402 lines
15 KiB
C++
402 lines
15 KiB
C++
/***************************************************************************************************
|
|
* Copyright (c) 2018, NVIDIA CORPORATION. All rights reserved.
|
|
*
|
|
* Redistribution and use in source and binary forms, with or without modification, are permitted
|
|
* provided that the following conditions are met:
|
|
* * Redistributions of source code must retain the above copyright notice, this list of
|
|
* conditions and the following disclaimer.
|
|
* * Redistributions in binary form must reproduce the above copyright notice, this list of
|
|
* conditions and the following disclaimer in the documentation and/or other materials
|
|
* provided with the distribution.
|
|
* * Neither the name of the NVIDIA CORPORATION nor the names of its contributors may be used
|
|
* to endorse or promote products derived from this software without specific prior written
|
|
* permission.
|
|
*
|
|
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR
|
|
* IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND
|
|
* FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL NVIDIA CORPORATION BE LIABLE
|
|
* FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
|
|
* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;
|
|
* OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT,
|
|
* STRICT LIABILITY, OR TOR (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
|
|
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
|
|
*
|
|
**************************************************************************************************/
|
|
|
|
#pragma once
|
|
|
|
#include <utility>
|
|
#include "cutlass/cutlass.h"
|
|
#include "tools/test/unit/gemm/gemm_testbed.h"
|
|
#include "cutlass/gemm/device_gemm.h"
|
|
#include "cutlass/gemm/device_gemm_traits.h"
|
|
|
|
template <typename GemmTraits_>
|
|
static void run_gemm(
|
|
int m,
|
|
int n,
|
|
int k,
|
|
int lda,
|
|
int ldb,
|
|
int ldc,
|
|
typename test::GemmTestbedTraits<typename GemmTraits_::Epilogue::Scalar>::host_type alpha =
|
|
typename test::GemmTestbedTraits<typename GemmTraits_::Epilogue::Scalar>::host_type(1.0f),
|
|
typename test::GemmTestbedTraits<typename GemmTraits_::Epilogue::Scalar>::host_type beta =
|
|
typename test::GemmTestbedTraits<typename GemmTraits_::Epilogue::Scalar>::host_type(0.0f)) {
|
|
|
|
typedef typename GemmTraits_::KernelClass Gemm;
|
|
typename Gemm::Params params;
|
|
|
|
test::GemmTestbed<
|
|
typename test::GemmTestbedTraits<
|
|
typename GemmTraits_::GemmConfig::ScalarA>::host_type, // AType
|
|
typename test::GemmTestbedTraits<
|
|
typename GemmTraits_::GemmConfig::ScalarB>::host_type, // BType
|
|
typename test::GemmTestbedTraits<
|
|
typename GemmTraits_::Epilogue::ScalarC>::host_type, // CType
|
|
typename test::GemmTestbedTraits<
|
|
typename GemmTraits_::Epilogue::Accumulators::Element>::host_type, // Accumulator
|
|
typename test::GemmTestbedTraits<typename GemmTraits_::Epilogue::Scalar>::host_type // Scalar
|
|
>
|
|
testbed(m,
|
|
n,
|
|
k,
|
|
lda,
|
|
ldb,
|
|
ldc,
|
|
test::convert(GemmTraits_::kLayoutA),
|
|
test::convert(GemmTraits_::kLayoutB),
|
|
alpha,
|
|
beta);
|
|
|
|
testbed.initialize();
|
|
|
|
if (testbed.has_cublas_support()) {
|
|
EXPECT_TRUE(testbed.verify_host_with_cublas());
|
|
EXPECT_TRUE(testbed.verify_reference_with_cublas());
|
|
}
|
|
|
|
|
|
params.initialize(testbed.M(),
|
|
testbed.N(),
|
|
testbed.K(),
|
|
testbed.alpha,
|
|
testbed.ptr_A(),
|
|
testbed.lda(),
|
|
testbed.ptr_B(),
|
|
testbed.ldb(),
|
|
testbed.beta,
|
|
testbed.ptr_C_initial(),
|
|
testbed.ldc(),
|
|
testbed.ptr_computed(),
|
|
testbed.ldc());
|
|
|
|
Gemm::launch(params);
|
|
|
|
cudaError_t result = cudaDeviceSynchronize();
|
|
ASSERT_EQ(result, cudaSuccess) << "\nCUDA kernel launch error: " << cudaGetErrorString(result)
|
|
<< "\n";
|
|
|
|
if (testbed.has_cublas_support()) {
|
|
ASSERT_TRUE(testbed.verify_with_cublas());
|
|
} else {
|
|
ASSERT_TRUE(testbed.verify_with_host());
|
|
}
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////////////////////////////////////
|
|
|
|
template <typename GemmTraits_>
|
|
static void run_gemm(
|
|
int m,
|
|
int n,
|
|
int k,
|
|
typename test::GemmTestbedTraits<typename GemmTraits_::Epilogue::Scalar>::host_type alpha =
|
|
typename test::GemmTestbedTraits<typename GemmTraits_::Epilogue::Scalar>::host_type(1.0f),
|
|
typename test::GemmTestbedTraits<typename GemmTraits_::Epilogue::Scalar>::host_type beta =
|
|
typename test::GemmTestbedTraits<typename GemmTraits_::Epilogue::Scalar>::host_type(0.0f)) {
|
|
//typedef cutlass::gemm::Gemm<GemmTraits_> Gemm;
|
|
typedef typename GemmTraits_::KernelClass Gemm;
|
|
typename Gemm::Params params;
|
|
|
|
typedef test::GemmTestbed<
|
|
typename test::GemmTestbedTraits<
|
|
typename GemmTraits_::GemmConfig::ScalarA>::host_type, // AType
|
|
typename test::GemmTestbedTraits<
|
|
typename GemmTraits_::GemmConfig::ScalarB>::host_type, // BType
|
|
typename test::GemmTestbedTraits<
|
|
typename GemmTraits_::Epilogue::ScalarC>::host_type, // CType
|
|
typename test::GemmTestbedTraits<
|
|
typename GemmTraits_::Epilogue::Accumulators::Element>::host_type, // Accumulator
|
|
typename test::GemmTestbedTraits<typename GemmTraits_::Epilogue::Scalar>::host_type // Scalar
|
|
> GemmTestbed;
|
|
|
|
GemmTestbed testbed(m,
|
|
n,
|
|
k,
|
|
test::convert(GemmTraits_::kLayoutA),
|
|
test::convert(GemmTraits_::kLayoutB),
|
|
alpha,
|
|
beta);
|
|
|
|
testbed.initialize();
|
|
|
|
if (testbed.has_cublas_support()) {
|
|
EXPECT_TRUE(testbed.verify_host_with_cublas());
|
|
EXPECT_TRUE(testbed.verify_reference_with_cublas());
|
|
}
|
|
|
|
params.initialize(testbed.M(),
|
|
testbed.N(),
|
|
testbed.K(),
|
|
testbed.alpha,
|
|
testbed.ptr_A(),
|
|
testbed.lda(),
|
|
testbed.ptr_B(),
|
|
testbed.ldb(),
|
|
testbed.beta,
|
|
testbed.ptr_C_initial(),
|
|
testbed.ldc(),
|
|
testbed.ptr_computed(),
|
|
testbed.ldc());
|
|
|
|
Gemm::launch(params);
|
|
|
|
cudaError_t result = cudaDeviceSynchronize();
|
|
ASSERT_EQ(result, cudaSuccess) << "\nCUDA kernel launch error: " << cudaGetErrorString(result)
|
|
<< "\n";
|
|
|
|
if (testbed.has_cublas_support()) {
|
|
ASSERT_TRUE(testbed.verify_with_cublas());
|
|
} else {
|
|
ASSERT_TRUE(testbed.verify_with_host());
|
|
}
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////////////////////////////////////
|
|
|
|
template <typename GemmTraits_>
|
|
static void run_batched_strided_gemm(
|
|
int m,
|
|
int n,
|
|
int k,
|
|
int batch_count,
|
|
typename test::GemmTestbedTraits<typename GemmTraits_::Epilogue::Scalar>::host_type alpha =
|
|
typename test::GemmTestbedTraits<typename GemmTraits_::Epilogue::Scalar>::host_type(1.0f),
|
|
typename test::GemmTestbedTraits<typename GemmTraits_::Epilogue::Scalar>::host_type beta =
|
|
typename test::GemmTestbedTraits<typename GemmTraits_::Epilogue::Scalar>::host_type(0.0f)) {
|
|
//typedef cutlass::gemm::Gemm<GemmTraits_> Gemm;
|
|
typedef typename GemmTraits_::KernelClass Gemm;
|
|
typename Gemm::Params params;
|
|
test::GemmTestbed<
|
|
typename test::GemmTestbedTraits<
|
|
typename GemmTraits_::GemmConfig::ScalarA>::host_type, // AType
|
|
typename test::GemmTestbedTraits<
|
|
typename GemmTraits_::GemmConfig::ScalarB>::host_type, // BType
|
|
typename test::GemmTestbedTraits<
|
|
typename GemmTraits_::Epilogue::ScalarC>::host_type, // CType
|
|
typename test::GemmTestbedTraits<
|
|
typename GemmTraits_::Epilogue::Accumulators::Element>::host_type, // Accumulator
|
|
typename test::GemmTestbedTraits<typename GemmTraits_::Epilogue::Scalar>::host_type // Scalar
|
|
>
|
|
testbed(m,
|
|
n,
|
|
k,
|
|
batch_count,
|
|
test::convert(GemmTraits_::kLayoutA),
|
|
test::convert(GemmTraits_::kLayoutB),
|
|
alpha,
|
|
beta);
|
|
|
|
testbed.initialize();
|
|
|
|
// host support is not implemented for strided batched gemm
|
|
// if (testbed.has_cublas_support()) {
|
|
// EXPECT_TRUE(testbed.verify_host_with_cublas());
|
|
//}
|
|
|
|
params.initialize(testbed.M(),
|
|
testbed.N(),
|
|
testbed.K(),
|
|
testbed.alpha,
|
|
testbed.ptr_A(),
|
|
testbed.lda(),
|
|
testbed.get_batch_stride_A(),
|
|
testbed.ptr_B(),
|
|
testbed.ldb(),
|
|
testbed.get_batch_stride_B(),
|
|
testbed.beta,
|
|
testbed.ptr_C_initial(),
|
|
testbed.ldc(),
|
|
testbed.get_batch_stride_C(),
|
|
testbed.ptr_computed(),
|
|
testbed.ldc(),
|
|
testbed.get_batch_stride_C(),
|
|
testbed.get_batch_count());
|
|
|
|
Gemm::launch(params);
|
|
|
|
cudaError_t result = cudaDeviceSynchronize();
|
|
ASSERT_EQ(result, cudaSuccess) << "\nCUDA kernel launch error: " << cudaGetErrorString(result)
|
|
<< "\n";
|
|
|
|
if (testbed.has_cublas_support()) {
|
|
ASSERT_TRUE(testbed.verify_with_cublas());
|
|
} else {
|
|
// ASSERT_TRUE(testbed.verify_with_host());
|
|
ASSERT_TRUE(false) << "host support is not implemented for strided batched gemm" << std::endl;
|
|
}
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////////////////////////////////////
|
|
|
|
template <typename GemmTraits_, typename ReductionTraits_>
|
|
static void run_splitK_gemm(int m,
|
|
int n,
|
|
int k,
|
|
typename test::GemmTestbedTraits<typename ReductionTraits_::ScalarAlphaBeta>::host_type alpha =
|
|
typename test::GemmTestbedTraits<typename ReductionTraits_::ScalarAlphaBeta>::host_type(1.0f),
|
|
typename test::GemmTestbedTraits<typename ReductionTraits_::ScalarAlphaBeta>::host_type beta =
|
|
typename test::GemmTestbedTraits<typename ReductionTraits_::ScalarAlphaBeta>::host_type(0.0f),
|
|
bool use_host_reference = false){
|
|
|
|
test::GemmTestbed<
|
|
typename test::GemmTestbedTraits<
|
|
typename GemmTraits_::GemmConfig::ScalarA>::host_type, // AType
|
|
typename test::GemmTestbedTraits<
|
|
typename GemmTraits_::GemmConfig::ScalarB>::host_type, // BType
|
|
typename test::GemmTestbedTraits<
|
|
typename ReductionTraits_::ScalarC>::host_type, // CType
|
|
typename test::GemmTestbedTraits<
|
|
typename GemmTraits_::GemmConfig::ScalarD>::host_type, // Workspace Accumulator
|
|
typename test::GemmTestbedTraits<typename ReductionTraits_::ScalarAlphaBeta>::host_type // Scalar
|
|
>
|
|
testbed(m,
|
|
n,
|
|
k,
|
|
test::convert(GemmTraits_::kLayoutA),
|
|
test::convert(GemmTraits_::kLayoutB),
|
|
alpha,
|
|
beta);
|
|
|
|
testbed.initialize();
|
|
|
|
// create a device gemm
|
|
typedef cutlass::gemm::SplitkPIGemmTraits<GemmTraits_, ReductionTraits_> deviceGemmTraits;
|
|
typedef typename deviceGemmTraits::KernelClass deviceGemm;
|
|
typename deviceGemm::Params deviceGemmParams(testbed.M(), testbed.N(), testbed.K());
|
|
|
|
// query if workspace is needed
|
|
int workspace_size = deviceGemmParams.required_workspace_memory_in_byte();
|
|
typename test::GemmTestbedTraits<typename GemmTraits_::GemmConfig::ScalarD>::device_type
|
|
*workspace_ptr = 0;
|
|
if (workspace_size != 0) {
|
|
cudaError_t workspace_err = cudaMalloc(&workspace_ptr, workspace_size);
|
|
ASSERT_EQ(workspace_err, cudaSuccess) << "\nCUDA workspace malloc error: " << cudaGetErrorString(workspace_err)
|
|
<< "\n";
|
|
}
|
|
|
|
deviceGemmParams.initialize(testbed.alpha,
|
|
testbed.ptr_A(),
|
|
testbed.lda(),
|
|
testbed.ptr_B(),
|
|
testbed.ldb(),
|
|
testbed.beta,
|
|
testbed.ptr_C_initial(),
|
|
testbed.ldc(),
|
|
testbed.ptr_computed(),
|
|
testbed.ldc(),
|
|
workspace_ptr);
|
|
|
|
|
|
deviceGemm::launch(deviceGemmParams);
|
|
|
|
cudaError_t result = cudaDeviceSynchronize();
|
|
ASSERT_EQ(result, cudaSuccess) << "\nCUDA kernel launch error: " << cudaGetErrorString(result)
|
|
<< "\n";
|
|
|
|
if (workspace_size != 0) {
|
|
cudaError_t workspace_err = cudaFree(workspace_ptr);
|
|
ASSERT_EQ(workspace_err, cudaSuccess) << "\nCUDA workspace free error: " << cudaGetErrorString(workspace_err)
|
|
<< "\n";
|
|
}
|
|
|
|
if (use_host_reference == true || testbed.has_cublas_support() == false) {
|
|
ASSERT_TRUE(testbed.verify_with_host());
|
|
}
|
|
else {
|
|
ASSERT_TRUE(testbed.verify_with_cublas());
|
|
}
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////////////////////////////////////
|
|
|
|
template <typename GemmTraits_>
|
|
static void run_partitioned_k_gemm(
|
|
int m,
|
|
int n,
|
|
int k,
|
|
int partitionK_count,
|
|
typename test::GemmTestbedTraits<typename GemmTraits_::Epilogue::Scalar>::host_type alpha =
|
|
typename test::GemmTestbedTraits<typename GemmTraits_::Epilogue::Scalar>::host_type(1.0f),
|
|
typename test::GemmTestbedTraits<typename GemmTraits_::Epilogue::Scalar>::host_type beta =
|
|
typename test::GemmTestbedTraits<typename GemmTraits_::Epilogue::Scalar>::host_type(0.0f)) {
|
|
//typedef cutlass::gemm::Gemm<GemmTraits_> Gemm;
|
|
typedef typename GemmTraits_::KernelClass Gemm;
|
|
typename Gemm::Params params;
|
|
test::GemmTestbed<
|
|
typename test::GemmTestbedTraits<
|
|
typename GemmTraits_::GemmConfig::ScalarA>::host_type, // AType
|
|
typename test::GemmTestbedTraits<
|
|
typename GemmTraits_::GemmConfig::ScalarB>::host_type, // BType
|
|
typename test::GemmTestbedTraits<
|
|
typename GemmTraits_::Epilogue::ScalarC>::host_type, // CType
|
|
typename test::GemmTestbedTraits<
|
|
typename GemmTraits_::Epilogue::Accumulators::Element>::host_type, // Accumulator
|
|
typename test::GemmTestbedTraits<typename GemmTraits_::Epilogue::Scalar>::host_type // Scalar
|
|
>
|
|
testbed(m,
|
|
n,
|
|
std::make_pair(k, partitionK_count),
|
|
test::convert(GemmTraits_::kLayoutA),
|
|
test::convert(GemmTraits_::kLayoutB),
|
|
alpha,
|
|
beta);
|
|
|
|
testbed.initialize();
|
|
|
|
// host support is not implemented for strided batched gemm
|
|
// if (testbed.has_cublas_support()) {
|
|
// EXPECT_TRUE(testbed.verify_host_with_cublas());
|
|
//}
|
|
|
|
params.initialize(testbed.M(),
|
|
testbed.N(),
|
|
testbed.K(),
|
|
testbed.alpha,
|
|
testbed.ptr_A(),
|
|
testbed.lda(),
|
|
testbed.ptr_B(),
|
|
testbed.ldb(),
|
|
testbed.beta,
|
|
testbed.ptr_C_initial(),
|
|
testbed.ldc(),
|
|
testbed.ptr_computed(),
|
|
testbed.ldc(),
|
|
partitionK_count);
|
|
|
|
Gemm::launch(params);
|
|
|
|
cudaError_t result = cudaDeviceSynchronize();
|
|
ASSERT_EQ(result, cudaSuccess) << "\nCUDA kernel launch error: " << cudaGetErrorString(result)
|
|
<< "\n";
|
|
|
|
if (testbed.has_cublas_support()) {
|
|
ASSERT_TRUE(testbed.verify_with_cublas());
|
|
}
|
|
else {
|
|
// ASSERT_TRUE(testbed.verify_with_host());
|
|
ASSERT_TRUE(false) << "host support is not implemented for strided batched gemm" << std::endl;
|
|
}
|
|
}
|