@ -65,17 +65,17 @@ __kernel void CopyPadMatrix(const int src_one, const int src_two,
|
||||||
// Same as above, but now un-pads a matrix. This kernel reads data from a padded source matrix, but
|
// Same as above, but now un-pads a matrix. This kernel reads data from a padded source matrix, but
|
||||||
// writes only the actual data back to the destination matrix. Again, the ld value and offset can
|
// writes only the actual data back to the destination matrix. Again, the ld value and offset can
|
||||||
// be different.
|
// be different.
|
||||||
__attribute__((reqd_work_group_size(PAD_DIMX, PAD_DIMY, 1)))
|
__kernel __attribute__((reqd_work_group_size(PAD_DIMX, PAD_DIMY, 1)))
|
||||||
__kernel void CopyMatrix(const int src_one, const int src_two,
|
void CopyMatrix(const int src_one, const int src_two,
|
||||||
const int src_ld, const int src_offset,
|
const int src_ld, const int src_offset,
|
||||||
__global const real* restrict src,
|
__global const real* restrict src,
|
||||||
const int dest_one, const int dest_two,
|
const int dest_one, const int dest_two,
|
||||||
const int dest_ld, const int dest_offset,
|
const int dest_ld, const int dest_offset,
|
||||||
__global real* dest,
|
__global real* dest,
|
||||||
const __constant real* restrict arg_alpha,
|
const real_arg arg_alpha,
|
||||||
const int upper, const int lower,
|
const int upper, const int lower,
|
||||||
const int diagonal_imag_zero) {
|
const int diagonal_imag_zero) {
|
||||||
const real alpha = arg_alpha[0];
|
const real alpha = GetRealArg(arg_alpha);
|
||||||
|
|
||||||
// Loops over the work per thread in both dimensions
|
// Loops over the work per thread in both dimensions
|
||||||
#pragma unroll
|
#pragma unroll
|
||||||
|
|
|
@ -36,12 +36,12 @@ R"(
|
||||||
|
|
||||||
// Transposes and copies a matrix. Requires both matrices to be of the same dimensions and without
|
// Transposes and copies a matrix. Requires both matrices to be of the same dimensions and without
|
||||||
// offset. A more general version is available in 'padtranspose.opencl'.
|
// offset. A more general version is available in 'padtranspose.opencl'.
|
||||||
__attribute__((reqd_work_group_size(TRA_DIM, TRA_DIM, 1)))
|
__kernel __attribute__((reqd_work_group_size(TRA_DIM, TRA_DIM, 1)))
|
||||||
__kernel void TransposeMatrixFast(const int ld,
|
void TransposeMatrixFast(const int ld,
|
||||||
__global const realT* restrict src,
|
__global const realT* restrict src,
|
||||||
__global realT* dest,
|
__global realT* dest,
|
||||||
const __constant real* restrict arg_alpha) {
|
const real_arg arg_alpha) {
|
||||||
const real alpha = arg_alpha[0];
|
const real alpha = GetRealArg(arg_alpha);
|
||||||
|
|
||||||
// Sets the group identifiers. They might be 'shuffled' around to distribute work in a different
|
// Sets the group identifiers. They might be 'shuffled' around to distribute work in a different
|
||||||
// way over workgroups, breaking memory-bank dependencies.
|
// way over workgroups, breaking memory-bank dependencies.
|
||||||
|
|
|
@ -24,16 +24,16 @@ R"(
|
||||||
|
|
||||||
// Transposes a matrix from source to destination. The output is padded with zero values in case the
|
// Transposes a matrix from source to destination. The output is padded with zero values in case the
|
||||||
// destination matrix dimensions are larger than the transposed source matrix dimensions.
|
// destination matrix dimensions are larger than the transposed source matrix dimensions.
|
||||||
__attribute__((reqd_work_group_size(PADTRA_TILE, PADTRA_TILE, 1)))
|
__kernel __attribute__((reqd_work_group_size(PADTRA_TILE, PADTRA_TILE, 1)))
|
||||||
__kernel void TransposePadMatrix(const int src_one, const int src_two,
|
void TransposePadMatrix(const int src_one, const int src_two,
|
||||||
const int src_ld, const int src_offset,
|
const int src_ld, const int src_offset,
|
||||||
__global const real* restrict src,
|
__global const real* restrict src,
|
||||||
const int dest_one, const int dest_two,
|
const int dest_one, const int dest_two,
|
||||||
const int dest_ld, const int dest_offset,
|
const int dest_ld, const int dest_offset,
|
||||||
__global real* dest,
|
__global real* dest,
|
||||||
const __constant real* restrict arg_alpha,
|
const real_arg arg_alpha,
|
||||||
const int do_conjugate) {
|
const int do_conjugate) {
|
||||||
const real alpha = arg_alpha[0];
|
const real alpha = GetRealArg(arg_alpha);
|
||||||
|
|
||||||
// Local memory to store a tile of the matrix (for coalescing)
|
// Local memory to store a tile of the matrix (for coalescing)
|
||||||
__local real tile[PADTRA_WPT*PADTRA_TILE][PADTRA_WPT*PADTRA_TILE + PADTRA_PAD];
|
__local real tile[PADTRA_WPT*PADTRA_TILE][PADTRA_WPT*PADTRA_TILE + PADTRA_PAD];
|
||||||
|
@ -88,17 +88,17 @@ __kernel void TransposePadMatrix(const int src_one, const int src_two,
|
||||||
// Transposes a matrix, while considering possible padding in the source matrix. Data is read from a
|
// Transposes a matrix, while considering possible padding in the source matrix. Data is read from a
|
||||||
// padded source matrix, but only the actual data is written back to the transposed destination
|
// padded source matrix, but only the actual data is written back to the transposed destination
|
||||||
// matrix. This kernel optionally checks for upper/lower triangular matrices.
|
// matrix. This kernel optionally checks for upper/lower triangular matrices.
|
||||||
__attribute__((reqd_work_group_size(PADTRA_TILE, PADTRA_TILE, 1)))
|
__kernel __attribute__((reqd_work_group_size(PADTRA_TILE, PADTRA_TILE, 1)))
|
||||||
__kernel void TransposeMatrix(const int src_one, const int src_two,
|
void TransposeMatrix(const int src_one, const int src_two,
|
||||||
const int src_ld, const int src_offset,
|
const int src_ld, const int src_offset,
|
||||||
__global const real* restrict src,
|
__global const real* restrict src,
|
||||||
const int dest_one, const int dest_two,
|
const int dest_one, const int dest_two,
|
||||||
const int dest_ld, const int dest_offset,
|
const int dest_ld, const int dest_offset,
|
||||||
__global real* dest,
|
__global real* dest,
|
||||||
const __constant real* restrict arg_alpha,
|
const real_arg arg_alpha,
|
||||||
const int upper, const int lower,
|
const int upper, const int lower,
|
||||||
const int diagonal_imag_zero) {
|
const int diagonal_imag_zero) {
|
||||||
const real alpha = arg_alpha[0];
|
const real alpha = GetRealArg(arg_alpha);
|
||||||
|
|
||||||
// Local memory to store a tile of the matrix (for coalescing)
|
// Local memory to store a tile of the matrix (for coalescing)
|
||||||
__local real tile[PADTRA_WPT*PADTRA_TILE][PADTRA_WPT*PADTRA_TILE + PADTRA_PAD];
|
__local real tile[PADTRA_WPT*PADTRA_TILE][PADTRA_WPT*PADTRA_TILE + PADTRA_PAD];
|
||||||
|
|
|
@ -31,7 +31,7 @@
|
||||||
// o-------o o-----o
|
// o-------o o-----o
|
||||||
//
|
//
|
||||||
//
|
//
|
||||||
// This kernel is seperated into two files. This is part 1 out of 2.
|
// This kernel is seperated into three files. This is part 1 out of 3.
|
||||||
//
|
//
|
||||||
// =================================================================================================
|
// =================================================================================================
|
||||||
|
|
||||||
|
|
|
@ -7,7 +7,7 @@
|
||||||
// Author(s):
|
// Author(s):
|
||||||
// Cedric Nugteren <www.cedricnugteren.nl>
|
// Cedric Nugteren <www.cedricnugteren.nl>
|
||||||
//
|
//
|
||||||
// This is part 2 of 2 of the GEMM kernel. See part 1 for more information.
|
// This is part 2 of 3 of the GEMM kernel. See part 1 for more information.
|
||||||
//
|
//
|
||||||
// =================================================================================================
|
// =================================================================================================
|
||||||
|
|
||||||
|
@ -133,11 +133,54 @@ inline void StoreResults(__global realM* cgm, realM cpm[NWI][MWI/VWM], const int
|
||||||
#endif
|
#endif
|
||||||
int idm = mg + GetGroupID0() * (MWG/VWM);
|
int idm = mg + GetGroupID0() * (MWG/VWM);
|
||||||
int idn = ng + GetGroupID1() * NWG;
|
int idn = ng + GetGroupID1() * NWG;
|
||||||
|
|
||||||
// The final multiplication with alpha and the addition with beta*C
|
|
||||||
int index = idn*(kSizeM/VWM) + idm;
|
int index = idn*(kSizeM/VWM) + idm;
|
||||||
|
|
||||||
realM result;
|
realM result;
|
||||||
realM xval = cpm[ni][mi];
|
realM xval = cpm[ni][mi];
|
||||||
|
|
||||||
|
// The final multiplication with alpha (in case beta == 0)
|
||||||
|
if (IsZero(beta)) {
|
||||||
|
#if VWM == 1
|
||||||
|
Multiply(result, alpha, xval);
|
||||||
|
#elif VWM == 2
|
||||||
|
Multiply(result.x, alpha, xval.x);
|
||||||
|
Multiply(result.y, alpha, xval.y);
|
||||||
|
#elif VWM == 4
|
||||||
|
Multiply(result.x, alpha, xval.x);
|
||||||
|
Multiply(result.y, alpha, xval.y);
|
||||||
|
Multiply(result.z, alpha, xval.z);
|
||||||
|
Multiply(result.w, alpha, xval.w);
|
||||||
|
#elif VWM == 8
|
||||||
|
Multiply(result.s0, alpha, xval.s0);
|
||||||
|
Multiply(result.s1, alpha, xval.s1);
|
||||||
|
Multiply(result.s2, alpha, xval.s2);
|
||||||
|
Multiply(result.s3, alpha, xval.s3);
|
||||||
|
Multiply(result.s4, alpha, xval.s4);
|
||||||
|
Multiply(result.s5, alpha, xval.s5);
|
||||||
|
Multiply(result.s6, alpha, xval.s6);
|
||||||
|
Multiply(result.s7, alpha, xval.s7);
|
||||||
|
#elif VWM == 16
|
||||||
|
Multiply(result.s0, alpha, xval.s0);
|
||||||
|
Multiply(result.s1, alpha, xval.s1);
|
||||||
|
Multiply(result.s2, alpha, xval.s2);
|
||||||
|
Multiply(result.s3, alpha, xval.s3);
|
||||||
|
Multiply(result.s4, alpha, xval.s4);
|
||||||
|
Multiply(result.s5, alpha, xval.s5);
|
||||||
|
Multiply(result.s6, alpha, xval.s6);
|
||||||
|
Multiply(result.s7, alpha, xval.s7);
|
||||||
|
Multiply(result.s8, alpha, xval.s8);
|
||||||
|
Multiply(result.s9, alpha, xval.s9);
|
||||||
|
Multiply(result.sA, alpha, xval.sA);
|
||||||
|
Multiply(result.sB, alpha, xval.sB);
|
||||||
|
Multiply(result.sC, alpha, xval.sC);
|
||||||
|
Multiply(result.sD, alpha, xval.sD);
|
||||||
|
Multiply(result.sE, alpha, xval.sE);
|
||||||
|
Multiply(result.sF, alpha, xval.sF);
|
||||||
|
#endif
|
||||||
|
}
|
||||||
|
|
||||||
|
// The final multiplication with alpha and the addition with beta*C
|
||||||
|
else {
|
||||||
realM yval = cgm[index];
|
realM yval = cgm[index];
|
||||||
#if VWM == 1
|
#if VWM == 1
|
||||||
AXPBY(result, alpha, xval, beta, yval);
|
AXPBY(result, alpha, xval, beta, yval);
|
||||||
|
@ -176,6 +219,7 @@ inline void StoreResults(__global realM* cgm, realM cpm[NWI][MWI/VWM], const int
|
||||||
AXPBY(result.sE, alpha, xval.sE, beta, yval.sE);
|
AXPBY(result.sE, alpha, xval.sE, beta, yval.sE);
|
||||||
AXPBY(result.sF, alpha, xval.sF, beta, yval.sF);
|
AXPBY(result.sF, alpha, xval.sF, beta, yval.sF);
|
||||||
#endif
|
#endif
|
||||||
|
}
|
||||||
cgm[index] = result;
|
cgm[index] = result;
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
|
@ -183,212 +227,6 @@ inline void StoreResults(__global realM* cgm, realM cpm[NWI][MWI/VWM], const int
|
||||||
|
|
||||||
// =================================================================================================
|
// =================================================================================================
|
||||||
|
|
||||||
// Main body of the matrix-multiplication algorithm. It calls the (inlined) functions above.
|
|
||||||
inline void XgemmBody(const int kSizeM, const int kSizeN, const int kSizeK,
|
|
||||||
const __global realM* restrict agm, const __global realN* restrict bgm,
|
|
||||||
__global realM* cgm, realM cpm[NWI][MWI/VWM]
|
|
||||||
#if SA == 1 && SB == 1
|
|
||||||
, __local realM* alm, __local realN* blm
|
|
||||||
#elif SA == 1
|
|
||||||
, __local realM* alm
|
|
||||||
#elif SB == 1
|
|
||||||
, __local realN* blm
|
|
||||||
#endif
|
|
||||||
) {
|
|
||||||
|
|
||||||
// Allocates workitem-private memory (registers)
|
|
||||||
realM apm[MWI/VWM];
|
|
||||||
realN bpm[NWI/VWN];
|
|
||||||
|
|
||||||
// Combined thread identifier (volatile to disable caching)
|
|
||||||
#if SA == 1 || SB == 1
|
|
||||||
volatile int tid = get_local_id(0) + MDIMC*get_local_id(1);
|
|
||||||
#endif
|
|
||||||
|
|
||||||
// Initializes the accumulation registers
|
|
||||||
InitAccRegisters(cpm);
|
|
||||||
|
|
||||||
// Loops over all workgroup tiles
|
|
||||||
for (int kwg=0; kwg<kSizeK; kwg+=KWG) {
|
|
||||||
|
|
||||||
// Loads data: off-chip --> local (matrix A)
|
|
||||||
#if SA == 1
|
|
||||||
GlobalToLocalA(agm, alm, kSizeM, tid, kwg);
|
|
||||||
#endif
|
|
||||||
// Loads data: off-chip --> local (matrix B)
|
|
||||||
#if SB == 1
|
|
||||||
GlobalToLocalB(bgm, blm, kSizeN, tid, kwg);
|
|
||||||
#endif
|
|
||||||
#if SA == 1 || SB == 1
|
|
||||||
barrier(CLK_LOCAL_MEM_FENCE);
|
|
||||||
#endif
|
|
||||||
|
|
||||||
// Loops over all workitem tiles, unrolled by a factor KWI
|
|
||||||
for (int pwi=0; pwi<KWG; pwi+=KWI) {
|
|
||||||
#pragma unroll
|
|
||||||
for (int pit=0; pit<KWI; ++pit) {
|
|
||||||
#if SA == 0 || SB == 0
|
|
||||||
int idk = kwg + pwi + pit;
|
|
||||||
#endif
|
|
||||||
#if SA == 1 || SB == 1
|
|
||||||
int kg = pwi+pit;
|
|
||||||
#endif
|
|
||||||
|
|
||||||
// Loads data: local --> private (matrix A)
|
|
||||||
#if SA == 1
|
|
||||||
LocalToPrivateA(alm, apm, kg);
|
|
||||||
// Loads data: off-chip --> private (matrix A)
|
|
||||||
#else
|
|
||||||
GlobalToPrivateA(agm, apm, kSizeM, idk, kwg);
|
|
||||||
#endif
|
|
||||||
|
|
||||||
// Loads data: local --> private (matrix B)
|
|
||||||
#if SB == 1
|
|
||||||
LocalToPrivateB(blm, bpm, kg);
|
|
||||||
// Loads data: off-chip --> private (matrix B)
|
|
||||||
#else
|
|
||||||
GlobalToPrivateB(bgm, bpm, kSizeN, idk);
|
|
||||||
#endif
|
|
||||||
|
|
||||||
// Performs the accumulation (Cpm += Apm * Bpm)
|
|
||||||
MultiplyAccumulate(cpm, apm, bpm);
|
|
||||||
}
|
|
||||||
}
|
|
||||||
#if SA == 1 || SB == 1
|
|
||||||
barrier(CLK_LOCAL_MEM_FENCE);
|
|
||||||
#endif
|
|
||||||
}
|
|
||||||
#if GLOBAL_MEM_FENCE == 1
|
|
||||||
barrier(CLK_GLOBAL_MEM_FENCE);
|
|
||||||
#endif
|
|
||||||
}
|
|
||||||
|
|
||||||
// =================================================================================================
|
|
||||||
// The upper-triangular and lower-triangular kernels are only used in special cases
|
|
||||||
#if defined(ROUTINE_SYRK) || defined(ROUTINE_HERK) || defined(ROUTINE_SYR2K) || defined(ROUTINE_HER2K)
|
|
||||||
|
|
||||||
// Main entry point of the kernel. This is the upper-triangular version.
|
|
||||||
__attribute__((reqd_work_group_size(MDIMC, NDIMC, 1)))
|
|
||||||
__kernel void XgemmUpper(const int kSizeN, const int kSizeK,
|
|
||||||
const __constant real* restrict arg_alpha,
|
|
||||||
const __constant real* restrict arg_beta,
|
|
||||||
const __global realM* restrict agm,
|
|
||||||
const __global realN* restrict bgm,
|
|
||||||
__global realM* cgm) {
|
|
||||||
const real alpha = arg_alpha[0];
|
|
||||||
const real beta = arg_beta[0];
|
|
||||||
|
|
||||||
// Skip these threads if they do not contain threads contributing to the upper-triangle
|
|
||||||
if (GetGroupID1()*NWG < GetGroupID0()*MWG) {
|
|
||||||
return;
|
|
||||||
}
|
|
||||||
|
|
||||||
// Allocates workgroup-private memory (local memory)
|
|
||||||
#if SA == 1
|
|
||||||
__local realM alm[KWG * MWG/VWM];
|
|
||||||
#endif
|
|
||||||
#if SB == 1
|
|
||||||
__local realN blm[KWG * NWG/VWN];
|
|
||||||
#endif
|
|
||||||
|
|
||||||
// Computes the matrix-multiplication and stores the result in register memory
|
|
||||||
realM cpm[NWI][MWI/VWM];
|
|
||||||
#if SA == 1 && SB == 1
|
|
||||||
XgemmBody(kSizeN, kSizeN, kSizeK, agm, bgm, cgm, cpm, alm, blm);
|
|
||||||
#elif SA == 1
|
|
||||||
XgemmBody(kSizeN, kSizeN, kSizeK, agm, bgm, cgm, cpm, alm);
|
|
||||||
#elif SB == 1
|
|
||||||
XgemmBody(kSizeN, kSizeN, kSizeK, agm, bgm, cgm, cpm, blm);
|
|
||||||
#else
|
|
||||||
XgemmBody(kSizeN, kSizeN, kSizeK, agm, bgm, cgm, cpm);
|
|
||||||
#endif
|
|
||||||
|
|
||||||
// Stores an MWG * NWG tile of results and performs the multiplication with alpha and beta
|
|
||||||
StoreResults(cgm, cpm, kSizeN, alpha, beta);
|
|
||||||
}
|
|
||||||
|
|
||||||
// Main entry point of the kernel. This is the lower-triangular version.
|
|
||||||
__attribute__((reqd_work_group_size(MDIMC, NDIMC, 1)))
|
|
||||||
__kernel void XgemmLower(const int kSizeN, const int kSizeK,
|
|
||||||
const __constant real* restrict arg_alpha,
|
|
||||||
const __constant real* restrict arg_beta,
|
|
||||||
const __global realM* restrict agm,
|
|
||||||
const __global realN* restrict bgm,
|
|
||||||
__global realM* cgm) {
|
|
||||||
const real alpha = arg_alpha[0];
|
|
||||||
const real beta = arg_beta[0];
|
|
||||||
|
|
||||||
// Skip these threads if they do not contain threads contributing to the lower-triangle
|
|
||||||
if (GetGroupID1()*NWG > GetGroupID0()*MWG) {
|
|
||||||
return;
|
|
||||||
}
|
|
||||||
|
|
||||||
// Allocates workgroup-private memory (local memory)
|
|
||||||
#if SA == 1
|
|
||||||
__local realM alm[KWG * MWG/VWM];
|
|
||||||
#endif
|
|
||||||
#if SB == 1
|
|
||||||
__local realN blm[KWG * NWG/VWN];
|
|
||||||
#endif
|
|
||||||
|
|
||||||
// Computes the matrix-multiplication and stores the result in register memory
|
|
||||||
realM cpm[NWI][MWI/VWM];
|
|
||||||
#if SA == 1 && SB == 1
|
|
||||||
XgemmBody(kSizeN, kSizeN, kSizeK, agm, bgm, cgm, cpm, alm, blm);
|
|
||||||
#elif SA == 1
|
|
||||||
XgemmBody(kSizeN, kSizeN, kSizeK, agm, bgm, cgm, cpm, alm);
|
|
||||||
#elif SB == 1
|
|
||||||
XgemmBody(kSizeN, kSizeN, kSizeK, agm, bgm, cgm, cpm, blm);
|
|
||||||
#else
|
|
||||||
XgemmBody(kSizeN, kSizeN, kSizeK, agm, bgm, cgm, cpm);
|
|
||||||
#endif
|
|
||||||
|
|
||||||
// Stores an MWG * NWG tile of results and performs the multiplication with alpha and beta
|
|
||||||
StoreResults(cgm, cpm, kSizeN, alpha, beta);
|
|
||||||
}
|
|
||||||
|
|
||||||
// =================================================================================================
|
|
||||||
// If not using a triangular version, include the regular kernel
|
|
||||||
#else
|
|
||||||
|
|
||||||
// Main entry point of the kernel. This is the regular full version.
|
|
||||||
__attribute__((reqd_work_group_size(MDIMC, NDIMC, 1)))
|
|
||||||
__kernel void Xgemm(const int kSizeM, const int kSizeN, const int kSizeK,
|
|
||||||
const __constant real* restrict arg_alpha,
|
|
||||||
const __constant real* restrict arg_beta,
|
|
||||||
const __global realM* restrict agm,
|
|
||||||
const __global realN* restrict bgm,
|
|
||||||
__global realM* cgm) {
|
|
||||||
const real alpha = arg_alpha[0];
|
|
||||||
const real beta = arg_beta[0];
|
|
||||||
|
|
||||||
// Allocates workgroup-private memory (local memory)
|
|
||||||
#if SA == 1
|
|
||||||
__local realM alm[KWG * MWG/VWM];
|
|
||||||
#endif
|
|
||||||
#if SB == 1
|
|
||||||
__local realN blm[KWG * NWG/VWN];
|
|
||||||
#endif
|
|
||||||
|
|
||||||
// Computes the matrix-multiplication and stores the result in register memory
|
|
||||||
realM cpm[NWI][MWI/VWM];
|
|
||||||
#if SA == 1 && SB == 1
|
|
||||||
XgemmBody(kSizeM, kSizeN, kSizeK, agm, bgm, cgm, cpm, alm, blm);
|
|
||||||
#elif SA == 1
|
|
||||||
XgemmBody(kSizeM, kSizeN, kSizeK, agm, bgm, cgm, cpm, alm);
|
|
||||||
#elif SB == 1
|
|
||||||
XgemmBody(kSizeM, kSizeN, kSizeK, agm, bgm, cgm, cpm, blm);
|
|
||||||
#else
|
|
||||||
XgemmBody(kSizeM, kSizeN, kSizeK, agm, bgm, cgm, cpm);
|
|
||||||
#endif
|
|
||||||
|
|
||||||
// Stores an MWG * NWG tile of results and performs the multiplication with alpha and beta
|
|
||||||
StoreResults(cgm, cpm, kSizeM, alpha, beta);
|
|
||||||
}
|
|
||||||
|
|
||||||
#endif
|
|
||||||
// =================================================================================================
|
|
||||||
|
|
||||||
// End of the C++11 raw string literal
|
// End of the C++11 raw string literal
|
||||||
)"
|
)"
|
||||||
|
|
||||||
|
|
229
src/kernels/level3/xgemm_part3.opencl
Normal file
229
src/kernels/level3/xgemm_part3.opencl
Normal file
|
@ -0,0 +1,229 @@
|
||||||
|
|
||||||
|
// =================================================================================================
|
||||||
|
// This file is part of the CLBlast project. The project is licensed under Apache Version 2.0. This
|
||||||
|
// project loosely follows the Google C++ styleguide and uses a tab-size of two spaces and a max-
|
||||||
|
// width of 100 characters per line.
|
||||||
|
//
|
||||||
|
// Author(s):
|
||||||
|
// Cedric Nugteren <www.cedricnugteren.nl>
|
||||||
|
//
|
||||||
|
// This is part 3 of 3 of the GEMM kernel. See part 1 for more information.
|
||||||
|
//
|
||||||
|
// =================================================================================================
|
||||||
|
|
||||||
|
// Enables loading of this file using the C++ pre-processor's #include (C++11 standard raw string
|
||||||
|
// literal). Comment-out this line for syntax-highlighting when developing.
|
||||||
|
R"(
|
||||||
|
|
||||||
|
// =================================================================================================
|
||||||
|
|
||||||
|
// Main body of the matrix-multiplication algorithm. It calls the (inlined) functions above.
|
||||||
|
inline void XgemmBody(const int kSizeM, const int kSizeN, const int kSizeK,
|
||||||
|
const __global realM* restrict agm, const __global realN* restrict bgm,
|
||||||
|
__global realM* cgm, realM cpm[NWI][MWI/VWM]
|
||||||
|
#if SA == 1 && SB == 1
|
||||||
|
, __local realM* alm, __local realN* blm
|
||||||
|
#elif SA == 1
|
||||||
|
, __local realM* alm
|
||||||
|
#elif SB == 1
|
||||||
|
, __local realN* blm
|
||||||
|
#endif
|
||||||
|
) {
|
||||||
|
|
||||||
|
// Allocates workitem-private memory (registers)
|
||||||
|
realM apm[MWI/VWM];
|
||||||
|
realN bpm[NWI/VWN];
|
||||||
|
|
||||||
|
// Combined thread identifier (volatile to disable caching)
|
||||||
|
#if SA == 1 || SB == 1
|
||||||
|
volatile int tid = get_local_id(0) + MDIMC*get_local_id(1);
|
||||||
|
#endif
|
||||||
|
|
||||||
|
// Initializes the accumulation registers
|
||||||
|
InitAccRegisters(cpm);
|
||||||
|
|
||||||
|
// Loops over all workgroup tiles
|
||||||
|
for (int kwg=0; kwg<kSizeK; kwg+=KWG) {
|
||||||
|
|
||||||
|
// Loads data: off-chip --> local (matrix A)
|
||||||
|
#if SA == 1
|
||||||
|
GlobalToLocalA(agm, alm, kSizeM, tid, kwg);
|
||||||
|
#endif
|
||||||
|
// Loads data: off-chip --> local (matrix B)
|
||||||
|
#if SB == 1
|
||||||
|
GlobalToLocalB(bgm, blm, kSizeN, tid, kwg);
|
||||||
|
#endif
|
||||||
|
#if SA == 1 || SB == 1
|
||||||
|
barrier(CLK_LOCAL_MEM_FENCE);
|
||||||
|
#endif
|
||||||
|
|
||||||
|
// Loops over all workitem tiles, unrolled by a factor KWI
|
||||||
|
for (int pwi=0; pwi<KWG; pwi+=KWI) {
|
||||||
|
#pragma unroll
|
||||||
|
for (int pit=0; pit<KWI; ++pit) {
|
||||||
|
#if SA == 0 || SB == 0
|
||||||
|
int idk = kwg + pwi + pit;
|
||||||
|
#endif
|
||||||
|
#if SA == 1 || SB == 1
|
||||||
|
int kg = pwi+pit;
|
||||||
|
#endif
|
||||||
|
|
||||||
|
// Loads data: local --> private (matrix A)
|
||||||
|
#if SA == 1
|
||||||
|
LocalToPrivateA(alm, apm, kg);
|
||||||
|
// Loads data: off-chip --> private (matrix A)
|
||||||
|
#else
|
||||||
|
GlobalToPrivateA(agm, apm, kSizeM, idk, kwg);
|
||||||
|
#endif
|
||||||
|
|
||||||
|
// Loads data: local --> private (matrix B)
|
||||||
|
#if SB == 1
|
||||||
|
LocalToPrivateB(blm, bpm, kg);
|
||||||
|
// Loads data: off-chip --> private (matrix B)
|
||||||
|
#else
|
||||||
|
GlobalToPrivateB(bgm, bpm, kSizeN, idk);
|
||||||
|
#endif
|
||||||
|
|
||||||
|
// Performs the accumulation (Cpm += Apm * Bpm)
|
||||||
|
MultiplyAccumulate(cpm, apm, bpm);
|
||||||
|
}
|
||||||
|
}
|
||||||
|
#if SA == 1 || SB == 1
|
||||||
|
barrier(CLK_LOCAL_MEM_FENCE);
|
||||||
|
#endif
|
||||||
|
}
|
||||||
|
#if GLOBAL_MEM_FENCE == 1
|
||||||
|
barrier(CLK_GLOBAL_MEM_FENCE);
|
||||||
|
#endif
|
||||||
|
}
|
||||||
|
|
||||||
|
// =================================================================================================
|
||||||
|
// The upper-triangular and lower-triangular kernels are only used in special cases
|
||||||
|
#if defined(ROUTINE_SYRK) || defined(ROUTINE_HERK) || defined(ROUTINE_SYR2K) || defined(ROUTINE_HER2K)
|
||||||
|
|
||||||
|
// Main entry point of the kernel. This is the upper-triangular version.
|
||||||
|
__kernel __attribute__((reqd_work_group_size(MDIMC, NDIMC, 1)))
|
||||||
|
void XgemmUpper(const int kSizeN, const int kSizeK,
|
||||||
|
const real_arg arg_alpha,
|
||||||
|
const real_arg arg_beta,
|
||||||
|
const __global realM* restrict agm,
|
||||||
|
const __global realN* restrict bgm,
|
||||||
|
__global realM* cgm) {
|
||||||
|
const real alpha = GetRealArg(arg_alpha);
|
||||||
|
const real beta = GetRealArg(arg_beta);
|
||||||
|
|
||||||
|
// Skip these threads if they do not contain threads contributing to the upper-triangle
|
||||||
|
if (GetGroupID1()*NWG < GetGroupID0()*MWG) {
|
||||||
|
return;
|
||||||
|
}
|
||||||
|
|
||||||
|
// Allocates workgroup-private memory (local memory)
|
||||||
|
#if SA == 1
|
||||||
|
__local realM alm[KWG * MWG/VWM];
|
||||||
|
#endif
|
||||||
|
#if SB == 1
|
||||||
|
__local realN blm[KWG * NWG/VWN];
|
||||||
|
#endif
|
||||||
|
|
||||||
|
// Computes the matrix-multiplication and stores the result in register memory
|
||||||
|
realM cpm[NWI][MWI/VWM];
|
||||||
|
#if SA == 1 && SB == 1
|
||||||
|
XgemmBody(kSizeN, kSizeN, kSizeK, agm, bgm, cgm, cpm, alm, blm);
|
||||||
|
#elif SA == 1
|
||||||
|
XgemmBody(kSizeN, kSizeN, kSizeK, agm, bgm, cgm, cpm, alm);
|
||||||
|
#elif SB == 1
|
||||||
|
XgemmBody(kSizeN, kSizeN, kSizeK, agm, bgm, cgm, cpm, blm);
|
||||||
|
#else
|
||||||
|
XgemmBody(kSizeN, kSizeN, kSizeK, agm, bgm, cgm, cpm);
|
||||||
|
#endif
|
||||||
|
|
||||||
|
// Stores an MWG * NWG tile of results and performs the multiplication with alpha and beta
|
||||||
|
StoreResults(cgm, cpm, kSizeN, alpha, beta);
|
||||||
|
}
|
||||||
|
|
||||||
|
// Main entry point of the kernel. This is the lower-triangular version.
|
||||||
|
__kernel __attribute__((reqd_work_group_size(MDIMC, NDIMC, 1)))
|
||||||
|
void XgemmLower(const int kSizeN, const int kSizeK,
|
||||||
|
const real_arg arg_alpha,
|
||||||
|
const real_arg arg_beta,
|
||||||
|
const __global realM* restrict agm,
|
||||||
|
const __global realN* restrict bgm,
|
||||||
|
__global realM* cgm) {
|
||||||
|
const real alpha = GetRealArg(arg_alpha);
|
||||||
|
const real beta = GetRealArg(arg_beta);
|
||||||
|
|
||||||
|
// Skip these threads if they do not contain threads contributing to the lower-triangle
|
||||||
|
if (GetGroupID1()*NWG > GetGroupID0()*MWG) {
|
||||||
|
return;
|
||||||
|
}
|
||||||
|
|
||||||
|
// Allocates workgroup-private memory (local memory)
|
||||||
|
#if SA == 1
|
||||||
|
__local realM alm[KWG * MWG/VWM];
|
||||||
|
#endif
|
||||||
|
#if SB == 1
|
||||||
|
__local realN blm[KWG * NWG/VWN];
|
||||||
|
#endif
|
||||||
|
|
||||||
|
// Computes the matrix-multiplication and stores the result in register memory
|
||||||
|
realM cpm[NWI][MWI/VWM];
|
||||||
|
#if SA == 1 && SB == 1
|
||||||
|
XgemmBody(kSizeN, kSizeN, kSizeK, agm, bgm, cgm, cpm, alm, blm);
|
||||||
|
#elif SA == 1
|
||||||
|
XgemmBody(kSizeN, kSizeN, kSizeK, agm, bgm, cgm, cpm, alm);
|
||||||
|
#elif SB == 1
|
||||||
|
XgemmBody(kSizeN, kSizeN, kSizeK, agm, bgm, cgm, cpm, blm);
|
||||||
|
#else
|
||||||
|
XgemmBody(kSizeN, kSizeN, kSizeK, agm, bgm, cgm, cpm);
|
||||||
|
#endif
|
||||||
|
|
||||||
|
// Stores an MWG * NWG tile of results and performs the multiplication with alpha and beta
|
||||||
|
StoreResults(cgm, cpm, kSizeN, alpha, beta);
|
||||||
|
}
|
||||||
|
|
||||||
|
// =================================================================================================
|
||||||
|
// If not using a triangular version, include the regular kernel
|
||||||
|
#else
|
||||||
|
|
||||||
|
// Main entry point of the kernel. This is the regular full version.
|
||||||
|
__kernel __attribute__((reqd_work_group_size(MDIMC, NDIMC, 1)))
|
||||||
|
void Xgemm(const int kSizeM, const int kSizeN, const int kSizeK,
|
||||||
|
const real_arg arg_alpha,
|
||||||
|
const real_arg arg_beta,
|
||||||
|
const __global realM* restrict agm,
|
||||||
|
const __global realN* restrict bgm,
|
||||||
|
__global realM* cgm) {
|
||||||
|
const real alpha = GetRealArg(arg_alpha);
|
||||||
|
const real beta = GetRealArg(arg_beta);
|
||||||
|
|
||||||
|
// Allocates workgroup-private memory (local memory)
|
||||||
|
#if SA == 1
|
||||||
|
__local realM alm[KWG * MWG/VWM];
|
||||||
|
#endif
|
||||||
|
#if SB == 1
|
||||||
|
__local realN blm[KWG * NWG/VWN];
|
||||||
|
#endif
|
||||||
|
|
||||||
|
// Computes the matrix-multiplication and stores the result in register memory
|
||||||
|
realM cpm[NWI][MWI/VWM];
|
||||||
|
#if SA == 1 && SB == 1
|
||||||
|
XgemmBody(kSizeM, kSizeN, kSizeK, agm, bgm, cgm, cpm, alm, blm);
|
||||||
|
#elif SA == 1
|
||||||
|
XgemmBody(kSizeM, kSizeN, kSizeK, agm, bgm, cgm, cpm, alm);
|
||||||
|
#elif SB == 1
|
||||||
|
XgemmBody(kSizeM, kSizeN, kSizeK, agm, bgm, cgm, cpm, blm);
|
||||||
|
#else
|
||||||
|
XgemmBody(kSizeM, kSizeN, kSizeK, agm, bgm, cgm, cpm);
|
||||||
|
#endif
|
||||||
|
|
||||||
|
// Stores an MWG * NWG tile of results and performs the multiplication with alpha and beta
|
||||||
|
StoreResults(cgm, cpm, kSizeM, alpha, beta);
|
||||||
|
}
|
||||||
|
|
||||||
|
#endif
|
||||||
|
// =================================================================================================
|
||||||
|
|
||||||
|
// End of the C++11 raw string literal
|
||||||
|
)"
|
||||||
|
|
||||||
|
// =================================================================================================
|
|
@ -1,34 +0,0 @@
|
||||||
|
|
||||||
// =================================================================================================
|
|
||||||
// This file is part of the CLBlast project. The project is licensed under Apache Version 2.0. This
|
|
||||||
// project loosely follows the Google C++ styleguide and uses a tab-size of two spaces and a max-
|
|
||||||
// width of 100 characters per line.
|
|
||||||
//
|
|
||||||
// Author(s):
|
|
||||||
// Cedric Nugteren <www.cedricnugteren.nl>
|
|
||||||
//
|
|
||||||
// This file provides macro's to define the public API. This is needed when building a Windows DLL.
|
|
||||||
// Note: this is only used for the C++ interface, the C interface has its own definition included in
|
|
||||||
// the header file itself.
|
|
||||||
//
|
|
||||||
// =================================================================================================
|
|
||||||
|
|
||||||
#ifndef CLBLAST_PUBLIC_API_H_
|
|
||||||
#define CLBLAST_PUBLIC_API_H_
|
|
||||||
|
|
||||||
namespace clblast {
|
|
||||||
// =================================================================================================
|
|
||||||
|
|
||||||
// Exports library functions under Windows when building a DLL. See also:
|
|
||||||
// https://msdn.microsoft.com/en-us/library/a90k134d.aspx
|
|
||||||
#ifdef _WIN32
|
|
||||||
#define PUBLIC_API __declspec(dllexport)
|
|
||||||
#else
|
|
||||||
#define PUBLIC_API
|
|
||||||
#endif
|
|
||||||
|
|
||||||
// =================================================================================================
|
|
||||||
} // namespace clblast
|
|
||||||
|
|
||||||
// CLBLAST_PUBLIC_API_H_
|
|
||||||
#endif
|
|
|
@ -13,6 +13,7 @@
|
||||||
|
|
||||||
#include <string>
|
#include <string>
|
||||||
#include <vector>
|
#include <vector>
|
||||||
|
#include <chrono>
|
||||||
|
|
||||||
#include "routine.hpp"
|
#include "routine.hpp"
|
||||||
|
|
||||||
|
@ -21,7 +22,8 @@ namespace clblast {
|
||||||
|
|
||||||
// Constructor: not much here, because no status codes can be returned
|
// Constructor: not much here, because no status codes can be returned
|
||||||
Routine::Routine(Queue &queue, EventPointer event, const std::string &name,
|
Routine::Routine(Queue &queue, EventPointer event, const std::string &name,
|
||||||
const std::vector<std::string> &routines, const Precision precision):
|
const std::vector<std::string> &routines, const Precision precision,
|
||||||
|
const std::vector<Database::DatabaseEntry> &userDatabase):
|
||||||
precision_(precision),
|
precision_(precision),
|
||||||
routine_name_(name),
|
routine_name_(name),
|
||||||
queue_(queue),
|
queue_(queue),
|
||||||
|
@ -29,7 +31,7 @@ Routine::Routine(Queue &queue, EventPointer event, const std::string &name,
|
||||||
context_(queue_.GetContext()),
|
context_(queue_.GetContext()),
|
||||||
device_(queue_.GetDevice()),
|
device_(queue_.GetDevice()),
|
||||||
device_name_(device_.Name()),
|
device_name_(device_.Name()),
|
||||||
db_(queue_, routines, precision_) {
|
db_(queue_, routines, precision_, userDatabase) {
|
||||||
}
|
}
|
||||||
|
|
||||||
// =================================================================================================
|
// =================================================================================================
|
||||||
|
@ -103,6 +105,13 @@ StatusCode Routine::SetUp() {
|
||||||
// Combines everything together into a single source string
|
// Combines everything together into a single source string
|
||||||
const auto source_string = defines + common_header + source_string_;
|
const auto source_string = defines + common_header + source_string_;
|
||||||
|
|
||||||
|
// Prints details of the routine to compile in case of debugging in verbose mode
|
||||||
|
#ifdef VERBOSE
|
||||||
|
printf("[DEBUG] Compiling routine '%s-%s' for device '%s'\n",
|
||||||
|
routine_name_.c_str(), ToString(precision_).c_str(), device_name_.c_str());
|
||||||
|
const auto start_time = std::chrono::steady_clock::now();
|
||||||
|
#endif
|
||||||
|
|
||||||
// Compiles the kernel
|
// Compiles the kernel
|
||||||
try {
|
try {
|
||||||
auto program = Program(context_, source_string);
|
auto program = Program(context_, source_string);
|
||||||
|
@ -123,6 +132,13 @@ StatusCode Routine::SetUp() {
|
||||||
StoreProgramToCache(program, context_, precision_, routine_name_);
|
StoreProgramToCache(program, context_, precision_, routine_name_);
|
||||||
} catch (...) { return StatusCode::kBuildProgramFailure; }
|
} catch (...) { return StatusCode::kBuildProgramFailure; }
|
||||||
|
|
||||||
|
// Prints the elapsed compilation time in case of debugging in verbose mode
|
||||||
|
#ifdef VERBOSE
|
||||||
|
const auto elapsed_time = std::chrono::steady_clock::now() - start_time;
|
||||||
|
const auto timing = std::chrono::duration<double,std::milli>(elapsed_time).count();
|
||||||
|
printf("[DEBUG] Completed compilation in %.2lf ms\n", timing);
|
||||||
|
#endif
|
||||||
|
|
||||||
// No errors, normal termination of this function
|
// No errors, normal termination of this function
|
||||||
return StatusCode::kSuccess;
|
return StatusCode::kSuccess;
|
||||||
}
|
}
|
||||||
|
|
|
@ -32,9 +32,11 @@ namespace clblast {
|
||||||
class Routine {
|
class Routine {
|
||||||
public:
|
public:
|
||||||
|
|
||||||
// Base class constructor
|
// Base class constructor. The user database is an optional extra database to override the
|
||||||
|
// built-in database.
|
||||||
explicit Routine(Queue &queue, EventPointer event, const std::string &name,
|
explicit Routine(Queue &queue, EventPointer event, const std::string &name,
|
||||||
const std::vector<std::string> &routines, const Precision precision);
|
const std::vector<std::string> &routines, const Precision precision,
|
||||||
|
const std::vector<Database::DatabaseEntry> &userDatabase = {});
|
||||||
|
|
||||||
// Set-up phase of the kernel
|
// Set-up phase of the kernel
|
||||||
StatusCode SetUp();
|
StatusCode SetUp();
|
||||||
|
|
|
@ -12,6 +12,7 @@
|
||||||
// =================================================================================================
|
// =================================================================================================
|
||||||
|
|
||||||
#include <vector>
|
#include <vector>
|
||||||
|
#include <chrono>
|
||||||
|
|
||||||
#include "routines/common.hpp"
|
#include "routines/common.hpp"
|
||||||
|
|
||||||
|
@ -21,8 +22,9 @@ namespace clblast {
|
||||||
// Enqueues a kernel, waits for completion, and checks for errors
|
// Enqueues a kernel, waits for completion, and checks for errors
|
||||||
StatusCode RunKernel(Kernel &kernel, Queue &queue, const Device &device,
|
StatusCode RunKernel(Kernel &kernel, Queue &queue, const Device &device,
|
||||||
std::vector<size_t> global, const std::vector<size_t> &local,
|
std::vector<size_t> global, const std::vector<size_t> &local,
|
||||||
EventPointer event, std::vector<Event>& waitForEvents) {
|
EventPointer event, const std::vector<Event> &waitForEvents) {
|
||||||
|
|
||||||
|
if (!local.empty()) {
|
||||||
// Tests for validity of the local thread sizes
|
// Tests for validity of the local thread sizes
|
||||||
if (local.size() > device.MaxWorkItemDimensions()) {
|
if (local.size() > device.MaxWorkItemDimensions()) {
|
||||||
return StatusCode::kInvalidLocalNumDimensions;
|
return StatusCode::kInvalidLocalNumDimensions;
|
||||||
|
@ -39,27 +41,35 @@ StatusCode RunKernel(Kernel &kernel, Queue &queue, const Device &device,
|
||||||
for (auto i=size_t{0}; i<global.size(); ++i) {
|
for (auto i=size_t{0}; i<global.size(); ++i) {
|
||||||
if (global[i] < local[i]) { global[i] = local[i]; }
|
if (global[i] < local[i]) { global[i] = local[i]; }
|
||||||
}
|
}
|
||||||
|
}
|
||||||
|
|
||||||
// Tests for local memory usage
|
// Tests for local memory usage
|
||||||
const auto local_mem_usage = kernel.LocalMemUsage(device);
|
const auto local_mem_usage = kernel.LocalMemUsage(device);
|
||||||
if (!device.IsLocalMemoryValid(local_mem_usage)) { return StatusCode::kInvalidLocalMemUsage; }
|
if (!device.IsLocalMemoryValid(local_mem_usage)) { return StatusCode::kInvalidLocalMemUsage; }
|
||||||
|
|
||||||
|
// Prints the name of the kernel to launch in case of debugging in verbose mode
|
||||||
|
#ifdef VERBOSE
|
||||||
|
queue.Finish();
|
||||||
|
printf("[DEBUG] Running kernel '%s'\n", kernel.GetFunctionName().c_str());
|
||||||
|
const auto start_time = std::chrono::steady_clock::now();
|
||||||
|
#endif
|
||||||
|
|
||||||
// Launches the kernel (and checks for launch errors)
|
// Launches the kernel (and checks for launch errors)
|
||||||
try {
|
try {
|
||||||
kernel.Launch(queue, global, local, event, waitForEvents);
|
kernel.Launch(queue, global, local, event, waitForEvents);
|
||||||
} catch (...) { return StatusCode::kKernelLaunchError; }
|
} catch (...) { return StatusCode::kKernelLaunchError; }
|
||||||
|
|
||||||
|
// Prints the elapsed execution time in case of debugging in verbose mode
|
||||||
|
#ifdef VERBOSE
|
||||||
|
queue.Finish();
|
||||||
|
const auto elapsed_time = std::chrono::steady_clock::now() - start_time;
|
||||||
|
const auto timing = std::chrono::duration<double,std::milli>(elapsed_time).count();
|
||||||
|
printf("[DEBUG] Completed kernel in %.2lf ms\n", timing);
|
||||||
|
#endif
|
||||||
|
|
||||||
// No errors, normal termination of this function
|
// No errors, normal termination of this function
|
||||||
return StatusCode::kSuccess;
|
return StatusCode::kSuccess;
|
||||||
}
|
}
|
||||||
|
|
||||||
// As above, but without an event waiting list
|
|
||||||
StatusCode RunKernel(Kernel &kernel, Queue &queue, const Device &device,
|
|
||||||
std::vector<size_t> global, const std::vector<size_t> &local,
|
|
||||||
EventPointer event) {
|
|
||||||
auto emptyWaitingList = std::vector<Event>();
|
|
||||||
return RunKernel(kernel, queue, device, global, local, event, emptyWaitingList);
|
|
||||||
}
|
|
||||||
|
|
||||||
// =================================================================================================
|
// =================================================================================================
|
||||||
} // namespace clblast
|
} // namespace clblast
|
||||||
|
|
|
@ -29,21 +29,16 @@ namespace clblast {
|
||||||
// Enqueues a kernel, waits for completion, and checks for errors
|
// Enqueues a kernel, waits for completion, and checks for errors
|
||||||
StatusCode RunKernel(Kernel &kernel, Queue &queue, const Device &device,
|
StatusCode RunKernel(Kernel &kernel, Queue &queue, const Device &device,
|
||||||
std::vector<size_t> global, const std::vector<size_t> &local,
|
std::vector<size_t> global, const std::vector<size_t> &local,
|
||||||
EventPointer event, std::vector<Event>& waitForEvents);
|
EventPointer event, const std::vector<Event> &waitForEvents = {});
|
||||||
|
|
||||||
// As above, but without an event waiting list
|
|
||||||
StatusCode RunKernel(Kernel &kernel, Queue &queue, const Device &device,
|
|
||||||
std::vector<size_t> global, const std::vector<size_t> &local,
|
|
||||||
EventPointer event);
|
|
||||||
|
|
||||||
// =================================================================================================
|
// =================================================================================================
|
||||||
|
|
||||||
// Copies or transposes a matrix and optionally pads/unpads it with zeros. This method is also able
|
// Copies or transposes a matrix and optionally pads/unpads it with zeros. This method is also able
|
||||||
// to write to symmetric and triangular matrices through optional arguments.
|
// to write to symmetric and triangular matrices through optional arguments.
|
||||||
template <typename T>
|
template <typename T>
|
||||||
StatusCode PadCopyTransposeMatrix(Queue &queue, const Device &device, const Context &context,
|
StatusCode PadCopyTransposeMatrix(Queue &queue, const Device &device,
|
||||||
const Database &db,
|
const Database &db,
|
||||||
EventPointer event, std::vector<Event>& waitForEvents,
|
EventPointer event, const std::vector<Event> &waitForEvents,
|
||||||
const size_t src_one, const size_t src_two,
|
const size_t src_one, const size_t src_two,
|
||||||
const size_t src_ld, const size_t src_offset,
|
const size_t src_ld, const size_t src_offset,
|
||||||
const Buffer<T> &src,
|
const Buffer<T> &src,
|
||||||
|
@ -88,10 +83,6 @@ StatusCode PadCopyTransposeMatrix(Queue &queue, const Device &device, const Cont
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
|
|
||||||
// Upload the scalar argument as a constant buffer to the device (needed for half-precision)
|
|
||||||
auto alpha_buffer = Buffer<T>(context, 1);
|
|
||||||
alpha_buffer.Write(queue, 1, &alpha);
|
|
||||||
|
|
||||||
// Retrieves the kernel from the compiled binary
|
// Retrieves the kernel from the compiled binary
|
||||||
try {
|
try {
|
||||||
auto kernel = Kernel(program, kernel_name);
|
auto kernel = Kernel(program, kernel_name);
|
||||||
|
@ -101,7 +92,7 @@ StatusCode PadCopyTransposeMatrix(Queue &queue, const Device &device, const Cont
|
||||||
kernel.SetArgument(0, static_cast<int>(src_ld));
|
kernel.SetArgument(0, static_cast<int>(src_ld));
|
||||||
kernel.SetArgument(1, src());
|
kernel.SetArgument(1, src());
|
||||||
kernel.SetArgument(2, dest());
|
kernel.SetArgument(2, dest());
|
||||||
kernel.SetArgument(3, alpha_buffer());
|
kernel.SetArgument(3, GetRealArg(alpha));
|
||||||
}
|
}
|
||||||
else {
|
else {
|
||||||
kernel.SetArgument(0, static_cast<int>(src_one));
|
kernel.SetArgument(0, static_cast<int>(src_one));
|
||||||
|
@ -114,7 +105,7 @@ StatusCode PadCopyTransposeMatrix(Queue &queue, const Device &device, const Cont
|
||||||
kernel.SetArgument(7, static_cast<int>(dest_ld));
|
kernel.SetArgument(7, static_cast<int>(dest_ld));
|
||||||
kernel.SetArgument(8, static_cast<int>(dest_offset));
|
kernel.SetArgument(8, static_cast<int>(dest_offset));
|
||||||
kernel.SetArgument(9, dest());
|
kernel.SetArgument(9, dest());
|
||||||
kernel.SetArgument(10, alpha_buffer());
|
kernel.SetArgument(10, GetRealArg(alpha));
|
||||||
if (do_pad) {
|
if (do_pad) {
|
||||||
kernel.SetArgument(11, static_cast<int>(do_conjugate));
|
kernel.SetArgument(11, static_cast<int>(do_conjugate));
|
||||||
}
|
}
|
||||||
|
|
|
@ -59,20 +59,16 @@ StatusCode Xaxpy<T>::DoAxpy(const size_t n, const T alpha,
|
||||||
const auto program = GetProgramFromCache(context_, PrecisionValue<T>(), routine_name_);
|
const auto program = GetProgramFromCache(context_, PrecisionValue<T>(), routine_name_);
|
||||||
auto kernel = Kernel(program, kernel_name);
|
auto kernel = Kernel(program, kernel_name);
|
||||||
|
|
||||||
// Upload the scalar argument as a constant buffer to the device (needed for half-precision)
|
|
||||||
auto alpha_buffer = Buffer<T>(context_, 1);
|
|
||||||
alpha_buffer.Write(queue_, 1, &alpha);
|
|
||||||
|
|
||||||
// Sets the kernel arguments
|
// Sets the kernel arguments
|
||||||
if (use_fast_kernel) {
|
if (use_fast_kernel) {
|
||||||
kernel.SetArgument(0, static_cast<int>(n));
|
kernel.SetArgument(0, static_cast<int>(n));
|
||||||
kernel.SetArgument(1, alpha_buffer());
|
kernel.SetArgument(1, GetRealArg(alpha));
|
||||||
kernel.SetArgument(2, x_buffer());
|
kernel.SetArgument(2, x_buffer());
|
||||||
kernel.SetArgument(3, y_buffer());
|
kernel.SetArgument(3, y_buffer());
|
||||||
}
|
}
|
||||||
else {
|
else {
|
||||||
kernel.SetArgument(0, static_cast<int>(n));
|
kernel.SetArgument(0, static_cast<int>(n));
|
||||||
kernel.SetArgument(1, alpha_buffer());
|
kernel.SetArgument(1, GetRealArg(alpha));
|
||||||
kernel.SetArgument(2, x_buffer());
|
kernel.SetArgument(2, x_buffer());
|
||||||
kernel.SetArgument(3, static_cast<int>(x_offset));
|
kernel.SetArgument(3, static_cast<int>(x_offset));
|
||||||
kernel.SetArgument(4, static_cast<int>(x_inc));
|
kernel.SetArgument(4, static_cast<int>(x_inc));
|
||||||
|
|
|
@ -22,7 +22,7 @@ namespace clblast {
|
||||||
// Constructor: forwards to base class constructor
|
// Constructor: forwards to base class constructor
|
||||||
template <typename T>
|
template <typename T>
|
||||||
Xgemv<T>::Xgemv(Queue &queue, EventPointer event, const std::string &name):
|
Xgemv<T>::Xgemv(Queue &queue, EventPointer event, const std::string &name):
|
||||||
Routine(queue, event, name, {"Pad", "Xgemv"}, PrecisionValue<T>()) {
|
Routine(queue, event, name, {"Pad", "Xgemv", "XgemvFast", "XgemvFastRot"}, PrecisionValue<T>()) {
|
||||||
source_string_ =
|
source_string_ =
|
||||||
#include "../../kernels/level2/xgemv.opencl"
|
#include "../../kernels/level2/xgemv.opencl"
|
||||||
#include "../../kernels/level2/xgemv_fast.opencl"
|
#include "../../kernels/level2/xgemv_fast.opencl"
|
||||||
|
@ -122,16 +122,10 @@ StatusCode Xgemv<T>::MatVec(const Layout layout, const Transpose a_transpose,
|
||||||
}
|
}
|
||||||
if (fast_kernel_rot) {
|
if (fast_kernel_rot) {
|
||||||
kernel_name = "XgemvFastRot";
|
kernel_name = "XgemvFastRot";
|
||||||
global_size = m_real / db_["WPT3"];
|
global_size = m_real;
|
||||||
local_size = db_["WGS3"];
|
local_size = db_["WGS3"];
|
||||||
}
|
}
|
||||||
|
|
||||||
// Upload the scalar arguments as constant buffers to the device (needed for half-precision)
|
|
||||||
auto alpha_buffer = Buffer<T>(context_, 1);
|
|
||||||
auto beta_buffer = Buffer<T>(context_, 1);
|
|
||||||
alpha_buffer.Write(queue_, 1, &alpha);
|
|
||||||
beta_buffer.Write(queue_, 1, &beta);
|
|
||||||
|
|
||||||
// Retrieves the Xgemv kernel from the compiled binary
|
// Retrieves the Xgemv kernel from the compiled binary
|
||||||
try {
|
try {
|
||||||
const auto program = GetProgramFromCache(context_, PrecisionValue<T>(), routine_name_);
|
const auto program = GetProgramFromCache(context_, PrecisionValue<T>(), routine_name_);
|
||||||
|
@ -140,8 +134,8 @@ StatusCode Xgemv<T>::MatVec(const Layout layout, const Transpose a_transpose,
|
||||||
// Sets the kernel arguments
|
// Sets the kernel arguments
|
||||||
kernel.SetArgument(0, static_cast<int>(m_real));
|
kernel.SetArgument(0, static_cast<int>(m_real));
|
||||||
kernel.SetArgument(1, static_cast<int>(n_real));
|
kernel.SetArgument(1, static_cast<int>(n_real));
|
||||||
kernel.SetArgument(2, alpha_buffer());
|
kernel.SetArgument(2, GetRealArg(alpha));
|
||||||
kernel.SetArgument(3, beta_buffer());
|
kernel.SetArgument(3, GetRealArg(beta));
|
||||||
kernel.SetArgument(4, static_cast<int>(a_rotated));
|
kernel.SetArgument(4, static_cast<int>(a_rotated));
|
||||||
kernel.SetArgument(5, a_buffer());
|
kernel.SetArgument(5, a_buffer());
|
||||||
kernel.SetArgument(6, static_cast<int>(a_offset));
|
kernel.SetArgument(6, static_cast<int>(a_offset));
|
||||||
|
|
|
@ -56,10 +56,6 @@ StatusCode Xger<T>::DoGer(const Layout layout,
|
||||||
status = TestVectorY(n, y_buffer, y_offset, y_inc);
|
status = TestVectorY(n, y_buffer, y_offset, y_inc);
|
||||||
if (ErrorIn(status)) { return status; }
|
if (ErrorIn(status)) { return status; }
|
||||||
|
|
||||||
// Upload the scalar argument as a constant buffer to the device (needed for half-precision)
|
|
||||||
auto alpha_buffer = Buffer<T>(context_, 1);
|
|
||||||
alpha_buffer.Write(queue_, 1, &alpha);
|
|
||||||
|
|
||||||
// Retrieves the kernel from the compiled binary
|
// Retrieves the kernel from the compiled binary
|
||||||
try {
|
try {
|
||||||
const auto program = GetProgramFromCache(context_, PrecisionValue<T>(), routine_name_);
|
const auto program = GetProgramFromCache(context_, PrecisionValue<T>(), routine_name_);
|
||||||
|
@ -68,7 +64,7 @@ StatusCode Xger<T>::DoGer(const Layout layout,
|
||||||
// Sets the kernel arguments
|
// Sets the kernel arguments
|
||||||
kernel.SetArgument(0, static_cast<int>(a_one));
|
kernel.SetArgument(0, static_cast<int>(a_one));
|
||||||
kernel.SetArgument(1, static_cast<int>(a_two));
|
kernel.SetArgument(1, static_cast<int>(a_two));
|
||||||
kernel.SetArgument(2, alpha_buffer());
|
kernel.SetArgument(2, GetRealArg(alpha));
|
||||||
kernel.SetArgument(3, x_buffer());
|
kernel.SetArgument(3, x_buffer());
|
||||||
kernel.SetArgument(4, static_cast<int>(x_offset));
|
kernel.SetArgument(4, static_cast<int>(x_offset));
|
||||||
kernel.SetArgument(5, static_cast<int>(x_inc));
|
kernel.SetArgument(5, static_cast<int>(x_inc));
|
||||||
|
|
|
@ -70,10 +70,6 @@ StatusCode Xher<T,U>::DoHer(const Layout layout, const Triangle triangle,
|
||||||
// Creates a matching version of alpha
|
// Creates a matching version of alpha
|
||||||
const auto matching_alpha = GetAlpha(alpha);
|
const auto matching_alpha = GetAlpha(alpha);
|
||||||
|
|
||||||
// Upload the scalar argument as a constant buffer to the device (needed for half-precision)
|
|
||||||
auto alpha_buffer = Buffer<T>(context_, 1);
|
|
||||||
alpha_buffer.Write(queue_, 1, &matching_alpha);
|
|
||||||
|
|
||||||
// Retrieves the kernel from the compiled binary
|
// Retrieves the kernel from the compiled binary
|
||||||
try {
|
try {
|
||||||
const auto program = GetProgramFromCache(context_, PrecisionValue<T>(), routine_name_);
|
const auto program = GetProgramFromCache(context_, PrecisionValue<T>(), routine_name_);
|
||||||
|
@ -81,7 +77,7 @@ StatusCode Xher<T,U>::DoHer(const Layout layout, const Triangle triangle,
|
||||||
|
|
||||||
// Sets the kernel arguments
|
// Sets the kernel arguments
|
||||||
kernel.SetArgument(0, static_cast<int>(n));
|
kernel.SetArgument(0, static_cast<int>(n));
|
||||||
kernel.SetArgument(1, alpha_buffer());
|
kernel.SetArgument(1, GetRealArg(matching_alpha));
|
||||||
kernel.SetArgument(2, x_buffer());
|
kernel.SetArgument(2, x_buffer());
|
||||||
kernel.SetArgument(3, static_cast<int>(x_offset));
|
kernel.SetArgument(3, static_cast<int>(x_offset));
|
||||||
kernel.SetArgument(4, static_cast<int>(x_inc));
|
kernel.SetArgument(4, static_cast<int>(x_inc));
|
||||||
|
|
|
@ -58,10 +58,6 @@ StatusCode Xher2<T>::DoHer2(const Layout layout, const Triangle triangle,
|
||||||
status = TestVectorY(n, y_buffer, y_offset, y_inc);
|
status = TestVectorY(n, y_buffer, y_offset, y_inc);
|
||||||
if (ErrorIn(status)) { return status; }
|
if (ErrorIn(status)) { return status; }
|
||||||
|
|
||||||
// Upload the scalar argument as a constant buffer to the device (needed for half-precision)
|
|
||||||
auto alpha_buffer = Buffer<T>(context_, 1);
|
|
||||||
alpha_buffer.Write(queue_, 1, &alpha);
|
|
||||||
|
|
||||||
// Retrieves the kernel from the compiled binary
|
// Retrieves the kernel from the compiled binary
|
||||||
try {
|
try {
|
||||||
const auto program = GetProgramFromCache(context_, PrecisionValue<T>(), routine_name_);
|
const auto program = GetProgramFromCache(context_, PrecisionValue<T>(), routine_name_);
|
||||||
|
@ -69,7 +65,7 @@ StatusCode Xher2<T>::DoHer2(const Layout layout, const Triangle triangle,
|
||||||
|
|
||||||
// Sets the kernel arguments
|
// Sets the kernel arguments
|
||||||
kernel.SetArgument(0, static_cast<int>(n));
|
kernel.SetArgument(0, static_cast<int>(n));
|
||||||
kernel.SetArgument(1, alpha_buffer());
|
kernel.SetArgument(1, GetRealArg(alpha));
|
||||||
kernel.SetArgument(2, x_buffer());
|
kernel.SetArgument(2, x_buffer());
|
||||||
kernel.SetArgument(3, static_cast<int>(x_offset));
|
kernel.SetArgument(3, static_cast<int>(x_offset));
|
||||||
kernel.SetArgument(4, static_cast<int>(x_inc));
|
kernel.SetArgument(4, static_cast<int>(x_inc));
|
||||||
|
|
|
@ -34,6 +34,7 @@ Xgemm<T>::Xgemm(Queue &queue, EventPointer event, const std::string &name):
|
||||||
#include "../../kernels/level3/convert_hermitian.opencl"
|
#include "../../kernels/level3/convert_hermitian.opencl"
|
||||||
#include "../../kernels/level3/xgemm_part1.opencl"
|
#include "../../kernels/level3/xgemm_part1.opencl"
|
||||||
#include "../../kernels/level3/xgemm_part2.opencl"
|
#include "../../kernels/level3/xgemm_part2.opencl"
|
||||||
|
#include "../../kernels/level3/xgemm_part3.opencl"
|
||||||
;
|
;
|
||||||
}
|
}
|
||||||
|
|
||||||
|
@ -63,9 +64,12 @@ StatusCode Xgemm<T>::DoGemm(const Layout layout,
|
||||||
const auto b_rotated = (layout == Layout::kColMajor && b_transpose != Transpose::kNo) ||
|
const auto b_rotated = (layout == Layout::kColMajor && b_transpose != Transpose::kNo) ||
|
||||||
(layout == Layout::kRowMajor && b_transpose == Transpose::kNo);
|
(layout == Layout::kRowMajor && b_transpose == Transpose::kNo);
|
||||||
const auto c_rotated = (layout == Layout::kRowMajor);
|
const auto c_rotated = (layout == Layout::kRowMajor);
|
||||||
const auto a_do_transpose = a_rotated;
|
static const auto a_want_rotated = false;
|
||||||
const auto b_do_transpose = !b_rotated;
|
static const auto b_want_rotated = true;
|
||||||
const auto c_do_transpose = c_rotated;
|
static const auto c_want_rotated = false;
|
||||||
|
const auto a_do_transpose = a_rotated != a_want_rotated;
|
||||||
|
const auto b_do_transpose = b_rotated != b_want_rotated;
|
||||||
|
const auto c_do_transpose = c_rotated != c_want_rotated;
|
||||||
|
|
||||||
// In case of complex data-types, the transpose can also become a conjugate transpose
|
// In case of complex data-types, the transpose can also become a conjugate transpose
|
||||||
const auto a_conjugate = (a_transpose == Transpose::kConjugate);
|
const auto a_conjugate = (a_transpose == Transpose::kConjugate);
|
||||||
|
@ -99,6 +103,15 @@ StatusCode Xgemm<T>::DoGemm(const Layout layout,
|
||||||
const auto n_ceiled = Ceil(n, db_["NWG"]);
|
const auto n_ceiled = Ceil(n, db_["NWG"]);
|
||||||
const auto k_ceiled = Ceil(k, db_["KWG"]);
|
const auto k_ceiled = Ceil(k, db_["KWG"]);
|
||||||
|
|
||||||
|
// Computes the first and second "internal" (ceiled) dimensions of the 3 matrices taking into account
|
||||||
|
// whether the matrices need to be rotated or not for the kernel.
|
||||||
|
const auto a_one_i = (a_want_rotated) ? k_ceiled : m_ceiled;
|
||||||
|
const auto a_two_i = (a_want_rotated) ? m_ceiled : k_ceiled;
|
||||||
|
const auto b_one_i = (b_want_rotated) ? n_ceiled : k_ceiled;
|
||||||
|
const auto b_two_i = (b_want_rotated) ? k_ceiled : n_ceiled;
|
||||||
|
const auto c_one_i = (c_want_rotated) ? n_ceiled : m_ceiled;
|
||||||
|
const auto c_two_i = (c_want_rotated) ? m_ceiled : n_ceiled;
|
||||||
|
|
||||||
// The padded/transposed input/output matrices: if memory allocation fails, throw an exception
|
// The padded/transposed input/output matrices: if memory allocation fails, throw an exception
|
||||||
try {
|
try {
|
||||||
|
|
||||||
|
@ -106,23 +119,17 @@ StatusCode Xgemm<T>::DoGemm(const Layout layout,
|
||||||
const auto program = GetProgramFromCache(context_, PrecisionValue<T>(), routine_name_);
|
const auto program = GetProgramFromCache(context_, PrecisionValue<T>(), routine_name_);
|
||||||
|
|
||||||
// Determines whether or not temporary matrices are needed
|
// Determines whether or not temporary matrices are needed
|
||||||
auto a_no_temp = a_one == m_ceiled && a_two == k_ceiled && a_ld == m_ceiled && a_offset == 0 &&
|
auto a_no_temp = a_one == a_one_i && a_two == a_two_i && a_ld == a_one && a_offset == 0 &&
|
||||||
a_do_transpose == false && a_conjugate == false;
|
a_do_transpose == false && a_conjugate == false;
|
||||||
auto b_no_temp = b_one == n_ceiled && b_two == k_ceiled && b_ld == n_ceiled && b_offset == 0 &&
|
auto b_no_temp = b_one == b_one_i && b_two == b_two_i && b_ld == b_one && b_offset == 0 &&
|
||||||
b_do_transpose == false && b_conjugate == false;
|
b_do_transpose == false && b_conjugate == false;
|
||||||
auto c_no_temp = c_one == m_ceiled && c_two == n_ceiled && c_ld == m_ceiled && c_offset == 0 &&
|
auto c_no_temp = c_one == c_one_i && c_two == c_two_i && c_ld == c_one && c_offset == 0 &&
|
||||||
c_do_transpose == false;
|
c_do_transpose == false;
|
||||||
|
|
||||||
// Creates the temporary matrices
|
// Creates the temporary matrices
|
||||||
const auto a_temp = (a_no_temp) ? a_buffer : Buffer<T>(context_, k_ceiled*m_ceiled);
|
const auto a_temp = (a_no_temp) ? a_buffer : Buffer<T>(context_, a_one_i*a_two_i);
|
||||||
const auto b_temp = (b_no_temp) ? b_buffer : Buffer<T>(context_, k_ceiled*n_ceiled);
|
const auto b_temp = (b_no_temp) ? b_buffer : Buffer<T>(context_, b_one_i*b_two_i);
|
||||||
const auto c_temp = (c_no_temp) ? c_buffer : Buffer<T>(context_, m_ceiled*n_ceiled);
|
const auto c_temp = (c_no_temp) ? c_buffer : Buffer<T>(context_, c_one_i*c_two_i);
|
||||||
|
|
||||||
// Upload the scalar arguments as constant buffers to the device (needed for half-precision)
|
|
||||||
auto alpha_buffer = Buffer<T>(context_, 1);
|
|
||||||
auto beta_buffer = Buffer<T>(context_, 1);
|
|
||||||
alpha_buffer.Write(queue_, 1, &alpha);
|
|
||||||
beta_buffer.Write(queue_, 1, &beta);
|
|
||||||
|
|
||||||
// Events of all kernels (including pre/post processing kernels)
|
// Events of all kernels (including pre/post processing kernels)
|
||||||
auto eventWaitList = std::vector<Event>();
|
auto eventWaitList = std::vector<Event>();
|
||||||
|
@ -133,9 +140,9 @@ StatusCode Xgemm<T>::DoGemm(const Layout layout,
|
||||||
// case nothing has to be done, these kernels can be skipped.
|
// case nothing has to be done, these kernels can be skipped.
|
||||||
if (!a_no_temp) {
|
if (!a_no_temp) {
|
||||||
auto eventProcessA = Event();
|
auto eventProcessA = Event();
|
||||||
status = PadCopyTransposeMatrix(queue_, device_, context_, db_, eventProcessA.pointer(), emptyEventList,
|
status = PadCopyTransposeMatrix(queue_, device_, db_, eventProcessA.pointer(), emptyEventList,
|
||||||
a_one, a_two, a_ld, a_offset, a_buffer,
|
a_one, a_two, a_ld, a_offset, a_buffer,
|
||||||
m_ceiled, k_ceiled, m_ceiled, 0, a_temp,
|
a_one_i, a_two_i, a_one_i, 0, a_temp,
|
||||||
ConstantOne<T>(), program,
|
ConstantOne<T>(), program,
|
||||||
true, a_do_transpose, a_conjugate);
|
true, a_do_transpose, a_conjugate);
|
||||||
if (ErrorIn(status)) { return status; }
|
if (ErrorIn(status)) { return status; }
|
||||||
|
@ -145,9 +152,9 @@ StatusCode Xgemm<T>::DoGemm(const Layout layout,
|
||||||
// As above, but now for matrix B
|
// As above, but now for matrix B
|
||||||
if (!b_no_temp) {
|
if (!b_no_temp) {
|
||||||
auto eventProcessB = Event();
|
auto eventProcessB = Event();
|
||||||
status = PadCopyTransposeMatrix(queue_, device_, context_, db_, eventProcessB.pointer(), emptyEventList,
|
status = PadCopyTransposeMatrix(queue_, device_, db_, eventProcessB.pointer(), emptyEventList,
|
||||||
b_one, b_two, b_ld, b_offset, b_buffer,
|
b_one, b_two, b_ld, b_offset, b_buffer,
|
||||||
n_ceiled, k_ceiled, n_ceiled, 0, b_temp,
|
b_one_i, b_two_i, b_one_i, 0, b_temp,
|
||||||
ConstantOne<T>(), program,
|
ConstantOne<T>(), program,
|
||||||
true, b_do_transpose, b_conjugate);
|
true, b_do_transpose, b_conjugate);
|
||||||
if (ErrorIn(status)) { return status; }
|
if (ErrorIn(status)) { return status; }
|
||||||
|
@ -157,9 +164,9 @@ StatusCode Xgemm<T>::DoGemm(const Layout layout,
|
||||||
// As above, but now for matrix C. This is only necessary if C is used both as input and output.
|
// As above, but now for matrix C. This is only necessary if C is used both as input and output.
|
||||||
if (!c_no_temp && beta != static_cast<T>(0)) {
|
if (!c_no_temp && beta != static_cast<T>(0)) {
|
||||||
auto eventProcessC = Event();
|
auto eventProcessC = Event();
|
||||||
status = PadCopyTransposeMatrix(queue_, device_, context_, db_, eventProcessC.pointer(), emptyEventList,
|
status = PadCopyTransposeMatrix(queue_, device_, db_, eventProcessC.pointer(), emptyEventList,
|
||||||
c_one, c_two, c_ld, c_offset, c_buffer,
|
c_one, c_two, c_ld, c_offset, c_buffer,
|
||||||
m_ceiled, n_ceiled, m_ceiled, 0, c_temp,
|
c_one_i, c_two_i, c_one_i, 0, c_temp,
|
||||||
ConstantOne<T>(), program,
|
ConstantOne<T>(), program,
|
||||||
true, c_do_transpose, false);
|
true, c_do_transpose, false);
|
||||||
if (ErrorIn(status)) { return status; }
|
if (ErrorIn(status)) { return status; }
|
||||||
|
@ -174,16 +181,16 @@ StatusCode Xgemm<T>::DoGemm(const Layout layout,
|
||||||
kernel.SetArgument(0, static_cast<int>(m_ceiled));
|
kernel.SetArgument(0, static_cast<int>(m_ceiled));
|
||||||
kernel.SetArgument(1, static_cast<int>(n_ceiled));
|
kernel.SetArgument(1, static_cast<int>(n_ceiled));
|
||||||
kernel.SetArgument(2, static_cast<int>(k_ceiled));
|
kernel.SetArgument(2, static_cast<int>(k_ceiled));
|
||||||
kernel.SetArgument(3, alpha_buffer());
|
kernel.SetArgument(3, GetRealArg(alpha));
|
||||||
kernel.SetArgument(4, beta_buffer());
|
kernel.SetArgument(4, GetRealArg(beta));
|
||||||
kernel.SetArgument(5, a_temp());
|
kernel.SetArgument(5, a_temp());
|
||||||
kernel.SetArgument(6, b_temp());
|
kernel.SetArgument(6, b_temp());
|
||||||
kernel.SetArgument(7, c_temp());
|
kernel.SetArgument(7, c_temp());
|
||||||
|
|
||||||
// Computes the global and local thread sizes
|
// Computes the global and local thread sizes
|
||||||
const auto global = std::vector<size_t>{
|
const auto global = std::vector<size_t>{
|
||||||
(m_ceiled * db_["MDIMC"]) / db_["MWG"],
|
(c_one_i * db_["MDIMC"]) / db_["MWG"],
|
||||||
(n_ceiled * db_["NDIMC"]) / db_["NWG"]
|
(c_two_i * db_["NDIMC"]) / db_["NWG"]
|
||||||
};
|
};
|
||||||
const auto local = std::vector<size_t>{db_["MDIMC"], db_["NDIMC"]};
|
const auto local = std::vector<size_t>{db_["MDIMC"], db_["NDIMC"]};
|
||||||
|
|
||||||
|
@ -196,8 +203,8 @@ StatusCode Xgemm<T>::DoGemm(const Layout layout,
|
||||||
// Runs the post-processing kernel if needed
|
// Runs the post-processing kernel if needed
|
||||||
if (!c_no_temp) {
|
if (!c_no_temp) {
|
||||||
eventWaitList.push_back(eventKernel);
|
eventWaitList.push_back(eventKernel);
|
||||||
status = PadCopyTransposeMatrix(queue_, device_, context_, db_, event_, eventWaitList,
|
status = PadCopyTransposeMatrix(queue_, device_, db_, event_, eventWaitList,
|
||||||
m_ceiled, n_ceiled, m_ceiled, 0, c_temp,
|
c_one_i, c_two_i, c_one_i, 0, c_temp,
|
||||||
c_one, c_two, c_ld, c_offset, c_buffer,
|
c_one, c_two, c_ld, c_offset, c_buffer,
|
||||||
ConstantOne<T>(), program,
|
ConstantOne<T>(), program,
|
||||||
false, c_do_transpose, false);
|
false, c_do_transpose, false);
|
||||||
|
|
|
@ -31,6 +31,7 @@ Xher2k<T,U>::Xher2k(Queue &queue, EventPointer event, const std::string &name):
|
||||||
#include "../../kernels/level3/transpose_pad.opencl"
|
#include "../../kernels/level3/transpose_pad.opencl"
|
||||||
#include "../../kernels/level3/xgemm_part1.opencl"
|
#include "../../kernels/level3/xgemm_part1.opencl"
|
||||||
#include "../../kernels/level3/xgemm_part2.opencl"
|
#include "../../kernels/level3/xgemm_part2.opencl"
|
||||||
|
#include "../../kernels/level3/xgemm_part3.opencl"
|
||||||
;
|
;
|
||||||
}
|
}
|
||||||
|
|
||||||
|
@ -107,12 +108,8 @@ StatusCode Xher2k<T,U>::DoHer2k(const Layout layout, const Triangle triangle, co
|
||||||
auto b2_temp = (b2_no_temp) ? b_buffer : Buffer<T>(context_, k_ceiled*n_ceiled);
|
auto b2_temp = (b2_no_temp) ? b_buffer : Buffer<T>(context_, k_ceiled*n_ceiled);
|
||||||
auto c_temp = Buffer<T>(context_, n_ceiled*n_ceiled);
|
auto c_temp = Buffer<T>(context_, n_ceiled*n_ceiled);
|
||||||
|
|
||||||
// Upload the scalar arguments as constant buffers to the device (needed for half-precision)
|
// Convert the arguments to complex versions
|
||||||
auto complex_beta = T{beta, static_cast<U>(0.0)};
|
auto complex_beta = T{beta, static_cast<U>(0.0)};
|
||||||
auto alpha_buffer = Buffer<T>(context_, 1);
|
|
||||||
auto beta_buffer = Buffer<T>(context_, 1);
|
|
||||||
alpha_buffer.Write(queue_, 1, &alpha);
|
|
||||||
beta_buffer.Write(queue_, 1, &complex_beta);
|
|
||||||
|
|
||||||
// Events of all kernels (including pre/post processing kernels)
|
// Events of all kernels (including pre/post processing kernels)
|
||||||
auto eventWaitList = std::vector<Event>();
|
auto eventWaitList = std::vector<Event>();
|
||||||
|
@ -123,7 +120,7 @@ StatusCode Xher2k<T,U>::DoHer2k(const Layout layout, const Triangle triangle, co
|
||||||
// case nothing has to be done, these kernels can be skipped.
|
// case nothing has to be done, these kernels can be skipped.
|
||||||
if (!a1_no_temp) {
|
if (!a1_no_temp) {
|
||||||
auto eventProcessA1 = Event();
|
auto eventProcessA1 = Event();
|
||||||
status = PadCopyTransposeMatrix(queue_, device_, context_, db_, eventProcessA1.pointer(), emptyEventList,
|
status = PadCopyTransposeMatrix(queue_, device_, db_, eventProcessA1.pointer(), emptyEventList,
|
||||||
ab_one, ab_two, a_ld, a_offset, a_buffer,
|
ab_one, ab_two, a_ld, a_offset, a_buffer,
|
||||||
n_ceiled, k_ceiled, n_ceiled, 0, a1_temp,
|
n_ceiled, k_ceiled, n_ceiled, 0, a1_temp,
|
||||||
ConstantOne<T>(), program,
|
ConstantOne<T>(), program,
|
||||||
|
@ -133,7 +130,7 @@ StatusCode Xher2k<T,U>::DoHer2k(const Layout layout, const Triangle triangle, co
|
||||||
}
|
}
|
||||||
if (!a2_no_temp) {
|
if (!a2_no_temp) {
|
||||||
auto eventProcessA2 = Event();
|
auto eventProcessA2 = Event();
|
||||||
status = PadCopyTransposeMatrix(queue_, device_, context_, db_, eventProcessA2.pointer(), emptyEventList,
|
status = PadCopyTransposeMatrix(queue_, device_, db_, eventProcessA2.pointer(), emptyEventList,
|
||||||
ab_one, ab_two, a_ld, a_offset, a_buffer,
|
ab_one, ab_two, a_ld, a_offset, a_buffer,
|
||||||
n_ceiled, k_ceiled, n_ceiled, 0, a2_temp,
|
n_ceiled, k_ceiled, n_ceiled, 0, a2_temp,
|
||||||
ConstantOne<T>(), program,
|
ConstantOne<T>(), program,
|
||||||
|
@ -143,7 +140,7 @@ StatusCode Xher2k<T,U>::DoHer2k(const Layout layout, const Triangle triangle, co
|
||||||
}
|
}
|
||||||
if (!b1_no_temp) {
|
if (!b1_no_temp) {
|
||||||
auto eventProcessB1 = Event();
|
auto eventProcessB1 = Event();
|
||||||
status = PadCopyTransposeMatrix(queue_, device_, context_, db_, eventProcessB1.pointer(), emptyEventList,
|
status = PadCopyTransposeMatrix(queue_, device_, db_, eventProcessB1.pointer(), emptyEventList,
|
||||||
ab_one, ab_two, b_ld, b_offset, b_buffer,
|
ab_one, ab_two, b_ld, b_offset, b_buffer,
|
||||||
n_ceiled, k_ceiled, n_ceiled, 0, b1_temp,
|
n_ceiled, k_ceiled, n_ceiled, 0, b1_temp,
|
||||||
ConstantOne<T>(), program,
|
ConstantOne<T>(), program,
|
||||||
|
@ -153,7 +150,7 @@ StatusCode Xher2k<T,U>::DoHer2k(const Layout layout, const Triangle triangle, co
|
||||||
}
|
}
|
||||||
if (!b2_no_temp) {
|
if (!b2_no_temp) {
|
||||||
auto eventProcessB2 = Event();
|
auto eventProcessB2 = Event();
|
||||||
status = PadCopyTransposeMatrix(queue_, device_, context_, db_, eventProcessB2.pointer(), emptyEventList,
|
status = PadCopyTransposeMatrix(queue_, device_, db_, eventProcessB2.pointer(), emptyEventList,
|
||||||
ab_one, ab_two, b_ld, b_offset, b_buffer,
|
ab_one, ab_two, b_ld, b_offset, b_buffer,
|
||||||
n_ceiled, k_ceiled, n_ceiled, 0, b2_temp,
|
n_ceiled, k_ceiled, n_ceiled, 0, b2_temp,
|
||||||
ConstantOne<T>(), program,
|
ConstantOne<T>(), program,
|
||||||
|
@ -165,7 +162,7 @@ StatusCode Xher2k<T,U>::DoHer2k(const Layout layout, const Triangle triangle, co
|
||||||
// Furthermore, also creates a (possibly padded) copy of matrix C, since it is not allowed to
|
// Furthermore, also creates a (possibly padded) copy of matrix C, since it is not allowed to
|
||||||
// modify the other triangle.
|
// modify the other triangle.
|
||||||
auto eventProcessC = Event();
|
auto eventProcessC = Event();
|
||||||
status = PadCopyTransposeMatrix(queue_, device_, context_, db_, eventProcessC.pointer(), emptyEventList,
|
status = PadCopyTransposeMatrix(queue_, device_, db_, eventProcessC.pointer(), emptyEventList,
|
||||||
n, n, c_ld, c_offset, c_buffer,
|
n, n, c_ld, c_offset, c_buffer,
|
||||||
n_ceiled, n_ceiled, n_ceiled, 0, c_temp,
|
n_ceiled, n_ceiled, n_ceiled, 0, c_temp,
|
||||||
ConstantOne<T>(), program,
|
ConstantOne<T>(), program,
|
||||||
|
@ -180,8 +177,8 @@ StatusCode Xher2k<T,U>::DoHer2k(const Layout layout, const Triangle triangle, co
|
||||||
// Sets the kernel arguments
|
// Sets the kernel arguments
|
||||||
kernel.SetArgument(0, static_cast<int>(n_ceiled));
|
kernel.SetArgument(0, static_cast<int>(n_ceiled));
|
||||||
kernel.SetArgument(1, static_cast<int>(k_ceiled));
|
kernel.SetArgument(1, static_cast<int>(k_ceiled));
|
||||||
kernel.SetArgument(2, alpha_buffer());
|
kernel.SetArgument(2, GetRealArg(alpha));
|
||||||
kernel.SetArgument(3, beta_buffer());
|
kernel.SetArgument(3, GetRealArg(complex_beta));
|
||||||
kernel.SetArgument(4, a1_temp());
|
kernel.SetArgument(4, a1_temp());
|
||||||
kernel.SetArgument(5, b2_temp());
|
kernel.SetArgument(5, b2_temp());
|
||||||
kernel.SetArgument(6, c_temp());
|
kernel.SetArgument(6, c_temp());
|
||||||
|
@ -202,10 +199,8 @@ StatusCode Xher2k<T,U>::DoHer2k(const Layout layout, const Triangle triangle, co
|
||||||
// Swaps the arguments for matrices A and B, sets 'beta' to 1, and conjugate alpha
|
// Swaps the arguments for matrices A and B, sets 'beta' to 1, and conjugate alpha
|
||||||
auto conjugate_alpha = T{alpha.real(), -alpha.imag()};
|
auto conjugate_alpha = T{alpha.real(), -alpha.imag()};
|
||||||
auto complex_one = T{static_cast<U>(1.0), static_cast<U>(0.0)};
|
auto complex_one = T{static_cast<U>(1.0), static_cast<U>(0.0)};
|
||||||
alpha_buffer.Write(queue_, 1, &conjugate_alpha);
|
kernel.SetArgument(2, GetRealArg(conjugate_alpha));
|
||||||
beta_buffer.Write(queue_, 1, &complex_one);
|
kernel.SetArgument(3, GetRealArg(complex_one));
|
||||||
kernel.SetArgument(2, alpha_buffer());
|
|
||||||
kernel.SetArgument(3, beta_buffer());
|
|
||||||
kernel.SetArgument(4, b1_temp());
|
kernel.SetArgument(4, b1_temp());
|
||||||
kernel.SetArgument(5, a2_temp());
|
kernel.SetArgument(5, a2_temp());
|
||||||
|
|
||||||
|
@ -218,7 +213,7 @@ StatusCode Xher2k<T,U>::DoHer2k(const Layout layout, const Triangle triangle, co
|
||||||
// Runs the post-processing kernel
|
// Runs the post-processing kernel
|
||||||
auto upper = (triangle == Triangle::kUpper);
|
auto upper = (triangle == Triangle::kUpper);
|
||||||
auto lower = (triangle == Triangle::kLower);
|
auto lower = (triangle == Triangle::kLower);
|
||||||
status = PadCopyTransposeMatrix(queue_, device_, context_, db_, event_, eventWaitList,
|
status = PadCopyTransposeMatrix(queue_, device_, db_, event_, eventWaitList,
|
||||||
n_ceiled, n_ceiled, n_ceiled, 0, c_temp,
|
n_ceiled, n_ceiled, n_ceiled, 0, c_temp,
|
||||||
n, n, c_ld, c_offset, c_buffer,
|
n, n, c_ld, c_offset, c_buffer,
|
||||||
ConstantOne<T>(), program,
|
ConstantOne<T>(), program,
|
||||||
|
|
|
@ -31,6 +31,7 @@ Xherk<T,U>::Xherk(Queue &queue, EventPointer event, const std::string &name):
|
||||||
#include "../../kernels/level3/transpose_pad.opencl"
|
#include "../../kernels/level3/transpose_pad.opencl"
|
||||||
#include "../../kernels/level3/xgemm_part1.opencl"
|
#include "../../kernels/level3/xgemm_part1.opencl"
|
||||||
#include "../../kernels/level3/xgemm_part2.opencl"
|
#include "../../kernels/level3/xgemm_part2.opencl"
|
||||||
|
#include "../../kernels/level3/xgemm_part3.opencl"
|
||||||
;
|
;
|
||||||
}
|
}
|
||||||
|
|
||||||
|
@ -98,13 +99,9 @@ StatusCode Xherk<T,U>::DoHerk(const Layout layout, const Triangle triangle, cons
|
||||||
auto b_temp = (b_no_temp) ? a_buffer : Buffer<T>(context_, k_ceiled*n_ceiled);
|
auto b_temp = (b_no_temp) ? a_buffer : Buffer<T>(context_, k_ceiled*n_ceiled);
|
||||||
auto c_temp = Buffer<T>(context_, n_ceiled*n_ceiled);
|
auto c_temp = Buffer<T>(context_, n_ceiled*n_ceiled);
|
||||||
|
|
||||||
// Upload the scalar arguments as constant buffers to the device (needed for half-precision)
|
// Convert the arguments to complex versions
|
||||||
auto complex_alpha = T{alpha, static_cast<U>(0.0)};
|
auto complex_alpha = T{alpha, static_cast<U>(0.0)};
|
||||||
auto complex_beta = T{beta, static_cast<U>(0.0)};
|
auto complex_beta = T{beta, static_cast<U>(0.0)};
|
||||||
auto alpha_buffer = Buffer<T>(context_, 1);
|
|
||||||
auto beta_buffer = Buffer<T>(context_, 1);
|
|
||||||
alpha_buffer.Write(queue_, 1, &complex_alpha);
|
|
||||||
beta_buffer.Write(queue_, 1, &complex_beta);
|
|
||||||
|
|
||||||
// Events of all kernels (including pre/post processing kernels)
|
// Events of all kernels (including pre/post processing kernels)
|
||||||
auto eventWaitList = std::vector<Event>();
|
auto eventWaitList = std::vector<Event>();
|
||||||
|
@ -115,7 +112,7 @@ StatusCode Xherk<T,U>::DoHerk(const Layout layout, const Triangle triangle, cons
|
||||||
// case nothing has to be done, these kernels can be skipped. Two copies are created.
|
// case nothing has to be done, these kernels can be skipped. Two copies are created.
|
||||||
if (!a_no_temp) {
|
if (!a_no_temp) {
|
||||||
auto eventProcessA = Event();
|
auto eventProcessA = Event();
|
||||||
status = PadCopyTransposeMatrix(queue_, device_, context_, db_, eventProcessA.pointer(), emptyEventList,
|
status = PadCopyTransposeMatrix(queue_, device_, db_, eventProcessA.pointer(), emptyEventList,
|
||||||
a_one, a_two, a_ld, a_offset, a_buffer,
|
a_one, a_two, a_ld, a_offset, a_buffer,
|
||||||
n_ceiled, k_ceiled, n_ceiled, 0, a_temp,
|
n_ceiled, k_ceiled, n_ceiled, 0, a_temp,
|
||||||
ConstantOne<T>(), program,
|
ConstantOne<T>(), program,
|
||||||
|
@ -125,7 +122,7 @@ StatusCode Xherk<T,U>::DoHerk(const Layout layout, const Triangle triangle, cons
|
||||||
}
|
}
|
||||||
if (!b_no_temp) {
|
if (!b_no_temp) {
|
||||||
auto eventProcessB = Event();
|
auto eventProcessB = Event();
|
||||||
status = PadCopyTransposeMatrix(queue_, device_, context_, db_, eventProcessB.pointer(), emptyEventList,
|
status = PadCopyTransposeMatrix(queue_, device_, db_, eventProcessB.pointer(), emptyEventList,
|
||||||
a_one, a_two, a_ld, a_offset, a_buffer,
|
a_one, a_two, a_ld, a_offset, a_buffer,
|
||||||
n_ceiled, k_ceiled, n_ceiled, 0, b_temp,
|
n_ceiled, k_ceiled, n_ceiled, 0, b_temp,
|
||||||
ConstantOne<T>(), program,
|
ConstantOne<T>(), program,
|
||||||
|
@ -137,7 +134,7 @@ StatusCode Xherk<T,U>::DoHerk(const Layout layout, const Triangle triangle, cons
|
||||||
// Furthermore, also creates a (possibly padded) copy of matrix C, since it is not allowed to
|
// Furthermore, also creates a (possibly padded) copy of matrix C, since it is not allowed to
|
||||||
// modify the other triangle.
|
// modify the other triangle.
|
||||||
auto eventProcessC = Event();
|
auto eventProcessC = Event();
|
||||||
status = PadCopyTransposeMatrix(queue_, device_, context_, db_, eventProcessC.pointer(), emptyEventList,
|
status = PadCopyTransposeMatrix(queue_, device_, db_, eventProcessC.pointer(), emptyEventList,
|
||||||
n, n, c_ld, c_offset, c_buffer,
|
n, n, c_ld, c_offset, c_buffer,
|
||||||
n_ceiled, n_ceiled, n_ceiled, 0, c_temp,
|
n_ceiled, n_ceiled, n_ceiled, 0, c_temp,
|
||||||
ConstantOne<T>(), program,
|
ConstantOne<T>(), program,
|
||||||
|
@ -152,8 +149,8 @@ StatusCode Xherk<T,U>::DoHerk(const Layout layout, const Triangle triangle, cons
|
||||||
// Sets the kernel arguments
|
// Sets the kernel arguments
|
||||||
kernel.SetArgument(0, static_cast<int>(n_ceiled));
|
kernel.SetArgument(0, static_cast<int>(n_ceiled));
|
||||||
kernel.SetArgument(1, static_cast<int>(k_ceiled));
|
kernel.SetArgument(1, static_cast<int>(k_ceiled));
|
||||||
kernel.SetArgument(2, alpha_buffer());
|
kernel.SetArgument(2, GetRealArg(complex_alpha));
|
||||||
kernel.SetArgument(3, beta_buffer());
|
kernel.SetArgument(3, GetRealArg(complex_beta));
|
||||||
kernel.SetArgument(4, a_temp());
|
kernel.SetArgument(4, a_temp());
|
||||||
kernel.SetArgument(5, b_temp());
|
kernel.SetArgument(5, b_temp());
|
||||||
kernel.SetArgument(6, c_temp());
|
kernel.SetArgument(6, c_temp());
|
||||||
|
@ -174,7 +171,7 @@ StatusCode Xherk<T,U>::DoHerk(const Layout layout, const Triangle triangle, cons
|
||||||
// Runs the post-processing kernel
|
// Runs the post-processing kernel
|
||||||
auto upper = (triangle == Triangle::kUpper);
|
auto upper = (triangle == Triangle::kUpper);
|
||||||
auto lower = (triangle == Triangle::kLower);
|
auto lower = (triangle == Triangle::kLower);
|
||||||
status = PadCopyTransposeMatrix(queue_, device_, context_, db_, event_, eventWaitList,
|
status = PadCopyTransposeMatrix(queue_, device_, db_, event_, eventWaitList,
|
||||||
n_ceiled, n_ceiled, n_ceiled, 0, c_temp,
|
n_ceiled, n_ceiled, n_ceiled, 0, c_temp,
|
||||||
n, n, c_ld, c_offset, c_buffer,
|
n, n, c_ld, c_offset, c_buffer,
|
||||||
ConstantOne<T>(), program,
|
ConstantOne<T>(), program,
|
||||||
|
|
|
@ -31,6 +31,7 @@ Xsyr2k<T>::Xsyr2k(Queue &queue, EventPointer event, const std::string &name):
|
||||||
#include "../../kernels/level3/transpose_pad.opencl"
|
#include "../../kernels/level3/transpose_pad.opencl"
|
||||||
#include "../../kernels/level3/xgemm_part1.opencl"
|
#include "../../kernels/level3/xgemm_part1.opencl"
|
||||||
#include "../../kernels/level3/xgemm_part2.opencl"
|
#include "../../kernels/level3/xgemm_part2.opencl"
|
||||||
|
#include "../../kernels/level3/xgemm_part3.opencl"
|
||||||
;
|
;
|
||||||
}
|
}
|
||||||
|
|
||||||
|
@ -97,12 +98,6 @@ StatusCode Xsyr2k<T>::DoSyr2k(const Layout layout, const Triangle triangle, cons
|
||||||
auto b_temp = (b_no_temp) ? b_buffer : Buffer<T>(context_, k_ceiled*n_ceiled);
|
auto b_temp = (b_no_temp) ? b_buffer : Buffer<T>(context_, k_ceiled*n_ceiled);
|
||||||
auto c_temp = Buffer<T>(context_, n_ceiled*n_ceiled);
|
auto c_temp = Buffer<T>(context_, n_ceiled*n_ceiled);
|
||||||
|
|
||||||
// Upload the scalar arguments as constant buffers to the device (needed for half-precision)
|
|
||||||
auto alpha_buffer = Buffer<T>(context_, 1);
|
|
||||||
auto beta_buffer = Buffer<T>(context_, 1);
|
|
||||||
alpha_buffer.Write(queue_, 1, &alpha);
|
|
||||||
beta_buffer.Write(queue_, 1, &beta);
|
|
||||||
|
|
||||||
// Events of all kernels (including pre/post processing kernels)
|
// Events of all kernels (including pre/post processing kernels)
|
||||||
auto eventWaitList = std::vector<Event>();
|
auto eventWaitList = std::vector<Event>();
|
||||||
auto emptyEventList = std::vector<Event>();
|
auto emptyEventList = std::vector<Event>();
|
||||||
|
@ -112,7 +107,7 @@ StatusCode Xsyr2k<T>::DoSyr2k(const Layout layout, const Triangle triangle, cons
|
||||||
// case nothing has to be done, these kernels can be skipped.
|
// case nothing has to be done, these kernels can be skipped.
|
||||||
if (!a_no_temp) {
|
if (!a_no_temp) {
|
||||||
auto eventProcessA = Event();
|
auto eventProcessA = Event();
|
||||||
status = PadCopyTransposeMatrix(queue_, device_, context_, db_, eventProcessA.pointer(), emptyEventList,
|
status = PadCopyTransposeMatrix(queue_, device_, db_, eventProcessA.pointer(), emptyEventList,
|
||||||
ab_one, ab_two, a_ld, a_offset, a_buffer,
|
ab_one, ab_two, a_ld, a_offset, a_buffer,
|
||||||
n_ceiled, k_ceiled, n_ceiled, 0, a_temp,
|
n_ceiled, k_ceiled, n_ceiled, 0, a_temp,
|
||||||
ConstantOne<T>(), program,
|
ConstantOne<T>(), program,
|
||||||
|
@ -122,7 +117,7 @@ StatusCode Xsyr2k<T>::DoSyr2k(const Layout layout, const Triangle triangle, cons
|
||||||
}
|
}
|
||||||
if (!b_no_temp) {
|
if (!b_no_temp) {
|
||||||
auto eventProcessB = Event();
|
auto eventProcessB = Event();
|
||||||
status = PadCopyTransposeMatrix(queue_, device_, context_, db_, eventProcessB.pointer(), emptyEventList,
|
status = PadCopyTransposeMatrix(queue_, device_, db_, eventProcessB.pointer(), emptyEventList,
|
||||||
ab_one, ab_two, b_ld, b_offset, b_buffer,
|
ab_one, ab_two, b_ld, b_offset, b_buffer,
|
||||||
n_ceiled, k_ceiled, n_ceiled, 0, b_temp,
|
n_ceiled, k_ceiled, n_ceiled, 0, b_temp,
|
||||||
ConstantOne<T>(), program,
|
ConstantOne<T>(), program,
|
||||||
|
@ -134,7 +129,7 @@ StatusCode Xsyr2k<T>::DoSyr2k(const Layout layout, const Triangle triangle, cons
|
||||||
// Furthermore, also creates a (possibly padded) copy of matrix C, since it is not allowed to
|
// Furthermore, also creates a (possibly padded) copy of matrix C, since it is not allowed to
|
||||||
// modify the other triangle.
|
// modify the other triangle.
|
||||||
auto eventProcessC = Event();
|
auto eventProcessC = Event();
|
||||||
status = PadCopyTransposeMatrix(queue_, device_, context_, db_, eventProcessC.pointer(), emptyEventList,
|
status = PadCopyTransposeMatrix(queue_, device_, db_, eventProcessC.pointer(), emptyEventList,
|
||||||
n, n, c_ld, c_offset, c_buffer,
|
n, n, c_ld, c_offset, c_buffer,
|
||||||
n_ceiled, n_ceiled, n_ceiled, 0, c_temp,
|
n_ceiled, n_ceiled, n_ceiled, 0, c_temp,
|
||||||
ConstantOne<T>(), program,
|
ConstantOne<T>(), program,
|
||||||
|
@ -149,8 +144,8 @@ StatusCode Xsyr2k<T>::DoSyr2k(const Layout layout, const Triangle triangle, cons
|
||||||
// Sets the kernel arguments
|
// Sets the kernel arguments
|
||||||
kernel.SetArgument(0, static_cast<int>(n_ceiled));
|
kernel.SetArgument(0, static_cast<int>(n_ceiled));
|
||||||
kernel.SetArgument(1, static_cast<int>(k_ceiled));
|
kernel.SetArgument(1, static_cast<int>(k_ceiled));
|
||||||
kernel.SetArgument(2, alpha_buffer());
|
kernel.SetArgument(2, GetRealArg(alpha));
|
||||||
kernel.SetArgument(3, beta_buffer());
|
kernel.SetArgument(3, GetRealArg(beta));
|
||||||
kernel.SetArgument(4, a_temp());
|
kernel.SetArgument(4, a_temp());
|
||||||
kernel.SetArgument(5, b_temp());
|
kernel.SetArgument(5, b_temp());
|
||||||
kernel.SetArgument(6, c_temp());
|
kernel.SetArgument(6, c_temp());
|
||||||
|
@ -170,8 +165,7 @@ StatusCode Xsyr2k<T>::DoSyr2k(const Layout layout, const Triangle triangle, cons
|
||||||
|
|
||||||
// Swaps the arguments for matrices A and B, and sets 'beta' to 1
|
// Swaps the arguments for matrices A and B, and sets 'beta' to 1
|
||||||
auto one = static_cast<T>(1);
|
auto one = static_cast<T>(1);
|
||||||
beta_buffer.Write(queue_, 1, &one);
|
kernel.SetArgument(3, GetRealArg(one));
|
||||||
kernel.SetArgument(3, beta_buffer());
|
|
||||||
kernel.SetArgument(4, b_temp());
|
kernel.SetArgument(4, b_temp());
|
||||||
kernel.SetArgument(5, a_temp());
|
kernel.SetArgument(5, a_temp());
|
||||||
|
|
||||||
|
@ -184,7 +178,7 @@ StatusCode Xsyr2k<T>::DoSyr2k(const Layout layout, const Triangle triangle, cons
|
||||||
// Runs the post-processing kernel
|
// Runs the post-processing kernel
|
||||||
auto upper = (triangle == Triangle::kUpper);
|
auto upper = (triangle == Triangle::kUpper);
|
||||||
auto lower = (triangle == Triangle::kLower);
|
auto lower = (triangle == Triangle::kLower);
|
||||||
status = PadCopyTransposeMatrix(queue_, device_, context_, db_, event_, eventWaitList,
|
status = PadCopyTransposeMatrix(queue_, device_, db_, event_, eventWaitList,
|
||||||
n_ceiled, n_ceiled, n_ceiled, 0, c_temp,
|
n_ceiled, n_ceiled, n_ceiled, 0, c_temp,
|
||||||
n, n, c_ld, c_offset, c_buffer,
|
n, n, c_ld, c_offset, c_buffer,
|
||||||
ConstantOne<T>(), program,
|
ConstantOne<T>(), program,
|
||||||
|
|
|
@ -31,6 +31,7 @@ Xsyrk<T>::Xsyrk(Queue &queue, EventPointer event, const std::string &name):
|
||||||
#include "../../kernels/level3/transpose_pad.opencl"
|
#include "../../kernels/level3/transpose_pad.opencl"
|
||||||
#include "../../kernels/level3/xgemm_part1.opencl"
|
#include "../../kernels/level3/xgemm_part1.opencl"
|
||||||
#include "../../kernels/level3/xgemm_part2.opencl"
|
#include "../../kernels/level3/xgemm_part2.opencl"
|
||||||
|
#include "../../kernels/level3/xgemm_part3.opencl"
|
||||||
;
|
;
|
||||||
}
|
}
|
||||||
|
|
||||||
|
@ -90,12 +91,6 @@ StatusCode Xsyrk<T>::DoSyrk(const Layout layout, const Triangle triangle, const
|
||||||
auto a_temp = (a_no_temp) ? a_buffer : Buffer<T>(context_, k_ceiled*n_ceiled);
|
auto a_temp = (a_no_temp) ? a_buffer : Buffer<T>(context_, k_ceiled*n_ceiled);
|
||||||
auto c_temp = Buffer<T>(context_, n_ceiled*n_ceiled);
|
auto c_temp = Buffer<T>(context_, n_ceiled*n_ceiled);
|
||||||
|
|
||||||
// Upload the scalar arguments as constant buffers to the device (needed for half-precision)
|
|
||||||
auto alpha_buffer = Buffer<T>(context_, 1);
|
|
||||||
auto beta_buffer = Buffer<T>(context_, 1);
|
|
||||||
alpha_buffer.Write(queue_, 1, &alpha);
|
|
||||||
beta_buffer.Write(queue_, 1, &beta);
|
|
||||||
|
|
||||||
// Events of all kernels (including pre/post processing kernels)
|
// Events of all kernels (including pre/post processing kernels)
|
||||||
auto eventWaitList = std::vector<Event>();
|
auto eventWaitList = std::vector<Event>();
|
||||||
auto emptyEventList = std::vector<Event>();
|
auto emptyEventList = std::vector<Event>();
|
||||||
|
@ -105,7 +100,7 @@ StatusCode Xsyrk<T>::DoSyrk(const Layout layout, const Triangle triangle, const
|
||||||
// case nothing has to be done, these kernels can be skipped.
|
// case nothing has to be done, these kernels can be skipped.
|
||||||
if (!a_no_temp) {
|
if (!a_no_temp) {
|
||||||
auto eventProcessA = Event();
|
auto eventProcessA = Event();
|
||||||
status = PadCopyTransposeMatrix(queue_, device_, context_, db_, eventProcessA.pointer(), emptyEventList,
|
status = PadCopyTransposeMatrix(queue_, device_, db_, eventProcessA.pointer(), emptyEventList,
|
||||||
a_one, a_two, a_ld, a_offset, a_buffer,
|
a_one, a_two, a_ld, a_offset, a_buffer,
|
||||||
n_ceiled, k_ceiled, n_ceiled, 0, a_temp,
|
n_ceiled, k_ceiled, n_ceiled, 0, a_temp,
|
||||||
ConstantOne<T>(), program,
|
ConstantOne<T>(), program,
|
||||||
|
@ -117,7 +112,7 @@ StatusCode Xsyrk<T>::DoSyrk(const Layout layout, const Triangle triangle, const
|
||||||
// Furthermore, also creates a (possibly padded) copy of matrix C, since it is not allowed to
|
// Furthermore, also creates a (possibly padded) copy of matrix C, since it is not allowed to
|
||||||
// modify the other triangle.
|
// modify the other triangle.
|
||||||
auto eventProcessC = Event();
|
auto eventProcessC = Event();
|
||||||
status = PadCopyTransposeMatrix(queue_, device_, context_, db_, eventProcessC.pointer(), emptyEventList,
|
status = PadCopyTransposeMatrix(queue_, device_, db_, eventProcessC.pointer(), emptyEventList,
|
||||||
n, n, c_ld, c_offset, c_buffer,
|
n, n, c_ld, c_offset, c_buffer,
|
||||||
n_ceiled, n_ceiled, n_ceiled, 0, c_temp,
|
n_ceiled, n_ceiled, n_ceiled, 0, c_temp,
|
||||||
ConstantOne<T>(), program,
|
ConstantOne<T>(), program,
|
||||||
|
@ -132,8 +127,8 @@ StatusCode Xsyrk<T>::DoSyrk(const Layout layout, const Triangle triangle, const
|
||||||
// Sets the kernel arguments
|
// Sets the kernel arguments
|
||||||
kernel.SetArgument(0, static_cast<int>(n_ceiled));
|
kernel.SetArgument(0, static_cast<int>(n_ceiled));
|
||||||
kernel.SetArgument(1, static_cast<int>(k_ceiled));
|
kernel.SetArgument(1, static_cast<int>(k_ceiled));
|
||||||
kernel.SetArgument(2, alpha_buffer());
|
kernel.SetArgument(2, GetRealArg(alpha));
|
||||||
kernel.SetArgument(3, beta_buffer());
|
kernel.SetArgument(3, GetRealArg(beta));
|
||||||
kernel.SetArgument(4, a_temp());
|
kernel.SetArgument(4, a_temp());
|
||||||
kernel.SetArgument(5, a_temp());
|
kernel.SetArgument(5, a_temp());
|
||||||
kernel.SetArgument(6, c_temp());
|
kernel.SetArgument(6, c_temp());
|
||||||
|
@ -154,7 +149,7 @@ StatusCode Xsyrk<T>::DoSyrk(const Layout layout, const Triangle triangle, const
|
||||||
// Runs the post-processing kernel
|
// Runs the post-processing kernel
|
||||||
auto upper = (triangle == Triangle::kUpper);
|
auto upper = (triangle == Triangle::kUpper);
|
||||||
auto lower = (triangle == Triangle::kLower);
|
auto lower = (triangle == Triangle::kLower);
|
||||||
status = PadCopyTransposeMatrix(queue_, device_, context_, db_, event_, eventWaitList,
|
status = PadCopyTransposeMatrix(queue_, device_, db_, event_, eventWaitList,
|
||||||
n_ceiled, n_ceiled, n_ceiled, 0, c_temp,
|
n_ceiled, n_ceiled, n_ceiled, 0, c_temp,
|
||||||
n, n, c_ld, c_offset, c_buffer,
|
n, n, c_ld, c_offset, c_buffer,
|
||||||
ConstantOne<T>(), program,
|
ConstantOne<T>(), program,
|
||||||
|
|
|
@ -72,7 +72,7 @@ StatusCode Xomatcopy<T>::DoOmatcopy(const Layout layout, const Transpose a_trans
|
||||||
const auto program = GetProgramFromCache(context_, PrecisionValue<T>(), routine_name_);
|
const auto program = GetProgramFromCache(context_, PrecisionValue<T>(), routine_name_);
|
||||||
|
|
||||||
auto emptyEventList = std::vector<Event>();
|
auto emptyEventList = std::vector<Event>();
|
||||||
status = PadCopyTransposeMatrix(queue_, device_, context_, db_, event_, emptyEventList,
|
status = PadCopyTransposeMatrix(queue_, device_, db_, event_, emptyEventList,
|
||||||
a_one, a_two, a_ld, a_offset, a_buffer,
|
a_one, a_two, a_ld, a_offset, a_buffer,
|
||||||
b_one, b_two, b_ld, b_offset, b_buffer,
|
b_one, b_two, b_ld, b_offset, b_buffer,
|
||||||
alpha, program, false, transpose, conjugate);
|
alpha, program, false, transpose, conjugate);
|
||||||
|
|
|
@ -86,11 +86,10 @@ class TuneCopy {
|
||||||
std::vector<T> &, std::vector<T> &,
|
std::vector<T> &, std::vector<T> &,
|
||||||
std::vector<T> &a_mat, std::vector<T> &b_mat, std::vector<T> &,
|
std::vector<T> &a_mat, std::vector<T> &b_mat, std::vector<T> &,
|
||||||
std::vector<T> &) {
|
std::vector<T> &) {
|
||||||
auto alpha_buffer = std::vector<T>{args.alpha};
|
|
||||||
tuner.AddArgumentScalar(static_cast<int>(args.m));
|
tuner.AddArgumentScalar(static_cast<int>(args.m));
|
||||||
tuner.AddArgumentInput(a_mat);
|
tuner.AddArgumentInput(a_mat);
|
||||||
tuner.AddArgumentOutput(b_mat);
|
tuner.AddArgumentOutput(b_mat);
|
||||||
tuner.AddArgumentInput(alpha_buffer);
|
tuner.AddArgumentScalar(GetRealArg(args.alpha));
|
||||||
}
|
}
|
||||||
|
|
||||||
// Describes how to compute the performance metrics
|
// Describes how to compute the performance metrics
|
||||||
|
|
|
@ -86,7 +86,6 @@ class TunePad {
|
||||||
std::vector<T> &, std::vector<T> &,
|
std::vector<T> &, std::vector<T> &,
|
||||||
std::vector<T> &a_mat, std::vector<T> &b_mat, std::vector<T> &,
|
std::vector<T> &a_mat, std::vector<T> &b_mat, std::vector<T> &,
|
||||||
std::vector<T> &) {
|
std::vector<T> &) {
|
||||||
auto alpha_buffer = std::vector<T>{args.alpha};
|
|
||||||
tuner.AddArgumentScalar(static_cast<int>(args.m));
|
tuner.AddArgumentScalar(static_cast<int>(args.m));
|
||||||
tuner.AddArgumentScalar(static_cast<int>(args.n));
|
tuner.AddArgumentScalar(static_cast<int>(args.n));
|
||||||
tuner.AddArgumentScalar(static_cast<int>(args.m));
|
tuner.AddArgumentScalar(static_cast<int>(args.m));
|
||||||
|
@ -97,7 +96,7 @@ class TunePad {
|
||||||
tuner.AddArgumentScalar(static_cast<int>(args.m));
|
tuner.AddArgumentScalar(static_cast<int>(args.m));
|
||||||
tuner.AddArgumentScalar(0);
|
tuner.AddArgumentScalar(0);
|
||||||
tuner.AddArgumentOutput(b_mat);
|
tuner.AddArgumentOutput(b_mat);
|
||||||
tuner.AddArgumentInput(alpha_buffer);
|
tuner.AddArgumentScalar(GetRealArg(args.alpha));
|
||||||
tuner.AddArgumentScalar(0);
|
tuner.AddArgumentScalar(0);
|
||||||
}
|
}
|
||||||
|
|
||||||
|
|
|
@ -91,11 +91,10 @@ class TuneTranspose {
|
||||||
std::vector<T> &, std::vector<T> &,
|
std::vector<T> &, std::vector<T> &,
|
||||||
std::vector<T> &a_mat, std::vector<T> &b_mat, std::vector<T> &,
|
std::vector<T> &a_mat, std::vector<T> &b_mat, std::vector<T> &,
|
||||||
std::vector<T> &) {
|
std::vector<T> &) {
|
||||||
auto alpha_buffer = std::vector<T>{args.alpha};
|
|
||||||
tuner.AddArgumentScalar(static_cast<int>(args.m));
|
tuner.AddArgumentScalar(static_cast<int>(args.m));
|
||||||
tuner.AddArgumentInput(a_mat);
|
tuner.AddArgumentInput(a_mat);
|
||||||
tuner.AddArgumentOutput(b_mat);
|
tuner.AddArgumentOutput(b_mat);
|
||||||
tuner.AddArgumentInput(alpha_buffer);
|
tuner.AddArgumentScalar(GetRealArg(args.alpha));
|
||||||
}
|
}
|
||||||
|
|
||||||
// Describes how to compute the performance metrics
|
// Describes how to compute the performance metrics
|
||||||
|
|
|
@ -90,7 +90,6 @@ class TunePadTranspose {
|
||||||
std::vector<T> &, std::vector<T> &,
|
std::vector<T> &, std::vector<T> &,
|
||||||
std::vector<T> &a_mat, std::vector<T> &b_mat, std::vector<T> &,
|
std::vector<T> &a_mat, std::vector<T> &b_mat, std::vector<T> &,
|
||||||
std::vector<T> &) {
|
std::vector<T> &) {
|
||||||
auto alpha_buffer = std::vector<T>{args.alpha};
|
|
||||||
tuner.AddArgumentScalar(static_cast<int>(args.m));
|
tuner.AddArgumentScalar(static_cast<int>(args.m));
|
||||||
tuner.AddArgumentScalar(static_cast<int>(args.n));
|
tuner.AddArgumentScalar(static_cast<int>(args.n));
|
||||||
tuner.AddArgumentScalar(static_cast<int>(args.m));
|
tuner.AddArgumentScalar(static_cast<int>(args.m));
|
||||||
|
@ -101,7 +100,7 @@ class TunePadTranspose {
|
||||||
tuner.AddArgumentScalar(static_cast<int>(args.n));
|
tuner.AddArgumentScalar(static_cast<int>(args.n));
|
||||||
tuner.AddArgumentScalar(0);
|
tuner.AddArgumentScalar(0);
|
||||||
tuner.AddArgumentOutput(b_mat);
|
tuner.AddArgumentOutput(b_mat);
|
||||||
tuner.AddArgumentInput(alpha_buffer);
|
tuner.AddArgumentScalar(GetRealArg(args.alpha));
|
||||||
tuner.AddArgumentScalar(0);
|
tuner.AddArgumentScalar(0);
|
||||||
}
|
}
|
||||||
|
|
||||||
|
|
|
@ -89,9 +89,8 @@ class TuneXaxpy {
|
||||||
std::vector<T> &x_vec, std::vector<T> &y_vec,
|
std::vector<T> &x_vec, std::vector<T> &y_vec,
|
||||||
std::vector<T> &, std::vector<T> &, std::vector<T> &,
|
std::vector<T> &, std::vector<T> &, std::vector<T> &,
|
||||||
std::vector<T> &) {
|
std::vector<T> &) {
|
||||||
auto alpha_buffer = std::vector<T>{args.alpha};
|
|
||||||
tuner.AddArgumentScalar(static_cast<int>(args.n));
|
tuner.AddArgumentScalar(static_cast<int>(args.n));
|
||||||
tuner.AddArgumentInput(alpha_buffer);
|
tuner.AddArgumentScalar(GetRealArg(args.alpha));
|
||||||
tuner.AddArgumentInput(x_vec);
|
tuner.AddArgumentInput(x_vec);
|
||||||
tuner.AddArgumentOutput(y_vec);
|
tuner.AddArgumentOutput(y_vec);
|
||||||
}
|
}
|
||||||
|
|
|
@ -7,7 +7,9 @@
|
||||||
// Author(s):
|
// Author(s):
|
||||||
// Cedric Nugteren <www.cedricnugteren.nl>
|
// Cedric Nugteren <www.cedricnugteren.nl>
|
||||||
//
|
//
|
||||||
// This file uses the CLTune auto-tuner to tune the xgemm OpenCL kernels.
|
// This file uses the CLTune auto-tuner to tune the xgemm OpenCL kernels. There are two variations:
|
||||||
|
// - V==1: This tests some limited set of tuning parameters exhaustively.
|
||||||
|
// - V==2: This tests a much larger set of tuning parameters by randomly sampling a subset.
|
||||||
//
|
//
|
||||||
// =================================================================================================
|
// =================================================================================================
|
||||||
|
|
||||||
|
@ -21,18 +23,19 @@ namespace clblast {
|
||||||
// =================================================================================================
|
// =================================================================================================
|
||||||
|
|
||||||
// See comment at top of file for a description of the class
|
// See comment at top of file for a description of the class
|
||||||
template <typename T>
|
template <typename T, int V>
|
||||||
class TuneXgemm {
|
class TuneXgemm {
|
||||||
public:
|
public:
|
||||||
|
|
||||||
// The representative kernel and the source code
|
// The representative kernel and the source code
|
||||||
static std::string KernelFamily() { return "xgemm"; }
|
static std::string KernelFamily() { return (V==1) ? "xgemm_1" : "xgemm_2"; }
|
||||||
static std::string KernelName() { return "Xgemm"; }
|
static std::string KernelName() { return "Xgemm"; }
|
||||||
static std::string GetSources() {
|
static std::string GetSources() {
|
||||||
return
|
return
|
||||||
#include "../src/kernels/common.opencl"
|
#include "../src/kernels/common.opencl"
|
||||||
#include "../src/kernels/level3/xgemm_part1.opencl"
|
#include "../src/kernels/level3/xgemm_part1.opencl"
|
||||||
#include "../src/kernels/level3/xgemm_part2.opencl"
|
#include "../src/kernels/level3/xgemm_part2.opencl"
|
||||||
|
#include "../src/kernels/level3/xgemm_part3.opencl"
|
||||||
;
|
;
|
||||||
}
|
}
|
||||||
|
|
||||||
|
@ -48,7 +51,7 @@ class TuneXgemm {
|
||||||
static size_t DefaultM() { return 1024; }
|
static size_t DefaultM() { return 1024; }
|
||||||
static size_t DefaultN() { return 1024; }
|
static size_t DefaultN() { return 1024; }
|
||||||
static size_t DefaultK() { return 1024; }
|
static size_t DefaultK() { return 1024; }
|
||||||
static double DefaultFraction() { return 2048.0; }
|
static double DefaultFraction() { return (V==1) ? 1.0 : 512.0; } // test all or sample randomly
|
||||||
|
|
||||||
// Describes how to obtain the sizes of the buffers
|
// Describes how to obtain the sizes of the buffers
|
||||||
static size_t GetSizeX(const Arguments<T> &) { return 1; } // N/A for this kernel
|
static size_t GetSizeX(const Arguments<T> &) { return 1; } // N/A for this kernel
|
||||||
|
@ -60,6 +63,23 @@ class TuneXgemm {
|
||||||
|
|
||||||
// Sets the tuning parameters and their possible values
|
// Sets the tuning parameters and their possible values
|
||||||
static void SetParameters(cltune::Tuner &tuner, const size_t id) {
|
static void SetParameters(cltune::Tuner &tuner, const size_t id) {
|
||||||
|
if (V==1) { // limited subset of tuning parameters - but explorable exhaustively
|
||||||
|
tuner.AddParameter(id, "MWG", {16, 32, 64});
|
||||||
|
tuner.AddParameter(id, "NWG", {16, 32, 64});
|
||||||
|
tuner.AddParameter(id, "KWG", {32});
|
||||||
|
tuner.AddParameter(id, "MDIMC", {8, 16, 32});
|
||||||
|
tuner.AddParameter(id, "NDIMC", {8, 16, 32});
|
||||||
|
tuner.AddParameter(id, "MDIMA", {8, 16, 32});
|
||||||
|
tuner.AddParameter(id, "NDIMB", {8, 16, 32});
|
||||||
|
tuner.AddParameter(id, "KWI", {2});
|
||||||
|
tuner.AddParameter(id, "VWM", {1, 2, 4});
|
||||||
|
tuner.AddParameter(id, "VWN", {1, 2, 4});
|
||||||
|
tuner.AddParameter(id, "STRM", {0});
|
||||||
|
tuner.AddParameter(id, "STRN", {0});
|
||||||
|
tuner.AddParameter(id, "SA", {0, 1});
|
||||||
|
tuner.AddParameter(id, "SB", {0, 1});
|
||||||
|
} // a lot more tuning parameters - has to be sampled randomly, too much to test all
|
||||||
|
else {
|
||||||
tuner.AddParameter(id, "MWG", {16, 32, 64, 128});
|
tuner.AddParameter(id, "MWG", {16, 32, 64, 128});
|
||||||
tuner.AddParameter(id, "NWG", {16, 32, 64, 128});
|
tuner.AddParameter(id, "NWG", {16, 32, 64, 128});
|
||||||
tuner.AddParameter(id, "KWG", {16, 32});
|
tuner.AddParameter(id, "KWG", {16, 32});
|
||||||
|
@ -67,7 +87,7 @@ class TuneXgemm {
|
||||||
tuner.AddParameter(id, "NDIMC", {8, 16, 32});
|
tuner.AddParameter(id, "NDIMC", {8, 16, 32});
|
||||||
tuner.AddParameter(id, "MDIMA", {8, 16, 32});
|
tuner.AddParameter(id, "MDIMA", {8, 16, 32});
|
||||||
tuner.AddParameter(id, "NDIMB", {8, 16, 32});
|
tuner.AddParameter(id, "NDIMB", {8, 16, 32});
|
||||||
tuner.AddParameter(id, "KWI", {2, 8});
|
tuner.AddParameter(id, "KWI", {2});
|
||||||
tuner.AddParameter(id, "VWM", {1, 2, 4, 8});
|
tuner.AddParameter(id, "VWM", {1, 2, 4, 8});
|
||||||
tuner.AddParameter(id, "VWN", {1, 2, 4, 8});
|
tuner.AddParameter(id, "VWN", {1, 2, 4, 8});
|
||||||
tuner.AddParameter(id, "STRM", {0, 1});
|
tuner.AddParameter(id, "STRM", {0, 1});
|
||||||
|
@ -75,6 +95,7 @@ class TuneXgemm {
|
||||||
tuner.AddParameter(id, "SA", {0, 1});
|
tuner.AddParameter(id, "SA", {0, 1});
|
||||||
tuner.AddParameter(id, "SB", {0, 1});
|
tuner.AddParameter(id, "SB", {0, 1});
|
||||||
}
|
}
|
||||||
|
}
|
||||||
|
|
||||||
// Sets the constraints
|
// Sets the constraints
|
||||||
static void SetConstraints(cltune::Tuner &tuner, const size_t id) {
|
static void SetConstraints(cltune::Tuner &tuner, const size_t id) {
|
||||||
|
@ -92,6 +113,14 @@ class TuneXgemm {
|
||||||
// KWG has to be a multiple of KDIMA = ((MDIMC*NDIMC)/(MDIMA)) and KDIMB = (...)
|
// KWG has to be a multiple of KDIMA = ((MDIMC*NDIMC)/(MDIMA)) and KDIMB = (...)
|
||||||
tuner.AddConstraint(id, MultipleOfXMulYDivZ, {"KWG", "MDIMC", "NDIMC", "MDIMA"});
|
tuner.AddConstraint(id, MultipleOfXMulYDivZ, {"KWG", "MDIMC", "NDIMC", "MDIMA"});
|
||||||
tuner.AddConstraint(id, MultipleOfXMulYDivZ, {"KWG", "MDIMC", "NDIMC", "NDIMB"});
|
tuner.AddConstraint(id, MultipleOfXMulYDivZ, {"KWG", "MDIMC", "NDIMC", "NDIMB"});
|
||||||
|
|
||||||
|
// Extra constraints for variation 1 to limit the set of options significantly
|
||||||
|
if (V==1) {
|
||||||
|
auto IsEqual = [] (std::vector<size_t> v) { return v[0] == v[1]; };
|
||||||
|
tuner.AddConstraint(id, IsEqual, {"MDIMC", "MDIMA"});
|
||||||
|
tuner.AddConstraint(id, IsEqual, {"NDIMC", "NDIMB"});
|
||||||
|
tuner.AddConstraint(id, IsEqual, {"SA", "SB"});
|
||||||
|
}
|
||||||
}
|
}
|
||||||
|
|
||||||
// Sets the local memory size
|
// Sets the local memory size
|
||||||
|
@ -121,13 +150,11 @@ class TuneXgemm {
|
||||||
std::vector<T> &, std::vector<T> &,
|
std::vector<T> &, std::vector<T> &,
|
||||||
std::vector<T> &a_mat, std::vector<T> &b_mat, std::vector<T> &c_mat,
|
std::vector<T> &a_mat, std::vector<T> &b_mat, std::vector<T> &c_mat,
|
||||||
std::vector<T> &) {
|
std::vector<T> &) {
|
||||||
auto alpha_buffer = std::vector<T>{args.alpha};
|
|
||||||
auto beta_buffer = std::vector<T>{args.beta};
|
|
||||||
tuner.AddArgumentScalar(static_cast<int>(args.m));
|
tuner.AddArgumentScalar(static_cast<int>(args.m));
|
||||||
tuner.AddArgumentScalar(static_cast<int>(args.n));
|
tuner.AddArgumentScalar(static_cast<int>(args.n));
|
||||||
tuner.AddArgumentScalar(static_cast<int>(args.k));
|
tuner.AddArgumentScalar(static_cast<int>(args.k));
|
||||||
tuner.AddArgumentInput(alpha_buffer);
|
tuner.AddArgumentScalar(GetRealArg(args.alpha));
|
||||||
tuner.AddArgumentInput(beta_buffer);
|
tuner.AddArgumentScalar(GetRealArg(args.beta));
|
||||||
tuner.AddArgumentInput(a_mat);
|
tuner.AddArgumentInput(a_mat);
|
||||||
tuner.AddArgumentInput(b_mat);
|
tuner.AddArgumentInput(b_mat);
|
||||||
tuner.AddArgumentOutput(c_mat);
|
tuner.AddArgumentOutput(c_mat);
|
||||||
|
@ -147,15 +174,22 @@ class TuneXgemm {
|
||||||
using float2 = clblast::float2;
|
using float2 = clblast::float2;
|
||||||
using double2 = clblast::double2;
|
using double2 = clblast::double2;
|
||||||
|
|
||||||
|
// Function to tune a specific variation V (not within the clblast namespace)
|
||||||
|
template <int V>
|
||||||
|
void StartVariation(int argc, char *argv[]) {
|
||||||
|
switch(clblast::GetPrecision(argc, argv)) {
|
||||||
|
case clblast::Precision::kHalf: clblast::Tuner<clblast::TuneXgemm<half,V>, half>(argc, argv); break;
|
||||||
|
case clblast::Precision::kSingle: clblast::Tuner<clblast::TuneXgemm<float,V>, float>(argc, argv); break;
|
||||||
|
case clblast::Precision::kDouble: clblast::Tuner<clblast::TuneXgemm<double,V>, double>(argc, argv); break;
|
||||||
|
case clblast::Precision::kComplexSingle: clblast::Tuner<clblast::TuneXgemm<float2,V>, float2>(argc, argv); break;
|
||||||
|
case clblast::Precision::kComplexDouble: clblast::Tuner<clblast::TuneXgemm<double2,V>, double2>(argc, argv); break;
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
// Main function (not within the clblast namespace)
|
// Main function (not within the clblast namespace)
|
||||||
int main(int argc, char *argv[]) {
|
int main(int argc, char *argv[]) {
|
||||||
switch(clblast::GetPrecision(argc, argv)) {
|
StartVariation<1>(argc, argv);
|
||||||
case clblast::Precision::kHalf: clblast::Tuner<clblast::TuneXgemm<half>, half>(argc, argv); break;
|
StartVariation<2>(argc, argv);
|
||||||
case clblast::Precision::kSingle: clblast::Tuner<clblast::TuneXgemm<float>, float>(argc, argv); break;
|
|
||||||
case clblast::Precision::kDouble: clblast::Tuner<clblast::TuneXgemm<double>, double>(argc, argv); break;
|
|
||||||
case clblast::Precision::kComplexSingle: clblast::Tuner<clblast::TuneXgemm<float2>, float2>(argc, argv); break;
|
|
||||||
case clblast::Precision::kComplexDouble: clblast::Tuner<clblast::TuneXgemm<double2>, double2>(argc, argv); break;
|
|
||||||
}
|
|
||||||
return 0;
|
return 0;
|
||||||
}
|
}
|
||||||
|
|
||||||
|
|
|
@ -29,7 +29,7 @@ class TuneXgemv {
|
||||||
public:
|
public:
|
||||||
|
|
||||||
// The representative kernel and the source code
|
// The representative kernel and the source code
|
||||||
static std::string KernelFamily() { return "xgemv_"+std::to_string(V); }
|
static std::string KernelFamily() { return (V==1) ? "xgemv" : ((V==2) ? "xgemv_fast" : "xgemv_fast_rot"); }
|
||||||
static std::string KernelName() { return (V==1) ? "Xgemv" : ((V==2) ? "XgemvFast" : "XgemvFastRot"); }
|
static std::string KernelName() { return (V==1) ? "Xgemv" : ((V==2) ? "XgemvFast" : "XgemvFastRot"); }
|
||||||
static std::string GetSources() {
|
static std::string GetSources() {
|
||||||
return
|
return
|
||||||
|
@ -61,22 +61,43 @@ class TuneXgemv {
|
||||||
|
|
||||||
// Sets the tuning parameters and their possible values
|
// Sets the tuning parameters and their possible values
|
||||||
static void SetParameters(cltune::Tuner &tuner, const size_t id) {
|
static void SetParameters(cltune::Tuner &tuner, const size_t id) {
|
||||||
tuner.AddParameter(id, "WGS"+std::to_string(V), {64, 128, 256});
|
if (V==1) {
|
||||||
|
tuner.AddParameter(id, "WGS"+std::to_string(V), {32, 64, 128, 256});
|
||||||
tuner.AddParameter(id, "WPT"+std::to_string(V), {1, 2, 4});
|
tuner.AddParameter(id, "WPT"+std::to_string(V), {1, 2, 4});
|
||||||
if (V==2 || V==3) { tuner.AddParameter(id, "VW"+std::to_string(V), {1, 2, 4, 8}); }
|
}
|
||||||
|
if (V==2) {
|
||||||
|
tuner.AddParameter(id, "WGS"+std::to_string(V), {16, 32, 64, 128, 256});
|
||||||
|
tuner.AddParameter(id, "WPT"+std::to_string(V), {1, 2, 4});
|
||||||
|
tuner.AddParameter(id, "VW"+std::to_string(V), {1, 2, 4, 8});
|
||||||
|
}
|
||||||
|
if (V==3) {
|
||||||
|
tuner.AddParameter(id, "WGS"+std::to_string(V), {16, 32, 64, 128});
|
||||||
|
tuner.AddParameter(id, "WPT"+std::to_string(V), {1, 2, 4, 8, 16, 32});
|
||||||
|
tuner.AddParameter(id, "VW"+std::to_string(V), {1, 2, 4, 8});
|
||||||
|
}
|
||||||
}
|
}
|
||||||
|
|
||||||
// Sets the constraints and local memory size
|
// Sets the constraints and local memory size
|
||||||
static void SetConstraints(cltune::Tuner &tuner, const size_t id) {
|
static void SetConstraints(cltune::Tuner &tuner, const size_t id) {
|
||||||
auto MultipleOfX = [] (std::vector<size_t> v) { return IsMultiple(v[0], v[1]); };
|
|
||||||
if (V==2 || V==3) {
|
if (V==2 || V==3) {
|
||||||
|
auto MultipleOfX = [] (std::vector<size_t> v) { return IsMultiple(v[0], v[1]); };
|
||||||
tuner.AddConstraint(id, MultipleOfX, {"WPT"+std::to_string(V), "VW"+std::to_string(V)});
|
tuner.AddConstraint(id, MultipleOfX, {"WPT"+std::to_string(V), "VW"+std::to_string(V)});
|
||||||
}
|
}
|
||||||
|
if (V==3) {
|
||||||
|
auto LargerOrEqual = [] (std::vector<size_t> v) { return v[0] >= v[1]; };
|
||||||
|
tuner.AddConstraint(id, LargerOrEqual, {"WGS"+std::to_string(V), "WPT"+std::to_string(V)});
|
||||||
|
}
|
||||||
}
|
}
|
||||||
static void SetLocalMemorySize(cltune::Tuner &tuner, const size_t id, const Arguments<T> &args) {
|
static void SetLocalMemorySize(cltune::Tuner &tuner, const size_t id, const Arguments<T> &args) {
|
||||||
|
if (V==1 || V==2) {
|
||||||
auto LocalMemorySize = [args] (std::vector<size_t> v) { return v[0]*GetBytes(args.precision); };
|
auto LocalMemorySize = [args] (std::vector<size_t> v) { return v[0]*GetBytes(args.precision); };
|
||||||
tuner.SetLocalMemoryUsage(id, LocalMemorySize, {"WGS"+std::to_string(V)});
|
tuner.SetLocalMemoryUsage(id, LocalMemorySize, {"WGS"+std::to_string(V)});
|
||||||
}
|
}
|
||||||
|
else {
|
||||||
|
auto LocalMemorySize = [args] (std::vector<size_t> v) { return (v[0]*v[1] + v[1])*GetBytes(args.precision); };
|
||||||
|
tuner.SetLocalMemoryUsage(id, LocalMemorySize, {"WGS"+std::to_string(V), "WPT"+std::to_string(V)});
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
// Sets the base thread configuration
|
// Sets the base thread configuration
|
||||||
static std::vector<size_t> GlobalSize(const Arguments<T> &args) { return {args.m}; }
|
static std::vector<size_t> GlobalSize(const Arguments<T> &args) { return {args.m}; }
|
||||||
|
@ -89,20 +110,21 @@ class TuneXgemv {
|
||||||
static TransformVector MulLocal() { return {{"WGS"+std::to_string(V)}}; }
|
static TransformVector MulLocal() { return {{"WGS"+std::to_string(V)}}; }
|
||||||
static TransformVector DivLocal() { return {}; }
|
static TransformVector DivLocal() { return {}; }
|
||||||
static TransformVector MulGlobal() { return {}; }
|
static TransformVector MulGlobal() { return {}; }
|
||||||
static TransformVector DivGlobal() { return {{"WPT"+std::to_string(V)}}; }
|
static TransformVector DivGlobal() {
|
||||||
|
if (V==1 || V==2) return {{"WPT"+std::to_string(V)}};
|
||||||
|
return {};
|
||||||
|
}
|
||||||
|
|
||||||
// Sets the kernel's arguments
|
// Sets the kernel's arguments
|
||||||
static void SetArguments(cltune::Tuner &tuner, const Arguments<T> &args,
|
static void SetArguments(cltune::Tuner &tuner, const Arguments<T> &args,
|
||||||
std::vector<T> &x_vec, std::vector<T> &y_vec,
|
std::vector<T> &x_vec, std::vector<T> &y_vec,
|
||||||
std::vector<T> &a_mat, std::vector<T> &, std::vector<T> &,
|
std::vector<T> &a_mat, std::vector<T> &, std::vector<T> &,
|
||||||
std::vector<T> &) {
|
std::vector<T> &) {
|
||||||
auto alpha_buffer = std::vector<T>{args.alpha};
|
|
||||||
auto beta_buffer = std::vector<T>{args.beta};
|
|
||||||
auto a_rotated = (V==3) ? 1 : 0;
|
auto a_rotated = (V==3) ? 1 : 0;
|
||||||
tuner.AddArgumentScalar(static_cast<int>(args.m));
|
tuner.AddArgumentScalar(static_cast<int>(args.m));
|
||||||
tuner.AddArgumentScalar(static_cast<int>(args.n));
|
tuner.AddArgumentScalar(static_cast<int>(args.n));
|
||||||
tuner.AddArgumentInput(alpha_buffer);
|
tuner.AddArgumentScalar(GetRealArg(args.alpha));
|
||||||
tuner.AddArgumentInput(beta_buffer);
|
tuner.AddArgumentScalar(GetRealArg(args.beta));
|
||||||
tuner.AddArgumentScalar(static_cast<int>(a_rotated));
|
tuner.AddArgumentScalar(static_cast<int>(a_rotated));
|
||||||
tuner.AddArgumentInput(a_mat);
|
tuner.AddArgumentInput(a_mat);
|
||||||
tuner.AddArgumentScalar(0);
|
tuner.AddArgumentScalar(0);
|
||||||
|
|
|
@ -85,10 +85,9 @@ class TuneXger {
|
||||||
std::vector<T> &x_vec, std::vector<T> &y_vec,
|
std::vector<T> &x_vec, std::vector<T> &y_vec,
|
||||||
std::vector<T> &a_mat, std::vector<T> &, std::vector<T> &,
|
std::vector<T> &a_mat, std::vector<T> &, std::vector<T> &,
|
||||||
std::vector<T> &) {
|
std::vector<T> &) {
|
||||||
auto alpha_buffer = std::vector<T>{args.alpha};
|
|
||||||
tuner.AddArgumentScalar(static_cast<int>(args.m));
|
tuner.AddArgumentScalar(static_cast<int>(args.m));
|
||||||
tuner.AddArgumentScalar(static_cast<int>(args.n));
|
tuner.AddArgumentScalar(static_cast<int>(args.n));
|
||||||
tuner.AddArgumentInput(alpha_buffer);
|
tuner.AddArgumentScalar(GetRealArg(args.alpha));
|
||||||
tuner.AddArgumentInput(x_vec);
|
tuner.AddArgumentInput(x_vec);
|
||||||
tuner.AddArgumentScalar(0); // x_offset
|
tuner.AddArgumentScalar(0); // x_offset
|
||||||
tuner.AddArgumentScalar(1); // x_increment
|
tuner.AddArgumentScalar(1); // x_increment
|
||||||
|
|
|
@ -161,6 +161,8 @@ template <typename T>
|
||||||
T ConvertArgument(const char* value) {
|
T ConvertArgument(const char* value) {
|
||||||
return static_cast<T>(std::stoi(value));
|
return static_cast<T>(std::stoi(value));
|
||||||
}
|
}
|
||||||
|
template size_t ConvertArgument(const char* value);
|
||||||
|
|
||||||
template <> half ConvertArgument(const char* value) {
|
template <> half ConvertArgument(const char* value) {
|
||||||
return FloatToHalf(static_cast<float>(std::stod(value)));
|
return FloatToHalf(static_cast<float>(std::stod(value)));
|
||||||
}
|
}
|
||||||
|
@ -179,6 +181,15 @@ template <> double2 ConvertArgument(const char* value) {
|
||||||
return double2{val, val};
|
return double2{val, val};
|
||||||
}
|
}
|
||||||
|
|
||||||
|
// Variant of "ConvertArgument" with default values
|
||||||
|
template <typename T>
|
||||||
|
T ConvertArgument(const char* value, T default_value) {
|
||||||
|
|
||||||
|
if (value) { return ConvertArgument<T>(value); }
|
||||||
|
return default_value;
|
||||||
|
}
|
||||||
|
template size_t ConvertArgument(const char* value, size_t default_value);
|
||||||
|
|
||||||
// This function matches patterns in the form of "-option value" or "--option value". It returns a
|
// This function matches patterns in the form of "-option value" or "--option value". It returns a
|
||||||
// default value in case the option is not found in the argument string.
|
// default value in case the option is not found in the argument string.
|
||||||
template <typename T>
|
template <typename T>
|
||||||
|
@ -332,6 +343,14 @@ void FloatToHalfBuffer(Buffer<half>& result, const Buffer<float>& source, cl_com
|
||||||
result.Write(queue, size, result_cpu);
|
result.Write(queue, size, result_cpu);
|
||||||
}
|
}
|
||||||
|
|
||||||
|
// Converts a 'real' value to a 'real argument' value to be passed to a kernel. Normally there is
|
||||||
|
// no conversion, but half-precision is not supported as kernel argument so it is converted to float.
|
||||||
|
template <> typename RealArg<half>::Type GetRealArg(const half value) { return HalfToFloat(value); }
|
||||||
|
template <> typename RealArg<float>::Type GetRealArg(const float value) { return value; }
|
||||||
|
template <> typename RealArg<double>::Type GetRealArg(const double value) { return value; }
|
||||||
|
template <> typename RealArg<float2>::Type GetRealArg(const float2 value) { return value; }
|
||||||
|
template <> typename RealArg<double2>::Type GetRealArg(const double2 value) { return value; }
|
||||||
|
|
||||||
// =================================================================================================
|
// =================================================================================================
|
||||||
|
|
||||||
// Rounding functions performing ceiling and division operations
|
// Rounding functions performing ceiling and division operations
|
||||||
|
|
|
@ -80,8 +80,9 @@ constexpr auto kArgComparecblas = "cblas";
|
||||||
constexpr auto kArgStepSize = "step";
|
constexpr auto kArgStepSize = "step";
|
||||||
constexpr auto kArgNumSteps = "num_steps";
|
constexpr auto kArgNumSteps = "num_steps";
|
||||||
constexpr auto kArgNumRuns = "runs";
|
constexpr auto kArgNumRuns = "runs";
|
||||||
|
constexpr auto kArgWarmUp = "warm_up";
|
||||||
|
|
||||||
// The client-specific arguments in string form
|
// The test-specific arguments in string form
|
||||||
constexpr auto kArgFullTest = "full_test";
|
constexpr auto kArgFullTest = "full_test";
|
||||||
constexpr auto kArgVerbose = "verbose";
|
constexpr auto kArgVerbose = "verbose";
|
||||||
|
|
||||||
|
@ -186,6 +187,10 @@ std::string ToString(T value);
|
||||||
template <typename T>
|
template <typename T>
|
||||||
T ConvertArgument(const char* value);
|
T ConvertArgument(const char* value);
|
||||||
|
|
||||||
|
// Variant of "ConvertArgument" with default values
|
||||||
|
template <typename T>
|
||||||
|
T ConvertArgument(const char* value, T default_value);
|
||||||
|
|
||||||
// Basic argument parser, matching patterns in the form of "-option value" and "--option value"
|
// Basic argument parser, matching patterns in the form of "-option value" and "--option value"
|
||||||
template <typename T>
|
template <typename T>
|
||||||
T GetArgument(const int argc, char **argv, std::string &help,
|
T GetArgument(const int argc, char **argv, std::string &help,
|
||||||
|
@ -226,6 +231,12 @@ void FloatToHalfBuffer(std::vector<half>& result, const std::vector<float>& sour
|
||||||
Buffer<float> HalfToFloatBuffer(const Buffer<half>& source, cl_command_queue queue_raw);
|
Buffer<float> HalfToFloatBuffer(const Buffer<half>& source, cl_command_queue queue_raw);
|
||||||
void FloatToHalfBuffer(Buffer<half>& result, const Buffer<float>& source, cl_command_queue queue_raw);
|
void FloatToHalfBuffer(Buffer<half>& result, const Buffer<float>& source, cl_command_queue queue_raw);
|
||||||
|
|
||||||
|
// Converts a 'real' value to a 'real argument' value to be passed to a kernel. Normally there is
|
||||||
|
// no conversion, but half-precision is not supported as kernel argument so it is converted to float.
|
||||||
|
template <typename T> struct RealArg { using Type = T; };
|
||||||
|
template <> struct RealArg<half> { using Type = float; };
|
||||||
|
template <typename T> typename RealArg<T>::Type GetRealArg(const T value);
|
||||||
|
|
||||||
// =================================================================================================
|
// =================================================================================================
|
||||||
|
|
||||||
// Rounding functions
|
// Rounding functions
|
||||||
|
|
|
@ -15,6 +15,7 @@
|
||||||
#include <vector>
|
#include <vector>
|
||||||
#include <iostream>
|
#include <iostream>
|
||||||
#include <cmath>
|
#include <cmath>
|
||||||
|
#include <cstdlib>
|
||||||
|
|
||||||
#include "test/correctness/tester.hpp"
|
#include "test/correctness/tester.hpp"
|
||||||
|
|
||||||
|
@ -27,8 +28,8 @@ template <typename T, typename U>
|
||||||
Tester<T,U>::Tester(int argc, char *argv[], const bool silent,
|
Tester<T,U>::Tester(int argc, char *argv[], const bool silent,
|
||||||
const std::string &name, const std::vector<std::string> &options):
|
const std::string &name, const std::vector<std::string> &options):
|
||||||
help_("Options given/available:\n"),
|
help_("Options given/available:\n"),
|
||||||
platform_(Platform(GetArgument(argc, argv, help_, kArgPlatform, size_t{0}))),
|
platform_(Platform(GetArgument(argc, argv, help_, kArgPlatform, ConvertArgument(std::getenv("CLBLAST_PLATFORM"), size_t{0})))),
|
||||||
device_(Device(platform_, GetArgument(argc, argv, help_, kArgDevice, size_t{0}))),
|
device_(Device(platform_, GetArgument(argc, argv, help_, kArgDevice, ConvertArgument(std::getenv("CLBLAST_DEVICE"), size_t{0})))),
|
||||||
context_(Context(device_)),
|
context_(Context(device_)),
|
||||||
queue_(Queue(context_, device_)),
|
queue_(Queue(context_, device_)),
|
||||||
full_test_(CheckArgument(argc, argv, help_, kArgFullTest)),
|
full_test_(CheckArgument(argc, argv, help_, kArgFullTest)),
|
||||||
|
|
|
@ -113,6 +113,7 @@ Arguments<U> Client<T,U>::ParseArguments(int argc, char *argv[], const size_t le
|
||||||
args.print_help = CheckArgument(argc, argv, help, kArgHelp);
|
args.print_help = CheckArgument(argc, argv, help, kArgHelp);
|
||||||
args.silent = CheckArgument(argc, argv, help, kArgQuiet);
|
args.silent = CheckArgument(argc, argv, help, kArgQuiet);
|
||||||
args.no_abbrv = CheckArgument(argc, argv, help, kArgNoAbbreviations);
|
args.no_abbrv = CheckArgument(argc, argv, help, kArgNoAbbreviations);
|
||||||
|
warm_up_ = CheckArgument(argc, argv, help, kArgWarmUp);
|
||||||
|
|
||||||
// Prints the chosen (or defaulted) arguments to screen. This also serves as the help message,
|
// Prints the chosen (or defaulted) arguments to screen. This also serves as the help message,
|
||||||
// which is thus always displayed (unless silence is specified).
|
// which is thus always displayed (unless silence is specified).
|
||||||
|
@ -244,12 +245,24 @@ template <typename T, typename U>
|
||||||
double Client<T,U>::TimedExecution(const size_t num_runs, const Arguments<U> &args,
|
double Client<T,U>::TimedExecution(const size_t num_runs, const Arguments<U> &args,
|
||||||
Buffers<T> &buffers, Queue &queue,
|
Buffers<T> &buffers, Queue &queue,
|
||||||
Routine run_blas, const std::string &library_name) {
|
Routine run_blas, const std::string &library_name) {
|
||||||
|
auto status = StatusCode::kSuccess;
|
||||||
|
|
||||||
|
// Do an optional warm-up to omit compilation times and initialisations from the measurements
|
||||||
|
if (warm_up_) {
|
||||||
|
try {
|
||||||
|
status = run_blas(args, buffers, queue);
|
||||||
|
} catch (...) { status = static_cast<StatusCode>(kUnknownError); }
|
||||||
|
if (status != StatusCode::kSuccess) {
|
||||||
|
throw std::runtime_error(library_name+" error: "+ToString(static_cast<int>(status)));
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
// Start the timed part
|
||||||
auto timings = std::vector<double>(num_runs);
|
auto timings = std::vector<double>(num_runs);
|
||||||
for (auto &timing: timings) {
|
for (auto &timing: timings) {
|
||||||
auto start_time = std::chrono::steady_clock::now();
|
auto start_time = std::chrono::steady_clock::now();
|
||||||
|
|
||||||
// Executes the main computation
|
// Executes the main computation
|
||||||
auto status = StatusCode::kSuccess;
|
|
||||||
try {
|
try {
|
||||||
status = run_blas(args, buffers, queue);
|
status = run_blas(args, buffers, queue);
|
||||||
} catch (...) { status = static_cast<StatusCode>(kUnknownError); }
|
} catch (...) { status = static_cast<StatusCode>(kUnknownError); }
|
||||||
|
|
|
@ -82,6 +82,9 @@ class Client {
|
||||||
const std::vector<std::string> options_;
|
const std::vector<std::string> options_;
|
||||||
const GetMetric get_flops_;
|
const GetMetric get_flops_;
|
||||||
const GetMetric get_bytes_;
|
const GetMetric get_bytes_;
|
||||||
|
|
||||||
|
// Extra arguments
|
||||||
|
bool warm_up_; // if enabled, do a warm-up run first before measuring execution time
|
||||||
};
|
};
|
||||||
|
|
||||||
// =================================================================================================
|
// =================================================================================================
|
||||||
|
|
Loading…
Reference in a new issue