cutlass/tools/test/unit/gemm/batched_strided_dgemm_128x128x8.cu
Andrew Kerr 877bdcace6
Cutlass 1.3 Release (#42)
CUTLASS 1.3 Release
- Efficient GEMM kernel targeting Volta Tensor Cores via mma.sync instruction added in CUDA 10.1.
2019-03-20 10:49:17 -07:00

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#include "cutlass_unit_test.h"
#include "cutlass/gemm/gemm.h"
#include "cutlass/gemm/dgemm_traits.h"
#include "tools/test/unit/gemm/gemm_testbed.h"
#include "tools/test/unit/gemm/run_gemm.h"
////////////////////////////////////////////////////////////////////////////////////////////////////
TEST(dgemm_strided_batched_128x128x8, dgemm_256x384x64x3_nn) {
typedef cutlass::gemm::DgemmTraits<cutlass::MatrixLayout::kColumnMajor,
cutlass::MatrixLayout::kColumnMajor, cutlass::Shape<8, 128, 128> >
DgemmTraits;
//think about using run_gemm directly
run_batched_strided_gemm<DgemmTraits>(256/*m*/, 384/*n*/, 64/*k*/, 3 /*batch_size*/);
}
////////////////////////////////////////////////////////////////////////////////////////////////////
TEST(dgemm_strided_batched_128x128x8, sgemm_128x384x192x2_nn) {
typedef cutlass::gemm::DgemmTraits<cutlass::MatrixLayout::kColumnMajor,
cutlass::MatrixLayout::kColumnMajor, cutlass::Shape<8, 128, 128> >
DgemmTraits;
//think about using run_gemm directly
run_batched_strided_gemm<DgemmTraits>(128/*m*/, 384/*n*/, 192/*k*/, 2 /*batch_size*/);
}
////////////////////////////////////////////////////////////////////////////////////////////////////
TEST(dgemm_strided_batched_128x128x8, dgemm_256x384x64x3_nt) {
typedef cutlass::gemm::DgemmTraits<cutlass::MatrixLayout::kColumnMajor,
cutlass::MatrixLayout::kRowMajor, cutlass::Shape<8, 128, 128> >
DgemmTraits;
//think about using run_gemm directly
run_batched_strided_gemm<DgemmTraits>(256/*m*/, 384/*n*/, 64/*k*/, 3 /*batch_size*/);
}
////////////////////////////////////////////////////////////////////////////////////////////////////
TEST(dgemm_strided_batched_128x128x8, sgemm_128x384x192x2_nt) {
typedef cutlass::gemm::DgemmTraits<cutlass::MatrixLayout::kColumnMajor,
cutlass::MatrixLayout::kRowMajor, cutlass::Shape<8, 128, 128> >
DgemmTraits;
//think about using run_gemm directly
run_batched_strided_gemm<DgemmTraits>(128/*m*/, 384/*n*/, 192/*k*/, 2 /*batch_size*/);
}
////////////////////////////////////////////////////////////////////////////////////////////////////
TEST(dgemm_strided_batched_128x128x8, dgemm_256x384x64x3_tn) {
typedef cutlass::gemm::DgemmTraits<cutlass::MatrixLayout::kRowMajor,
cutlass::MatrixLayout::kColumnMajor, cutlass::Shape<8, 128, 128> >
DgemmTraits;
//think about using run_gemm directly
run_batched_strided_gemm<DgemmTraits>(256/*m*/, 384/*n*/, 64/*k*/, 3 /*batch_size*/);
}
////////////////////////////////////////////////////////////////////////////////////////////////////
TEST(dgemm_strided_batched_128x128x8, sgemm_128x384x192x2_tn) {
typedef cutlass::gemm::DgemmTraits<cutlass::MatrixLayout::kRowMajor,
cutlass::MatrixLayout::kColumnMajor, cutlass::Shape<8, 128, 128> >
DgemmTraits;
//think about using run_gemm directly
run_batched_strided_gemm<DgemmTraits>(128/*m*/, 384/*n*/, 192/*k*/, 2 /*batch_size*/);
}
////////////////////////////////////////////////////////////////////////////////////////////////////
TEST(dgemm_strided_batched_128x128x8, dgemm_256x384x64x3_tt) {
typedef cutlass::gemm::DgemmTraits<cutlass::MatrixLayout::kRowMajor,
cutlass::MatrixLayout::kRowMajor, cutlass::Shape<8, 128, 128> >
DgemmTraits;
//think about using run_gemm directly
run_batched_strided_gemm<DgemmTraits>(256/*m*/, 384/*n*/, 64/*k*/, 3 /*batch_size*/);
}
////////////////////////////////////////////////////////////////////////////////////////////////////