2017-01-15 17:30:00 +01:00
|
|
|
|
|
|
|
// =================================================================================================
|
|
|
|
// 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 implements a class with static methods to describe the Xinvert routine. Examples of
|
|
|
|
// such 'descriptions' are how to calculate the size a of buffer or how to run the routine. These
|
|
|
|
// static methods are used by the correctness tester and the performance tester.
|
|
|
|
//
|
|
|
|
// =================================================================================================
|
|
|
|
|
|
|
|
#ifndef CLBLAST_TEST_ROUTINES_XINVERT_H_
|
|
|
|
#define CLBLAST_TEST_ROUTINES_XINVERT_H_
|
|
|
|
|
2017-04-11 21:50:18 +02:00
|
|
|
#include "test/routines/common.hpp"
|
2017-10-25 20:35:21 +02:00
|
|
|
#include "src/routines/levelx/xinvert.hpp"
|
2017-01-15 17:30:00 +01:00
|
|
|
|
|
|
|
namespace clblast {
|
|
|
|
// =================================================================================================
|
|
|
|
|
|
|
|
template <typename T>
|
2017-04-01 13:36:24 +02:00
|
|
|
StatusCode RunReference(const Arguments<T> &args, BuffersHost<T> &buffers_host) {
|
2017-01-15 17:30:00 +01:00
|
|
|
const bool is_upper = ((args.triangle == Triangle::kUpper && args.layout != Layout::kRowMajor) ||
|
|
|
|
(args.triangle == Triangle::kLower && args.layout == Layout::kRowMajor));
|
|
|
|
|
|
|
|
// Helper variables
|
|
|
|
const auto block_size = args.m;
|
|
|
|
const auto num_blocks = CeilDiv(args.n, block_size);
|
|
|
|
const auto a_ld = args.a_ld;
|
|
|
|
const auto b_ld = block_size;
|
2017-02-25 12:23:04 +01:00
|
|
|
|
|
|
|
// Checks for valid arguments
|
|
|
|
if ((block_size == 0) || (args.n == 0)) {
|
2017-01-15 17:30:00 +01:00
|
|
|
return StatusCode::kInvalidDimension;
|
|
|
|
}
|
2017-02-25 12:23:04 +01:00
|
|
|
if ((block_size % 16 != 0) || (block_size > 128)) {
|
|
|
|
return StatusCode::kUnknownError;
|
|
|
|
}
|
2017-01-15 17:30:00 +01:00
|
|
|
|
2017-10-25 20:35:21 +02:00
|
|
|
// Start at zero
|
|
|
|
for (size_t i =0; i < args.m; ++i) {
|
|
|
|
for (size_t j = 0; j < args.n; ++j) {
|
|
|
|
buffers_host.b_mat[j * args.m + i] = T{0.0};
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
2017-01-15 17:30:00 +01:00
|
|
|
// Loops over the amount of diagonal blocks of size args.m by args.m each
|
|
|
|
for (auto block_id = size_t{0}; block_id < num_blocks; ++block_id) {
|
|
|
|
const auto a_offset = block_id * (block_size + a_ld * block_size) + args.a_offset;
|
|
|
|
const auto b_offset = block_id * block_size * block_size;
|
|
|
|
|
|
|
|
// Inverts the diagonal elements of the matrix
|
|
|
|
for (auto i = size_t{0}; i < block_size; ++i) {
|
|
|
|
auto a_value = T{1.0};
|
|
|
|
if (args.diagonal == Diagonal::kNonUnit) {
|
|
|
|
if (i + block_id * block_size < args.n) {
|
2017-04-01 13:36:24 +02:00
|
|
|
if (buffers_host.a_mat[i * a_ld + i + a_offset] == T{0.0}) { return StatusCode::kUnknownError; }
|
|
|
|
a_value = T{1.0} / buffers_host.a_mat[i * a_ld + i + a_offset];
|
2017-01-15 17:30:00 +01:00
|
|
|
}
|
|
|
|
}
|
2017-04-01 13:36:24 +02:00
|
|
|
buffers_host.b_mat[i * b_ld + i + b_offset] = a_value;
|
2017-01-15 17:30:00 +01:00
|
|
|
}
|
|
|
|
|
|
|
|
// Inverts the upper triangle row by row
|
|
|
|
if (is_upper) {
|
|
|
|
for (int i = static_cast<int>(block_size) - 2; i >= 0; --i) {
|
|
|
|
for (auto j = static_cast<int>(block_size) - 1; j > i; --j) {
|
|
|
|
auto sum = T{0.0};
|
|
|
|
for (auto k = i + 1; k <= j; ++k) {
|
|
|
|
auto a_value = T{0.0};
|
|
|
|
if ((i + block_id * block_size < args.n) && (k + block_id * block_size < args.n)) {
|
2017-04-01 13:36:24 +02:00
|
|
|
a_value = buffers_host.a_mat[k * a_ld + i + a_offset];
|
2017-01-15 17:30:00 +01:00
|
|
|
}
|
2017-04-01 13:36:24 +02:00
|
|
|
sum += a_value * buffers_host.b_mat[j * b_ld + k + b_offset];
|
2017-01-15 17:30:00 +01:00
|
|
|
}
|
2017-04-01 13:36:24 +02:00
|
|
|
buffers_host.b_mat[j * b_ld + i + b_offset] = - sum * buffers_host.b_mat[i * b_ld + i + b_offset];
|
2017-01-15 17:30:00 +01:00
|
|
|
}
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
// Inverts the lower triangle row by row
|
|
|
|
else {
|
|
|
|
for (auto i = size_t{1}; i < block_size; ++i) {
|
|
|
|
for (auto j = size_t{0}; j < i; ++j) {
|
|
|
|
auto sum = T{0.0};
|
|
|
|
for (auto k = j; k < i; ++k) {
|
|
|
|
auto a_value = T{0.0};
|
|
|
|
if ((i + block_id * block_size < args.n) && (k + block_id * block_size < args.n)) {
|
2017-04-01 13:36:24 +02:00
|
|
|
a_value = buffers_host.a_mat[k * a_ld + i + a_offset];
|
2017-01-15 17:30:00 +01:00
|
|
|
}
|
2017-04-01 13:36:24 +02:00
|
|
|
sum += a_value * buffers_host.b_mat[j * b_ld + k + b_offset];
|
2017-01-15 17:30:00 +01:00
|
|
|
}
|
2017-04-01 13:36:24 +02:00
|
|
|
buffers_host.b_mat[j * b_ld + i + b_offset] = - sum * buffers_host.b_mat[i * b_ld + i + b_offset];
|
2017-01-15 17:30:00 +01:00
|
|
|
}
|
|
|
|
}
|
|
|
|
}
|
|
|
|
}
|
|
|
|
return StatusCode::kSuccess;
|
|
|
|
}
|
|
|
|
|
|
|
|
// Half-precision version calling the above reference implementation after conversions
|
|
|
|
template <>
|
2017-04-01 13:36:24 +02:00
|
|
|
StatusCode RunReference<half>(const Arguments<half> &args, BuffersHost<half> &buffers_host) {
|
|
|
|
auto a_buffer2 = HalfToFloatBuffer(buffers_host.a_mat);
|
|
|
|
auto b_buffer2 = HalfToFloatBuffer(buffers_host.b_mat);
|
|
|
|
auto dummy = std::vector<float>(0);
|
|
|
|
auto buffers2 = BuffersHost<float>{dummy, dummy, a_buffer2, b_buffer2, dummy, dummy, dummy};
|
2017-01-15 17:30:00 +01:00
|
|
|
auto args2 = Arguments<float>();
|
|
|
|
args2.a_size = args.a_size; args2.b_size = args.b_size;
|
|
|
|
args2.a_ld = args.a_ld; args2.m = args.m; args2.n = args.n;
|
|
|
|
args2.a_offset = args.a_offset;
|
|
|
|
args2.layout = args.layout; args2.triangle = args.triangle; args2.diagonal = args.diagonal;
|
2017-04-01 13:36:24 +02:00
|
|
|
auto status = RunReference(args2, buffers2);
|
|
|
|
FloatToHalfBuffer(buffers_host.b_mat, b_buffer2);
|
2017-01-15 17:30:00 +01:00
|
|
|
return status;
|
|
|
|
}
|
|
|
|
|
|
|
|
// =================================================================================================
|
|
|
|
|
|
|
|
// See comment at top of file for a description of the class
|
|
|
|
template <typename T>
|
|
|
|
class TestXinvert {
|
|
|
|
public:
|
|
|
|
|
|
|
|
// The BLAS level: 4 for the extra routines
|
|
|
|
static size_t BLASLevel() { return 4; }
|
|
|
|
|
|
|
|
// The list of arguments relevant for this routine
|
|
|
|
static std::vector<std::string> GetOptions() {
|
|
|
|
return {kArgN, kArgM,
|
|
|
|
kArgLayout, kArgTriangle, kArgDiagonal,
|
|
|
|
kArgALeadDim, kArgAOffset};
|
|
|
|
}
|
2017-04-01 13:36:24 +02:00
|
|
|
static std::vector<std::string> BuffersIn() { return {kBufMatA, kBufMatB}; }
|
|
|
|
static std::vector<std::string> BuffersOut() { return {kBufMatB}; }
|
2017-01-15 17:30:00 +01:00
|
|
|
|
|
|
|
// Describes how to obtain the sizes of the buffers
|
|
|
|
static size_t GetSizeA(const Arguments<T> &args) {
|
|
|
|
return args.n * args.a_ld + args.a_offset;
|
|
|
|
}
|
|
|
|
static size_t GetSizeB(const Arguments<T> &args) {
|
|
|
|
const auto block_size = args.m;
|
|
|
|
const auto num_blocks = CeilDiv(args.n, block_size);
|
|
|
|
return num_blocks * block_size * block_size;
|
|
|
|
}
|
|
|
|
|
|
|
|
// Describes how to set the sizes of all the buffers
|
|
|
|
static void SetSizes(Arguments<T> &args) {
|
|
|
|
args.a_size = GetSizeA(args);
|
|
|
|
args.b_size = GetSizeB(args);
|
|
|
|
}
|
|
|
|
|
|
|
|
// Describes what the default values of the leading dimensions of the matrices are
|
|
|
|
static size_t DefaultLDA(const Arguments<T> &args) { return args.n; }
|
|
|
|
static size_t DefaultLDB(const Arguments<T> &) { return 1; } // N/A for this routine
|
|
|
|
static size_t DefaultLDC(const Arguments<T> &) { return 1; } // N/A for this routine
|
|
|
|
|
|
|
|
// Describes which omatcopyose options are relevant for this routine
|
|
|
|
using Transposes = std::vector<Transpose>;
|
|
|
|
static Transposes GetATransposes(const Transposes &) { return {}; } // N/A for this routine
|
|
|
|
static Transposes GetBTransposes(const Transposes &) { return {}; } // N/A for this routine
|
|
|
|
|
2017-03-04 15:21:33 +01:00
|
|
|
// Describes how to prepare the input data
|
|
|
|
static void PrepareData(const Arguments<T>&, Queue&, const int, std::vector<T>&,
|
|
|
|
std::vector<T>&, std::vector<T>&, std::vector<T>&, std::vector<T>&,
|
|
|
|
std::vector<T>&, std::vector<T>&) {} // N/A for this routine
|
|
|
|
|
2017-01-15 17:30:00 +01:00
|
|
|
// Describes how to run the CLBlast routine
|
2017-03-08 20:10:20 +01:00
|
|
|
static StatusCode RunRoutine(const Arguments<T> &args, Buffers<T> &buffers, Queue &queue) {
|
2017-01-15 17:30:00 +01:00
|
|
|
try {
|
2017-10-15 19:35:21 +02:00
|
|
|
#ifdef OPENCL_API
|
|
|
|
auto event = cl_event{};
|
|
|
|
auto inverter = Xinvert<T>(queue, &event);
|
|
|
|
inverter.InvertMatrixDiagonalBlocks(args.layout, args.triangle, args.diagonal,
|
|
|
|
args.n, args.m,
|
|
|
|
buffers.a_mat, args.a_offset, args.a_ld,
|
|
|
|
buffers.b_mat);
|
|
|
|
clWaitForEvents(1, &event);
|
|
|
|
clReleaseEvent(event);
|
|
|
|
#elif CUDA_API
|
|
|
|
auto inverter = Xinvert<T>(queue, nullptr);
|
|
|
|
inverter.InvertMatrixDiagonalBlocks(args.layout, args.triangle, args.diagonal,
|
|
|
|
args.n, args.m,
|
|
|
|
buffers.a_mat, args.a_offset, args.a_ld,
|
|
|
|
buffers.b_mat);
|
|
|
|
cuStreamSynchronize(queue());
|
|
|
|
#endif
|
2017-01-15 17:30:00 +01:00
|
|
|
} catch (...) { return DispatchException(); }
|
|
|
|
return StatusCode::kSuccess;
|
|
|
|
}
|
|
|
|
|
|
|
|
// Describes how to run a naive version of the routine (for correctness/performance comparison).
|
|
|
|
// Note that a proper clBLAS or CPU BLAS comparison is not available for non-BLAS routines.
|
2017-03-08 20:10:20 +01:00
|
|
|
static StatusCode RunReference1(const Arguments<T> &args, Buffers<T> &buffers, Queue &queue) {
|
2017-04-01 13:36:24 +02:00
|
|
|
auto buffers_host = BuffersHost<T>();
|
|
|
|
DeviceToHost(args, buffers, buffers_host, queue, BuffersIn());
|
|
|
|
const auto status = RunReference(args, buffers_host);
|
|
|
|
HostToDevice(args, buffers, buffers_host, queue, BuffersOut());
|
|
|
|
return status;
|
2017-01-15 17:30:00 +01:00
|
|
|
}
|
|
|
|
|
2017-04-01 13:36:24 +02:00
|
|
|
static StatusCode RunReference2(const Arguments<T> &args, BuffersHost<T> &buffers_host, Queue&) {
|
|
|
|
return RunReference(args, buffers_host);
|
2017-01-15 17:30:00 +01:00
|
|
|
}
|
2017-04-10 22:54:14 +02:00
|
|
|
static StatusCode RunReference3(const Arguments<T> &args, BuffersCUDA<T> &buffers, Queue &) {
|
|
|
|
return StatusCode::kUnknownError;
|
|
|
|
}
|
2017-01-15 17:30:00 +01:00
|
|
|
|
|
|
|
// Describes how to download the results of the computation (more importantly: which buffer)
|
|
|
|
static std::vector<T> DownloadResult(const Arguments<T> &args, Buffers<T> &buffers, Queue &queue) {
|
|
|
|
std::vector<T> result(args.b_size, static_cast<T>(0));
|
|
|
|
buffers.b_mat.Read(queue, args.b_size, result);
|
|
|
|
return result;
|
|
|
|
}
|
|
|
|
|
|
|
|
// Describes how to compute the indices of the result buffer
|
|
|
|
static size_t ResultID1(const Arguments<T> &args) { return args.m; }
|
|
|
|
static size_t ResultID2(const Arguments<T> &args) { return Ceil(args.n, args.m); }
|
|
|
|
static size_t GetResultIndex(const Arguments<T> &args, const size_t id1, const size_t id2) {
|
|
|
|
return id1 * Ceil(args.n, args.m) + id2;
|
|
|
|
}
|
|
|
|
|
|
|
|
// Describes how to compute performance metrics
|
|
|
|
static size_t GetFlops(const Arguments<T> &args) {
|
|
|
|
const auto block_size = args.m;
|
|
|
|
const auto num_blocks = CeilDiv(args.n, block_size);
|
|
|
|
return num_blocks * (block_size * (block_size / 2) * (block_size / 2));
|
|
|
|
}
|
|
|
|
static size_t GetBytes(const Arguments<T> &args) {
|
|
|
|
return (args.a_size * args.b_size) * sizeof(T);
|
|
|
|
}
|
|
|
|
};
|
|
|
|
|
|
|
|
// =================================================================================================
|
|
|
|
} // namespace clblast
|
|
|
|
|
|
|
|
// CLBLAST_TEST_ROUTINES_XINVERT_H_
|
|
|
|
#endif
|