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fixed rdna4 instances

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This commit is contained in:
Zoltan Lakatos
2025-06-23 12:23:58 +00:00
parent a8dec7a4da
commit 1c01ff60d4
7 changed files with 59 additions and 44 deletions
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8
library/src/tensor_operation_instance/gpu/gemm_multiply_multiply/device_gemm_multiply_multiply_wmma_c_shuffle_f8_f8_bf16_mk_nk_mn.cpp
View File

@@ -19,9 +19,9 @@ static constexpr auto GemmDefault = GemmSpecialization::Default;
static constexpr auto GemmMNKPadding = GemmSpecialization::MNKPadding;
static constexpr auto Intrawave = BlockGemmPipelineScheduler::Intrawave;
// static constexpr auto Interwave = BlockGemmPipelineScheduler::Interwave;
static constexpr auto Interwave = BlockGemmPipelineScheduler::Interwave;
// static constexpr auto V3 = BlockGemmPipelineVersion::v3;
static constexpr auto V3 = BlockGemmPipelineVersion::v3;
static constexpr auto V1 = BlockGemmPipelineVersion::v1;
template <GemmSpecialization GemmSpec>
@@ -32,7 +32,7 @@ using device_gemm_multiply_multiply_wmma_f8_f8_bf16_mk_nk_mn_instances =
//##################################| | | | | Type| Type| Type| Type| Type| DataType| Elementwise| Elementwise| Elementwise| | Size| Block| Block| Block| | | Wmma| Wmma| | | ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraN| MRepeat| NRepeat| ClusterLengths| ScalarPerVectors| PipeSched| PipelineVer| TypeA| TypeB|
//##################################| | | | | | | | | | | Operation| Operation| Operation| | | | | | | | | | | | Lengths_AK0_M_AK1| ArrangeOrder| | | PerVector| PerVector_AK1| | Lengths_BK0_N_BK1| ArrangeOrder| | | PerVector| PerVector_BK1| | PerShuffle| PerShuffle| _MBlock_MPerBlock| | | | | |
//##################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | _NBlock_NPerBlock| | | | | |
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, F8, F8, F32_F32_Tuple, BF16, F32, F32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 128, 128, 64, 64, 8, 8, 16, 16, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 32, 1, 4>, S<1, 1, 1>, Intrawave, V1, F8, F8>/*,
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, F8, F8, F32_F32_Tuple, BF16, F32, F32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 128, 128, 64, 64, 8, 8, 16, 16, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 32, 1, 4>, S<1, 1, 1>, Intrawave, V1, F8, F8>,
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, F8, F8, F32_F32_Tuple, BF16, F32, F32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 256, 128, 256, 64, 8, 8, 16, 16, 4, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<1, 1, 1>, Intrawave, V1, F8, F8>,
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, F8, F8, F32_F32_Tuple, BF16, F32, F32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 128, 64, 256, 64, 8, 8, 16, 16, 2, 8, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 4>, S<1, 1, 1>, Intrawave, V1, F8, F8>,
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, F8, F8, F32_F32_Tuple, BF16, F32, F32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 16, 1, 4>, S<1, 1, 1>, Intrawave, V1, F8, F8>,
@@ -42,7 +42,7 @@ using device_gemm_multiply_multiply_wmma_f8_f8_bf16_mk_nk_mn_instances =
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, F8, F8, F32_F32_Tuple, BF16, F32, F32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 16, 1, 4>, S<1, 1, 1>, Interwave, V1, F8, F8>,
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, F8, F8, F32_F32_Tuple, BF16, F32, F32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<1, 1, 1>, Intrawave, V3, F8, F8>,
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, F8, F8, F32_F32_Tuple, BF16, F32, F32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 256, 128, 128, 64, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<1, 1, 1>, Intrawave, V3, F8, F8>,
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, F8, F8, F32_F32_Tuple, BF16, F32, F32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 16, 1, 4>, S<1, 1, 1>, Intrawave, V3, F8, F8>*/
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, F8, F8, F32_F32_Tuple, BF16, F32, F32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 16, 1, 4>, S<1, 1, 1>, Intrawave, V3, F8, F8>
// clang-format on
>;

8
library/src/tensor_operation_instance/gpu/gemm_multiply_multiply/device_gemm_multiply_multiply_wmma_c_shuffle_f8_f8_f16_mk_nk_mn.cpp
View File

@@ -19,9 +19,9 @@ static constexpr auto GemmDefault = GemmSpecialization::Default;
static constexpr auto GemmMNKPadding = GemmSpecialization::MNKPadding;
static constexpr auto Intrawave = BlockGemmPipelineScheduler::Intrawave;
// static constexpr auto Interwave = BlockGemmPipelineScheduler::Interwave;
static constexpr auto Interwave = BlockGemmPipelineScheduler::Interwave;
// static constexpr auto V3 = BlockGemmPipelineVersion::v3;
static constexpr auto V3 = BlockGemmPipelineVersion::v3;
static constexpr auto V1 = BlockGemmPipelineVersion::v1;
template <GemmSpecialization GemmSpec>
@@ -32,7 +32,7 @@ using device_gemm_multiply_multiply_wmma_f8_f8_f16_mk_nk_mn_instances =
//##################################| | | | | Type| Type| Type| Type| Type| DataType| Elementwise| Elementwise| Elementwise| | Size| Block| Block| Block| | | Wmma| Wmma| | | ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraN| MRepeat| NRepeat| ClusterLengths| ScalarPerVectors| PipeSched| PipelineVer| TypeA| TypeB|
//##################################| | | | | | | | | | | Operation| Operation| Operation| | | | | | | | | | | | Lengths_AK0_M_AK1| ArrangeOrder| | | PerVector| PerVector_AK1| | Lengths_BK0_N_BK1| ArrangeOrder| | | PerVector| PerVector_BK1| | PerShuffle| PerShuffle| _MBlock_MPerBlock| | | | | |
//##################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | _NBlock_NPerBlock| | | | | |
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, F8, F8, F32_F32_Tuple, F16, F32, F32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 128, 128, 64, 64, 8, 8, 16, 16, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 32, 1, 4>, S<1, 1, 1>, Intrawave, V1, F8, F8>/*,
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, F8, F8, F32_F32_Tuple, F16, F32, F32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 128, 128, 64, 64, 8, 8, 16, 16, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 32, 1, 4>, S<1, 1, 1>, Intrawave, V1, F8, F8>,
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, F8, F8, F32_F32_Tuple, F16, F32, F32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 256, 128, 256, 64, 8, 8, 16, 16, 4, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<1, 1, 1>, Intrawave, V1, F8, F8>,
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, F8, F8, F32_F32_Tuple, F16, F32, F32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 128, 64, 256, 64, 8, 8, 16, 16, 2, 8, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 4>, S<1, 1, 1>, Intrawave, V1, F8, F8>,
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, F8, F8, F32_F32_Tuple, F16, F32, F32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 16, 1, 4>, S<1, 1, 1>, Intrawave, V1, F8, F8>,
@@ -42,7 +42,7 @@ using device_gemm_multiply_multiply_wmma_f8_f8_f16_mk_nk_mn_instances =
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, F8, F8, F32_F32_Tuple, F16, F32, F32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 16, 1, 4>, S<1, 1, 1>, Interwave, V1, F8, F8>,
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, F8, F8, F32_F32_Tuple, F16, F32, F32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<1, 1, 1>, Intrawave, V3, F8, F8>,
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, F8, F8, F32_F32_Tuple, F16, F32, F32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 256, 128, 128, 64, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<1, 1, 1>, Intrawave, V3, F8, F8>,
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, F8, F8, F32_F32_Tuple, F16, F32, F32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 16, 1, 4>, S<1, 1, 1>, Intrawave, V3, F8, F8>*/
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, F8, F8, F32_F32_Tuple, F16, F32, F32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 16, 1, 4>, S<1, 1, 1>, Intrawave, V3, F8, F8>
// clang-format on
>;

8
library/src/tensor_operation_instance/gpu/gemm_multiply_multiply/device_gemm_multiply_multiply_wmma_c_shuffle_i8_i8_bf16_mk_nk_mn.cpp
View File

@@ -19,9 +19,9 @@ static constexpr auto GemmDefault = GemmSpecialization::Default;
static constexpr auto GemmMNKPadding = GemmSpecialization::MNKPadding;
static constexpr auto Intrawave = BlockGemmPipelineScheduler::Intrawave;
// static constexpr auto Interwave = BlockGemmPipelineScheduler::Interwave;
static constexpr auto Interwave = BlockGemmPipelineScheduler::Interwave;
// static constexpr auto V3 = BlockGemmPipelineVersion::v3;
static constexpr auto V3 = BlockGemmPipelineVersion::v3;
static constexpr auto V1 = BlockGemmPipelineVersion::v1;
template <GemmSpecialization GemmSpec>
@@ -32,7 +32,7 @@ using device_gemm_multiply_multiply_wmma_i8_i8_bf16_mk_nk_mn_instances =
//##################################| | | | | Type| Type| Type| Type| Type| DataType| Elementwise| Elementwise| Elementwise| | Size| Block| Block| Block| | | Wmma| Wmma| | | ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraN| MRepeat| NRepeat| ClusterLengths| ScalarPerVectors| PipeSched| PipelineVer| TypeA| TypeB|
//##################################| | | | | | | | | | | Operation| Operation| Operation| | | | | | | | | | | | Lengths_AK0_M_AK1| ArrangeOrder| | | PerVector| PerVector_AK1| | Lengths_BK0_N_BK1| ArrangeOrder| | | PerVector| PerVector_BK1| | PerShuffle| PerShuffle| _MBlock_MPerBlock| | | | | |
//##################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | _NBlock_NPerBlock| | | | | |
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, I8, I8, F32_F32_Tuple, BF16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 128, 128, 64, 64, 8, 8, 16, 16, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 32, 1, 4>, S<1, 1, 1>, Intrawave, V1, I8, I8>/*,
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, I8, I8, F32_F32_Tuple, BF16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 128, 128, 64, 64, 8, 8, 16, 16, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 32, 1, 4>, S<1, 1, 1>, Intrawave, V1, I8, I8>,
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, I8, I8, F32_F32_Tuple, BF16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 256, 128, 256, 64, 8, 8, 16, 16, 4, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<1, 1, 1>, Intrawave, V1, I8, I8>,
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, I8, I8, F32_F32_Tuple, BF16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 128, 64, 256, 64, 8, 8, 16, 16, 2, 8, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 4>, S<1, 1, 1>, Intrawave, V1, I8, I8>,
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, I8, I8, F32_F32_Tuple, BF16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 16, 1, 4>, S<1, 1, 1>, Intrawave, V1, I8, I8>,
@@ -42,7 +42,7 @@ using device_gemm_multiply_multiply_wmma_i8_i8_bf16_mk_nk_mn_instances =
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, I8, I8, F32_F32_Tuple, BF16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 16, 1, 4>, S<1, 1, 1>, Interwave, V1, I8, I8>,
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, I8, I8, F32_F32_Tuple, BF16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<1, 1, 1>, Intrawave, V3, I8, I8>,
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, I8, I8, F32_F32_Tuple, BF16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 256, 128, 128, 64, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<1, 1, 1>, Intrawave, V3, I8, I8>,
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, I8, I8, F32_F32_Tuple, BF16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 16, 1, 4>, S<1, 1, 1>, Intrawave, V3, I8, I8>*/
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, I8, I8, F32_F32_Tuple, BF16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 16, 1, 4>, S<1, 1, 1>, Intrawave, V3, I8, I8>
// clang-format on
>;

8
library/src/tensor_operation_instance/gpu/gemm_multiply_multiply/device_gemm_multiply_multiply_wmma_c_shuffle_i8_i8_f16_mk_nk_mn.cpp
View File

@@ -19,9 +19,9 @@ static constexpr auto GemmDefault = GemmSpecialization::Default;
static constexpr auto GemmMNKPadding = GemmSpecialization::MNKPadding;
static constexpr auto Intrawave = BlockGemmPipelineScheduler::Intrawave;
//static constexpr auto Interwave = BlockGemmPipelineScheduler::Interwave;
static constexpr auto Interwave = BlockGemmPipelineScheduler::Interwave;
//static constexpr auto V3 = BlockGemmPipelineVersion::v3;
static constexpr auto V3 = BlockGemmPipelineVersion::v3;
static constexpr auto V1 = BlockGemmPipelineVersion::v1;
template <GemmSpecialization GemmSpec>
@@ -32,7 +32,7 @@ using device_gemm_multiply_multiply_wmma_i8_i8_f16_mk_nk_mn_instances =
//##################################| | | | | Type| Type| Type| Type| Type| DataType| Elementwise| Elementwise| Elementwise| | Size| Block| Block| Block| | | Wmma| Wmma| | | ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| ExtraN| MRepeat| NRepeat| ClusterLengths| ScalarPerVectors| PipeSched| PipelineVer| TypeA| TypeB|
//##################################| | | | | | | | | | | Operation| Operation| Operation| | | | | | | | | | | | Lengths_AK0_M_AK1| ArrangeOrder| | | PerVector| PerVector_AK1| | Lengths_BK0_N_BK1| ArrangeOrder| | | PerVector| PerVector_BK1| | PerShuffle| PerShuffle| _MBlock_MPerBlock| | | | | |
//##################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | _NBlock_NPerBlock| | | | | |
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, I8, I8, F16_F16_Tuple, F16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 128, 128, 64, 64, 8, 8, 16, 16, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 32, 1, 4>, S<1, 1, 1>, Intrawave, V1, I8, I8>/*,
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, I8, I8, F16_F16_Tuple, F16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 128, 128, 64, 64, 8, 8, 16, 16, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 32, 1, 4>, S<1, 1, 1>, Intrawave, V1, I8, I8>,
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, I8, I8, F16_F16_Tuple, F16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 256, 128, 256, 64, 8, 8, 16, 16, 4, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<1, 1, 1>, Intrawave, V1, I8, I8>,
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, I8, I8, F16_F16_Tuple, F16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 128, 64, 256, 64, 8, 8, 16, 16, 2, 8, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 4>, S<1, 1, 1>, Intrawave, V1, I8, I8>,
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, I8, I8, F16_F16_Tuple, F16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 16, 1, 4>, S<1, 1, 1>, Intrawave, V1, I8, I8>,
@@ -42,7 +42,7 @@ using device_gemm_multiply_multiply_wmma_i8_i8_f16_mk_nk_mn_instances =
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, I8, I8, F16_F16_Tuple, F16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 16, 1, 4>, S<1, 1, 1>, Interwave, V1, I8, I8>,
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, I8, I8, F16_F16_Tuple, F16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<1, 1, 1>, Intrawave, V3, I8, I8>,
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, I8, I8, F16_F16_Tuple, F16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 256, 128, 128, 64, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, S<1, 1, 1>, Intrawave, V3, I8, I8>,
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, I8, I8, F16_F16_Tuple, F16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 16, 1, 4>, S<1, 1, 1>, Intrawave, V3, I8, I8>*/
DeviceGemmMultipleD_Wmma_CShuffleV3< Row, Col, Row_Col_Tuple, Row, I8, I8, F16_F16_Tuple, F16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 64, 32, 64, 64, 8, 8, 16, 16, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, 1, 1, S<1, 16, 1, 4>, S<1, 1, 1>, Intrawave, V3, I8, I8>
// clang-format on
>;

2
test/CMakeLists.txt
View File

@@ -270,7 +270,7 @@ add_subdirectory(conv_tensor_rearrange)
add_subdirectory(transpose)
add_subdirectory(permute_scale)
add_subdirectory(wrapper)
if(SUPPORTED_GPU_TARGETS MATCHES "gfx11|gfx12")
if(SUPPORTED_GPU_TARGETS MATCHES "gfx11")
add_subdirectory(wmma_op)
endif()
if(SUPPORTED_GPU_TARGETS MATCHES "gfx942" OR SUPPORTED_GPU_TARGETS MATCHES "gfx950") # smfmac needs ROCm6.2

5
test/wmma_op/wmma_op.cpp
View File

@@ -13,8 +13,6 @@
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
#include "test/wmma_op/wmma_op_util.hpp"
#include <hip/hip_runtime.h>
template <typename SrcType,
typename DstType,
typename GPUAccType,
@@ -62,9 +60,6 @@ int main(int, char*[])
pass &= run_test<ck::half_t, ck::half_t, ck::half_t, ck::half_t, 16 >();
pass &= run_test<ck::bhalf_t, ck::bhalf_t, ck::bhalf_t, float, 16 >();
pass &= run_test<int8_t, int8_t, int32_t, int32_t, 8 >();
#if defined(CK_USE_WMMA_FP8)
pass &= run_test<ck::f8_t, ck::f8_t, float, float, 8 >();
#endif
// clang-format on
std::cout << "TestGemm ..... " << (pass ? "SUCCESS" : "FAILURE") << std::endl;

64
test/wmma_op/wmma_op_util.hpp
View File

@@ -130,7 +130,7 @@ __global__ void matmul(const src_t* a, const src_t* b, dst_t* c)
}
__syncthreads();
for(int ele = 0; ele < 8; ++ele)
{
p_shared[8 * 16 * lane_hi + 8 * lane_lo + ele] = a_temp[ele];
@@ -373,33 +373,53 @@ struct TestWmma
ck::wmma_op_util::RunHostGEMM<ReferenceGemmInstance>(
a, b, c_host, a_element_op, b_element_op, c_element_op);
// Unsupported types should be filtered out before calling test operator.
bool res = ck::wmma_op_util::RunDeviceGEMM(wmma_kernel, a, b, c_device);
// Act
bool is_supported = ck::is_gfx11_supported() &&
ck::wmma_op_util::RunDeviceGEMM(wmma_kernel, a, b, c_device);
if(std::is_same<CDataType, ck::bhalf_t>::value)
if(is_supported)
{
// 0.5 Pixel Error Tolerance is introduced by Accumulator difference.
// BF16 WMMA Accumulator is in BF16 Type while On Host-side Accumulator is Float.
res = ck::utils::check_err(
c_device.mData, c_host.mData, "Error: Incorrect results!", 0, 1.0);
std::cout << (res ? "SUCCESS" : "FAILURE") << std::endl;
}
else if(std::is_same<CDataType, float>::value ||
std::is_same<CDataType, ck::half_t>::value ||
std::is_same<CDataType, int8_t>::value ||
std::is_same<CDataType, double>::value ||
std::is_same<CDataType, f8_t>::value)
{
// Run with default error thresholds.
res = ck::utils::check_err(c_device.mData, c_host.mData);
std::cout << (res ? "SUCCESS" : "FAILURE") << std::endl;
// Assert
bool res = false;
if(std::is_same<CDataType, float>::value)
{
res = ck::utils::check_err(c_device.mData, c_host.mData);
std::cout << (res ? "SUCCESS" : "FAILURE") << std::endl;
}
else if(std::is_same<CDataType, ck::half_t>::value)
{
res = ck::utils::check_err(c_device.mData, c_host.mData);
std::cout << (res ? "SUCCESS" : "FAILURE") << std::endl;
}
else if(std::is_same<CDataType, ck::bhalf_t>::value)
{
// 0.5 Pixel Error Tolerance is introduced by Accumulator difference.
// BF16 WMMA Accumulator is in BF16 Type while On Host-side Accumulator is Float.
res = ck::utils::check_err(
c_device.mData, c_host.mData, "Error: Incorrect results!", 0, 1.0);
std::cout << (res ? "SUCCESS" : "FAILURE") << std::endl;
}
else if(std::is_same<CDataType, int8_t>::value)
{
res = ck::utils::check_err(c_device.mData, c_host.mData);
std::cout << (res ? "SUCCESS" : "FAILURE") << std::endl;
}
else if(std::is_same<CDataType, double>::value)
{
res = ck::utils::check_err(c_device.mData, c_host.mData);
std::cout << (res ? "SUCCESS" : "FAILURE") << std::endl;
}
else
{
std::cout << "UNSUPPORTED CDataType" << std::endl;
}
return res;
}
else
{
return false;
return true;
}
return res;
}
};