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238 lines
12 KiB
C++
238 lines
12 KiB
C++
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// =================================================================================================
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// This file is part of the CLBlast project. The project is licensed under Apache Version 2.0. This
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// project loosely follows the Google C++ styleguide and uses a tab-size of two spaces and a max-
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// width of 100 characters per line.
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//
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// Author(s):
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// Cedric Nugteren <www.cedricnugteren.nl>
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//
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// This file implements a class with static methods to describe the XgemmBatched routine. Examples of
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// such 'descriptions' are how to calculate the size a of buffer or how to run the routine. These
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// static methods are used by the correctness tester and the performance tester.
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//
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// =================================================================================================
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#ifndef CLBLAST_TEST_ROUTINES_XGEMMBATCHED_H_
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#define CLBLAST_TEST_ROUTINES_XGEMMBATCHED_H_
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#include "test/routines/common.hpp"
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namespace clblast {
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// =================================================================================================
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// See comment at top of file for a description of the class
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template <typename T>
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class TestXgemmBatched {
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public:
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// Although it is a non-BLAS routine, it can still be tested against level-3 routines in a loop
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static size_t BLASLevel() { return 3; }
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// The list of arguments relevant for this routine
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static std::vector<std::string> GetOptions() {
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return {kArgM, kArgN, kArgK,
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kArgLayout, kArgATransp, kArgBTransp,
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kArgALeadDim, kArgBLeadDim, kArgCLeadDim,
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kArgAOffset, kArgBOffset, kArgCOffset,
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kArgBatchCount, kArgAlpha, kArgBeta};
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}
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static std::vector<std::string> BuffersIn() { return {kBufMatA, kBufMatB, kBufMatC}; }
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static std::vector<std::string> BuffersOut() { return {kBufMatC}; }
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// Helper for the sizes per batch
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static size_t PerBatchSizeA(const Arguments<T> &args) {
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auto a_rotated = (args.layout == Layout::kColMajor && args.a_transpose != Transpose::kNo) ||
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(args.layout == Layout::kRowMajor && args.a_transpose == Transpose::kNo);
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auto a_two = (a_rotated) ? args.m : args.k;
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return a_two * args.a_ld;
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}
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static size_t PerBatchSizeB(const Arguments<T> &args) {
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auto b_rotated = (args.layout == Layout::kColMajor && args.b_transpose != Transpose::kNo) ||
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(args.layout == Layout::kRowMajor && args.b_transpose == Transpose::kNo);
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auto b_two = (b_rotated) ? args.k : args.n;
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return b_two * args.b_ld;
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}
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static size_t PerBatchSizeC(const Arguments<T> &args) {
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auto c_rotated = (args.layout == Layout::kRowMajor);
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auto c_two = (c_rotated) ? args.m : args.n;
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return c_two * args.c_ld;
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}
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// Describes how to obtain the sizes of the buffers
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static size_t GetSizeA(const Arguments<T> &args) {
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return PerBatchSizeA(args) * args.batch_count + args.a_offset;
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}
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static size_t GetSizeB(const Arguments<T> &args) {
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return PerBatchSizeB(args) * args.batch_count + args.b_offset;
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}
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static size_t GetSizeC(const Arguments<T> &args) {
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return PerBatchSizeC(args) * args.batch_count + args.c_offset;
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}
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// Describes how to set the sizes of all the buffers
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static void SetSizes(Arguments<T> &args, Queue&) {
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args.a_size = GetSizeA(args);
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args.b_size = GetSizeB(args);
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args.c_size = GetSizeC(args);
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// Also sets the batch-related variables
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args.a_offsets = std::vector<size_t>(args.batch_count);
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args.b_offsets = std::vector<size_t>(args.batch_count);
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args.c_offsets = std::vector<size_t>(args.batch_count);
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args.alphas = std::vector<T>(args.batch_count);
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args.betas = std::vector<T>(args.batch_count);
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for (auto batch = size_t{0}; batch < args.batch_count; ++batch) {
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args.a_offsets[batch] = batch * PerBatchSizeA(args) + args.a_offset;
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args.b_offsets[batch] = batch * PerBatchSizeB(args) + args.b_offset;
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args.c_offsets[batch] = batch * PerBatchSizeC(args) + args.c_offset;
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args.alphas[batch] = args.alpha + Constant<T>(static_cast<double>(batch + 1));
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args.betas[batch] = args.beta + Constant<T>(static_cast<double>(batch + 1));
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}
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}
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// Describes what the default values of the leading dimensions of the matrices are
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static size_t DefaultLDA(const Arguments<T> &args) { return args.k; }
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static size_t DefaultLDB(const Arguments<T> &args) { return args.n; }
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static size_t DefaultLDC(const Arguments<T> &args) { return args.n; }
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// Describes which transpose options are relevant for this routine
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using Transposes = std::vector<Transpose>;
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static Transposes GetATransposes(const Transposes &all) { return all; }
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static Transposes GetBTransposes(const Transposes &all) { return all; }
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// Describes how to prepare the input data
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static void PrepareData(const Arguments<T>&, Queue&, const int, std::vector<T>&,
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std::vector<T>&, std::vector<T>&, std::vector<T>&, std::vector<T>&,
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std::vector<T>&, std::vector<T>&) {} // N/A for this routine
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// Describes how to run the CLBlast routine
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static StatusCode RunRoutine(const Arguments<T> &args, Buffers<T> &buffers, Queue &queue) {
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// Relaxed requirement on ld_a and ld_b within the library, this is here to match clBLAS
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auto a_rotated = (args.layout == Layout::kColMajor && args.a_transpose != Transpose::kNo) ||
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(args.layout == Layout::kRowMajor && args.a_transpose == Transpose::kNo);
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auto b_rotated = (args.layout == Layout::kColMajor && args.b_transpose != Transpose::kNo) ||
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(args.layout == Layout::kRowMajor && args.b_transpose == Transpose::kNo);
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auto a_one = (!a_rotated) ? args.m : args.k;
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auto b_one = (!b_rotated) ? args.k : args.n;
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if (args.a_ld < a_one) { return StatusCode::kInvalidLeadDimA; }
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if (args.b_ld < b_one) { return StatusCode::kInvalidLeadDimB; }
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#ifdef OPENCL_API
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auto queue_plain = queue();
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auto event = cl_event{};
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auto status = GemmBatched(args.layout, args.a_transpose, args.b_transpose,
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args.m, args.n, args.k, args.alphas.data(),
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buffers.a_mat(), args.a_offsets.data(), args.a_ld,
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buffers.b_mat(), args.b_offsets.data(), args.b_ld, args.betas.data(),
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buffers.c_mat(), args.c_offsets.data(), args.c_ld,
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args.batch_count,
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&queue_plain, &event);
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if (status == StatusCode::kSuccess) { clWaitForEvents(1, &event); clReleaseEvent(event); }
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#elif CUDA_API
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auto status = GemmBatched(args.layout, args.a_transpose, args.b_transpose,
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args.m, args.n, args.k, args.alphas.data(),
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buffers.a_mat(), args.a_offsets.data(), args.a_ld,
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buffers.b_mat(), args.b_offsets.data(), args.b_ld, args.betas.data(),
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buffers.c_mat(), args.c_offsets.data(), args.c_ld,
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args.batch_count,
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queue.GetContext()(), queue.GetDevice()());
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cuStreamSynchronize(queue());
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#endif
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return status;
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}
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// Describes how to run the clBLAS routine (for correctness/performance comparison)
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#ifdef CLBLAST_REF_CLBLAS
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static StatusCode RunReference1(const Arguments<T> &args, Buffers<T> &buffers, Queue &queue) {
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auto queue_plain = queue();
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for (auto batch = size_t{0}; batch < args.batch_count; ++batch) {
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auto event = cl_event{};
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auto status = clblasXgemm(convertToCLBLAS(args.layout),
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convertToCLBLAS(args.a_transpose),
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convertToCLBLAS(args.b_transpose),
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args.m, args.n, args.k, args.alphas[batch],
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buffers.a_mat, args.a_offsets[batch], args.a_ld,
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buffers.b_mat, args.b_offsets[batch], args.b_ld, args.betas[batch],
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buffers.c_mat, args.c_offsets[batch], args.c_ld,
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1, &queue_plain, 0, nullptr, &event);
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clWaitForEvents(1, &event);
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if (static_cast<StatusCode>(status) != StatusCode::kSuccess) {
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return static_cast<StatusCode>(status);
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}
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}
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return StatusCode::kSuccess;
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}
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#endif
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// Describes how to run the CPU BLAS routine (for correctness/performance comparison)
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#ifdef CLBLAST_REF_CBLAS
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static StatusCode RunReference2(const Arguments<T> &args, BuffersHost<T> &buffers_host, Queue &) {
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for (auto batch = size_t{0}; batch < args.batch_count; ++batch) {
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cblasXgemm(convertToCBLAS(args.layout),
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convertToCBLAS(args.a_transpose),
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convertToCBLAS(args.b_transpose),
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args.m, args.n, args.k, args.alphas[batch],
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buffers_host.a_mat, args.a_offsets[batch], args.a_ld,
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buffers_host.b_mat, args.b_offsets[batch], args.b_ld, args.betas[batch],
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buffers_host.c_mat, args.c_offsets[batch], args.c_ld);
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}
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return StatusCode::kSuccess;
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}
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#endif
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// Describes how to run the cuBLAS routine (for correctness/performance comparison)
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#ifdef CLBLAST_REF_CUBLAS
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static StatusCode RunReference3(const Arguments<T> &args, BuffersCUDA<T> &buffers, Queue &) {
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for (auto batch = size_t{0}; batch < args.batch_count; ++batch) {
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auto status = cublasXgemm(reinterpret_cast<cublasHandle_t>(args.cublas_handle), args.layout,
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convertToCUBLAS(args.a_transpose),
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convertToCUBLAS(args.b_transpose),
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args.m, args.n, args.k, args.alphas[batch],
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buffers.a_mat, args.a_offsets[batch], args.a_ld,
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buffers.b_mat, args.b_offsets[batch], args.b_ld, args.betas[batch],
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buffers.c_mat, args.c_offsets[batch], args.c_ld);
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if (status != CUBLAS_STATUS_SUCCESS) { return StatusCode::kUnknownError; }
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}
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return StatusCode::kSuccess;
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}
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#endif
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// Describes how to download the results of the computation (more importantly: which buffer)
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static std::vector<T> DownloadResult(const Arguments<T> &args, Buffers<T> &buffers, Queue &queue) {
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std::vector<T> result(args.c_size, static_cast<T>(0));
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buffers.c_mat.Read(queue, args.c_size, result);
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return result;
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}
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// Describes how to compute the indices of the result buffer
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static size_t ResultID1(const Arguments<T> &args) { return args.m; }
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static size_t ResultID2(const Arguments<T> &args) { return args.n * args.batch_count; }
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static size_t GetResultIndex(const Arguments<T> &args, const size_t id1, const size_t id2_3) {
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const size_t id2 = id2_3 % args.n;
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const size_t id3 = id2_3 / args.n;
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return (args.layout == Layout::kRowMajor) ?
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id1*args.c_ld + id2 + args.c_offsets[id3]:
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id2*args.c_ld + id1 + args.c_offsets[id3];
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}
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// Describes how to compute performance metrics
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static size_t GetFlops(const Arguments<T> &args) {
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if((args.precision == Precision::kComplexSingle) || (args.precision == Precision::kComplexDouble)) {
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// complex flops
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return args.batch_count * args.m * args.n * (8 * args.k - 2);
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} else {
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// scalar flops
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return args.batch_count * args.m * args.n * (2 * args.k - 1);
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}
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}
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static size_t GetBytes(const Arguments<T> &args) {
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return args.batch_count * (args.m*args.k + args.k*args.n + 2*args.m*args.n) * sizeof(T);
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}
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};
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// =================================================================================================
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} // namespace clblast
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// CLBLAST_TEST_ROUTINES_XGEMMBATCHED_H_
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#endif
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