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https://github.com/ROCm/composable_kernel.git
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add int8 gemm multiply multiply a8w8 (#1591)
* add int8 gemm multiply multiply a8w8
* uncomment
* clang-format-12
* Add example_gemm_multiply_multiply_xdl_int8
* Remove shell scripts
* update preprocess number for mi308; bring back printout in ckprofiler
* format
---------
Co-authored-by: chenjun <junchen2@amd.com>
Co-authored-by: Haocong WANG <haocwang@amd.com>
Co-authored-by: carlushuang <carlus.huang@amd.com>
[ROCm/composable_kernel commit: 37f7afed1e]
This commit is contained in:
valarLip
@@ -1,3 +1,4 @@
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add_example_executable(example_gemm_multiply_multiply_xdl_fp8 gemm_multiply_multiply_xdl_fp8.cpp)
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add_example_executable(example_gemm_multiply_multiply_xdl_fp8_ab_scale gemm_multiply_multiply_xdl_fp8_ab_scale.cpp)
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add_example_executable(example_gemm_add_add_xdl_fp16 gemm_add_add_xdl_fp16.cpp)
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add_example_executable(example_gemm_multiply_multiply_xdl_int8 gemm_multiply_multiply_xdl_int8.cpp)
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@@ -0,0 +1,304 @@
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// SPDX-License-Identifier: MIT
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// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
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#include <iostream>
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#include <numeric>
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#include <initializer_list>
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#include <cstdlib>
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#include "ck/ck.hpp"
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#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
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#include "ck/tensor_operation/gpu/device/impl/device_gemm_multiple_d_xdl_cshuffle_v3.hpp"
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#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
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#include "ck/tensor_operation/gpu/element/unary_element_wise_operation.hpp"
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#include "ck/library/utility/device_memory.hpp"
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#include "ck/library/utility/host_tensor.hpp"
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#include "ck/library/utility/host_tensor_generator.hpp"
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#include "ck/library/utility/literals.hpp"
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#include "ck/library/reference_tensor_operation/cpu/reference_gemm.hpp"
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#include "ck/library/utility/check_err.hpp"
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#include "ck/utility/blkgemmpipe_scheduler.hpp"
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template <ck::index_t... Is>
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using S = ck::Sequence<Is...>;
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using I8 = int8_t;
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using I32 = int;
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using F16 = ck::half_t;
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using FP8 = ck::f8_t;
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using F32 = float;
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using Row = ck::tensor_layout::gemm::RowMajor;
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using Col = ck::tensor_layout::gemm::ColumnMajor;
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using A0DataType = I8;
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using B0DataType = I8;
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using AccDataType = I32;
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using CShuffleDataType = I32;
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using D0DataType = F32;
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using D1DataType = F32;
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using DsDataType = ck::Tuple<D0DataType, D1DataType>;
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using EDataType = F16;
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using A0Layout = Row;
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using B0Layout = Col;
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using D0Layout = Row;
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using D1Layout = Col;
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using DsLayout = ck::Tuple<D0Layout, D1Layout>;
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using ELayout = Row;
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struct MultiplyMultiply
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{
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template <typename E, typename C, typename D0, typename D1>
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__host__ __device__ constexpr void
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operator()(E& e, const C& c, const D0& d0, const D1& d1) const;
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template <>
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__host__ __device__ constexpr void operator()<ck::half_t, float, float, float>(
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ck::half_t& e, const float& c, const float& d0, const float& d1) const
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{
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const float x0_f = c * d0 * d1;
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e = ck::type_convert<ck::half_t>(x0_f);
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}
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template <>
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__host__ __device__ constexpr void operator()<ck::half_t, int, float, float>(
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ck::half_t& e, const int& c, const float& d0, const float& d1) const
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{
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const float x0_f =
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ck::type_convert<float>(c) * ck::type_convert<float>(d0) * ck::type_convert<float>(d1);
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e = ck::type_convert<ck::half_t>(x0_f);
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}
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template <>
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__host__ __device__ constexpr void operator()<ck::bhalf_t, int, float, float>(
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ck::bhalf_t& e, const int& c, const float& d0, const float& d1) const
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{
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const float x0_f =
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ck::type_convert<float>(c) * ck::type_convert<float>(d0) * ck::type_convert<float>(d1);
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e = ck::type_convert<ck::bhalf_t>(x0_f);
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}
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};
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using PassThrough = ck::tensor_operation::element_wise::PassThrough;
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using AElementOp = PassThrough;
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using BElementOp = PassThrough;
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using CDEElementOp = MultiplyMultiply;
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static constexpr auto GemmSpec = ck::tensor_operation::device::GemmSpecialization::MNPadding;
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using DeviceOpInstance = ck::tensor_operation::device::DeviceGemmMultiD_Xdl_CShuffle_V3
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// clang-format off
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///######| ALayout| BLayout| DsLayout| ELayout| AData| BData| DsData| EData| AccData| CShuffle| A| B| CDE| GEMM| Block| MPer| NPer| KPer| AK1| BK1| MPer| NPer| MXdl| NXdl| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CBlockTransferClusterLengths| CBlockTransfer|
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///######| | | | | Type| Type| Type| Type| Type| DataType| Elementwise| Elementwise| Elementwise| Spacialization| Size| Block| Block| Block| | | XDL| XDL| Per| Per| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave| _MBlock_MWaveMPerXdl| ScalarPerVector|
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///######| | | | | | | | | | | Operation| Operation| Operation| | | | | | | | | | Wave| Wave| Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | PerShuffle| PerShuffle| _NBlock_NWaveNPerXdl| _NWaveNPerXdl|
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///######| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | S<C, D0, D1>|
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///###### RRR
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///< Row, Row, DsLayout, ELayout, A0DataType, B0DataType, DsDataType, EDataType, AccDataType, CShuffleDataType, AElementOp, BElementOp, CDEElementOp, GemmSpec, 256, 256, 128, 64, 16, 4, 32, 32, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, S<16, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 8, 4, 0, 1, 1, S<1, 32, 1, 8>, S<8, 8, 1>, ck::BlockGemmPipelineScheduler::Interwave, ck::BlockGemmPipelineVersion::v1, I8>;
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///###### RCR
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< Row, Col, DsLayout, ELayout, A0DataType, B0DataType, DsDataType, EDataType, AccDataType, CShuffleDataType, AElementOp, BElementOp, CDEElementOp, GemmSpec, 256, 256, 128, 64, 16, 16, 32, 32, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, 1, 1, S<1, 32, 1, 8>, S<8, 8, 1>, ck::BlockGemmPipelineScheduler::Interwave, ck::BlockGemmPipelineVersion::v1, I8>;
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// clang-format on
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int main(int argc, char* argv[])
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{
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bool do_verification = true;
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int init_method = 1;
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bool time_kernel = false;
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// GEMM shape
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ck::index_t M = 3840;
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ck::index_t N = 4096;
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ck::index_t K = 4096;
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ck::index_t StrideA = K;
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ck::index_t StrideB = K;
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ck::index_t StrideD = 0;
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ck::index_t StrideE = N;
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ck::index_t KBatch = 1;
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if(argc == 1)
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{
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// use default case
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}
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else if(argc == 4)
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{
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do_verification = std::stoi(argv[1]);
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init_method = std::stoi(argv[2]);
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time_kernel = std::stoi(argv[3]);
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}
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else if(argc == 12)
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{
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do_verification = std::stoi(argv[1]);
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init_method = std::stoi(argv[2]);
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time_kernel = std::stoi(argv[3]);
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M = std::stoi(argv[4]);
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N = std::stoi(argv[5]);
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K = std::stoi(argv[6]);
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StrideA = std::stoi(argv[7]);
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StrideB = std::stoi(argv[8]);
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StrideD = std::stoi(argv[9]);
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StrideE = std::stoi(argv[10]);
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KBatch = std::stoi(argv[11]);
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}
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else
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{
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printf("arg1: verification (0=no, 1=yes)\n");
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printf("arg2: initialization (0=no init, 1=integer value, 2=decimal value)\n");
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printf("arg3: time kernel (0=no, 1=yes)\n");
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printf(
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"arg4 to 9: M (256x), N(128x), K(32x), StrideA, StrideB, StrideD, StrideE, KBatch\n");
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exit(0);
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}
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do_verification = false;
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auto f_host_tensor_descriptor =
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[](std::size_t row, std::size_t col, std::size_t stride, auto layout) {
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using namespace ck::literals;
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if(std::is_same<decltype(layout), ck::tensor_layout::gemm::RowMajor>::value)
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{
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return HostTensorDescriptor({row, col}, {stride, 1_uz});
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}
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else
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{
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return HostTensorDescriptor({row, col}, {1_uz, stride});
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}
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};
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Tensor<A0DataType> a0_m_k(f_host_tensor_descriptor(M, K, StrideA, A0Layout{}));
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Tensor<B0DataType> b0_k_n(f_host_tensor_descriptor(K, N, StrideB, B0Layout{}));
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Tensor<D0DataType> d0_m_n(f_host_tensor_descriptor(M, N, StrideD, D0Layout{}));
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Tensor<D1DataType> d1_m_n(f_host_tensor_descriptor(M, N, StrideD, D1Layout{}));
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Tensor<EDataType> e_m_n_host_result(f_host_tensor_descriptor(M, N, StrideE, ELayout{}));
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Tensor<EDataType> e_m_n_device_result(f_host_tensor_descriptor(M, N, StrideE, ELayout{}));
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std::cout << "a0_m_k: " << a0_m_k.mDesc << std::endl;
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std::cout << "b0_k_n: " << b0_k_n.mDesc << std::endl;
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std::cout << "d1_m_n: " << d1_m_n.mDesc << std::endl;
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std::cout << "d0_m_n: " << d0_m_n.mDesc << std::endl;
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std::cout << "e_m_n: " << e_m_n_host_result.mDesc << std::endl;
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switch(init_method)
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{
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case 0: break;
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case 1:
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a0_m_k.GenerateTensorValue(GeneratorTensor_2<A0DataType>{-2, 2});
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b0_k_n.GenerateTensorValue(GeneratorTensor_2<B0DataType>{0, 2});
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d0_m_n.GenerateTensorValue(GeneratorTensor_2<D0DataType>{0, 2});
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d1_m_n.GenerateTensorValue(GeneratorTensor_2<D1DataType>{0, 2});
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break;
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default:
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a0_m_k.GenerateTensorValue(GeneratorTensor_3<A0DataType>{0.0, 1.0});
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b0_k_n.GenerateTensorValue(GeneratorTensor_3<B0DataType>{-0.5, 0.5});
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d0_m_n.GenerateTensorValue(GeneratorTensor_3<D0DataType>{-0.5, 0.5});
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d1_m_n.GenerateTensorValue(GeneratorTensor_3<D1DataType>{-0.5, 0.5});
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}
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DeviceMem a0_device_buf(sizeof(A0DataType) * a0_m_k.mDesc.GetElementSpaceSize());
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DeviceMem b0_device_buf(sizeof(B0DataType) * b0_k_n.mDesc.GetElementSpaceSize());
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DeviceMem d0_device_buf(sizeof(D0DataType) * d0_m_n.mDesc.GetElementSpaceSize());
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DeviceMem d1_device_buf(sizeof(D1DataType) * d1_m_n.mDesc.GetElementSpaceSize());
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DeviceMem e_device_buf(sizeof(EDataType) * e_m_n_device_result.mDesc.GetElementSpaceSize());
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a0_device_buf.ToDevice(a0_m_k.mData.data());
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b0_device_buf.ToDevice(b0_k_n.mData.data());
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d0_device_buf.ToDevice(d0_m_n.mData.data());
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d1_device_buf.ToDevice(d1_m_n.mData.data());
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e_device_buf.ToDevice(e_m_n_device_result.mData.data());
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auto a_element_op = AElementOp{};
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auto b_element_op = BElementOp{};
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auto cde_element_op = CDEElementOp{};
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constexpr ck::index_t NumDTensor = DsDataType::Size();
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constexpr auto I0 = ck::Number<0>{};
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// do GEMM
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auto device_op = DeviceOpInstance{};
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auto invoker = device_op.MakeInvoker();
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auto argument =
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device_op.MakeArgument(a0_device_buf.GetDeviceBuffer(),
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b0_device_buf.GetDeviceBuffer(),
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std::array<const void*, NumDTensor>{d0_device_buf.GetDeviceBuffer(),
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d1_device_buf.GetDeviceBuffer()},
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e_device_buf.GetDeviceBuffer(),
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M,
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N,
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K,
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StrideA,
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StrideB,
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std::array<ck::index_t, NumDTensor>{I0, I0},
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StrideE,
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KBatch,
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a_element_op,
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b_element_op,
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cde_element_op);
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if(!device_op.IsSupportedArgument(argument))
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{
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throw std::runtime_error(
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"wrong! device_gemm with the specified compilation parameters does "
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"not support this GEMM problem");
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}
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float ave_time = invoker.Run(argument, StreamConfig{nullptr, time_kernel, 20, 50});
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std::size_t flop = std::size_t(2) * M * N * K;
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std::size_t num_btype =
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sizeof(A0DataType) * M * K + sizeof(B0DataType) * K * N + sizeof(EDataType) * M * N;
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float tflops = static_cast<float>(flop) / 1.E9 / ave_time;
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float gb_per_sec = num_btype / 1.E6 / ave_time;
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std::cout << "Perf: " << ave_time << " ms, " << tflops << " TFlops, " << gb_per_sec << " GB/s"
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<< std::endl;
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if(do_verification)
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{
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invoker.Run(argument, StreamConfig{nullptr, false});
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e_device_buf.FromDevice(e_m_n_device_result.mData.data());
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Tensor<CShuffleDataType> c_m_n({M, N});
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using ReferenceGemmInstance = ck::tensor_operation::host::ReferenceGemm<A0DataType,
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B0DataType,
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CShuffleDataType,
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AccDataType,
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PassThrough,
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PassThrough,
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PassThrough>;
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auto ref_gemm = ReferenceGemmInstance{};
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auto ref_invoker = ref_gemm.MakeInvoker();
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auto ref_argument = ref_gemm.MakeArgument(
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a0_m_k, b0_k_n, c_m_n, PassThrough{}, PassThrough{}, PassThrough{});
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ref_invoker.Run(ref_argument);
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for(int m = 0; m < M; ++m)
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{
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for(int n = 0; n < N; ++n)
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{
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cde_element_op(e_m_n_host_result(m, n), c_m_n(m, n), d0_m_n(m, n), d1_m_n(m, n));
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}
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}
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e_device_buf.FromDevice(e_m_n_device_result.mData.data());
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return ck::utils::check_err(e_m_n_device_result, e_m_n_host_result) ? 0 : 1;
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}
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return 0;
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}
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@@ -237,7 +237,7 @@ float launch_and_time_kernel_with_preprocess(const StreamConfig& stream_config,
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Args... args)
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{
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#if CK_TIME_KERNEL
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#define MEDIAN 1
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#define MEDIAN 0
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if(stream_config.time_kernel_)
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{
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if(ck::EnvIsEnabled(CK_ENV(CK_LOGGING)))
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@@ -275,6 +275,14 @@ float launch_and_time_kernel_with_preprocess(const StreamConfig& stream_config,
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#else
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float total_time = 0;
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#endif
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hipEvent_t start, stop;
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hip_check_error(hipEventCreate(&start));
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hip_check_error(hipEventCreate(&stop));
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hip_check_error(hipDeviceSynchronize());
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hip_check_error(hipEventRecord(start, stream_config.stream_id_));
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for(int i = 0; i < nrepeat; ++i)
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{
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if constexpr(!TimePreprocess)
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@@ -282,13 +290,13 @@ float launch_and_time_kernel_with_preprocess(const StreamConfig& stream_config,
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preprocess();
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}
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hipEvent_t start, stop;
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// hipEvent_t start, stop;
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hip_check_error(hipEventCreate(&start));
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hip_check_error(hipEventCreate(&stop));
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// hip_check_error(hipEventCreate(&start));
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// hip_check_error(hipEventCreate(&stop));
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hip_check_error(hipDeviceSynchronize());
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hip_check_error(hipEventRecord(start, stream_config.stream_id_));
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// hip_check_error(hipDeviceSynchronize());
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// hip_check_error(hipEventRecord(start, stream_config.stream_id_));
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// calculate preprocess time
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if constexpr(TimePreprocess)
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{
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@@ -299,25 +307,34 @@ float launch_and_time_kernel_with_preprocess(const StreamConfig& stream_config,
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hip_check_error(hipGetLastError());
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// end real kernel
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hip_check_error(hipEventRecord(stop, stream_config.stream_id_));
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hip_check_error(hipEventSynchronize(stop));
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float cur_time = 0;
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hip_check_error(hipEventElapsedTime(&cur_time, start, stop));
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#if MEDIAN
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times.insert(cur_time);
|
||||
#else
|
||||
total_time += cur_time;
|
||||
#endif
|
||||
// hip_check_error(hipEventRecord(stop, stream_config.stream_id_));
|
||||
// hip_check_error(hipEventSynchronize(stop));
|
||||
// float cur_time = 0;
|
||||
// hip_check_error(hipEventElapsedTime(&cur_time, start, stop));
|
||||
// #if MEDIAN
|
||||
// times.insert(cur_time);
|
||||
// #else
|
||||
// total_time += cur_time;
|
||||
// #endif
|
||||
|
||||
if(ck::EnvIsEnabled(CK_ENV(CK_LOGGING)))
|
||||
{
|
||||
std::cout << "i: " << i << " cur_time: " << cur_time << std::endl;
|
||||
// std::cout << "i: " << i << " cur_time: " << cur_time << std::endl;
|
||||
|
||||
printf("gemm_args.p_a_grid: %p, gemm_args.p_b_grid:%p\n",
|
||||
static_cast<const void*>(gemm_args.p_a_grid),
|
||||
static_cast<const void*>(gemm_args.p_b_grid));
|
||||
}
|
||||
}
|
||||
hip_check_error(hipEventRecord(stop, stream_config.stream_id_));
|
||||
hip_check_error(hipEventSynchronize(stop));
|
||||
float cur_time = 0;
|
||||
hip_check_error(hipEventElapsedTime(&cur_time, start, stop));
|
||||
#if MEDIAN
|
||||
times.insert(cur_time);
|
||||
#else
|
||||
total_time += cur_time;
|
||||
#endif
|
||||
|
||||
#if MEDIAN
|
||||
auto mid = times.begin();
|
||||
@@ -333,7 +350,11 @@ float launch_and_time_kernel_with_preprocess(const StreamConfig& stream_config,
|
||||
return (*mid + *mid_next) / 2;
|
||||
}
|
||||
#else
|
||||
return total_time / nrepeat;
|
||||
// return total_time / nrepeat;
|
||||
hipDeviceProp_t deviceProps;
|
||||
hip_check_error(hipGetDeviceProperties(&deviceProps, 0));
|
||||
float preprocess_offset = deviceProps.multiProcessorCount == 80 ? 0.005 : 0.01;
|
||||
return (total_time - preprocess_offset * nrepeat) / nrepeat;
|
||||
#endif
|
||||
}
|
||||
else
|
||||
|
||||
@@ -272,6 +272,26 @@ struct MultiplyMultiply
|
||||
|
||||
e = ck::type_convert<ck::bhalf_t>(x0_f);
|
||||
}
|
||||
|
||||
template <>
|
||||
__host__ __device__ constexpr void operator()<ck::half_t, int, ck::half_t, ck::half_t>(
|
||||
ck::half_t& e, const int& c, const ck::half_t& d0, const ck::half_t& d1) const
|
||||
{
|
||||
const float x0_f =
|
||||
ck::type_convert<float>(c) * ck::type_convert<float>(d0) * ck::type_convert<float>(d1);
|
||||
|
||||
e = ck::type_convert<ck::half_t>(x0_f);
|
||||
}
|
||||
|
||||
template <>
|
||||
__host__ __device__ constexpr void operator()<ck::bhalf_t, int, float, float>(
|
||||
ck::bhalf_t& e, const int& c, const float& d0, const float& d1) const
|
||||
{
|
||||
const float x0_f =
|
||||
ck::type_convert<float>(c) * ck::type_convert<float>(d0) * ck::type_convert<float>(d1);
|
||||
|
||||
e = ck::type_convert<ck::bhalf_t>(x0_f);
|
||||
}
|
||||
};
|
||||
|
||||
struct MultiplyAddFastGelu
|
||||
|
||||
@@ -327,12 +327,12 @@ struct intrin_mfma_i32_16x16x32i8<16, 16>
|
||||
__device__ static void Run(const int8x8_t& reg_a, const int8x8_t& reg_b, FloatC& reg_c)
|
||||
{
|
||||
reg_c.template AsType<int32x4_t>()(Number<0>{}) =
|
||||
__builtin_amdgcn_mfma_i32_16x16x32i8(bit_cast<int64_t>(reg_a),
|
||||
bit_cast<int64_t>(reg_b),
|
||||
reg_c.template AsType<int32x4_t>()[Number<0>{}],
|
||||
0,
|
||||
0,
|
||||
0);
|
||||
__builtin_amdgcn_mfma_i32_16x16x32_i8(bit_cast<int64_t>(reg_a),
|
||||
bit_cast<int64_t>(reg_b),
|
||||
reg_c.template AsType<int32x4_t>()[Number<0>{}],
|
||||
0,
|
||||
0,
|
||||
0);
|
||||
}
|
||||
};
|
||||
|
||||
|
||||
@@ -96,6 +96,87 @@ void add_device_gemm_multiply_multiply_xdl_f8_f8_bf16_mk_nk_mn_mem_v2_kpadding_i
|
||||
MultiplyMultiply>>>& instances);
|
||||
#endif
|
||||
|
||||
#if(defined(CK_ENABLE_BF16) || defined(CK_ENABLE_INT8))
|
||||
void add_device_gemm_multiply_multiply_xdl_i8_i8_bf16_mk_nk_mn_comp_default_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Col,
|
||||
Tuple<Row, Col>,
|
||||
Row,
|
||||
I8,
|
||||
I8,
|
||||
Tuple<F32, F32>,
|
||||
BF16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
MultiplyMultiply>>>& instances);
|
||||
|
||||
void add_device_gemm_multiply_multiply_xdl_i8_i8_bf16_mk_nk_mn_comp_kpadding_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Col,
|
||||
Tuple<Row, Col>,
|
||||
Row,
|
||||
I8,
|
||||
I8,
|
||||
Tuple<F32, F32>,
|
||||
BF16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
MultiplyMultiply>>>& instances);
|
||||
|
||||
void add_device_gemm_multiply_multiply_xdl_i8_i8_bf16_mk_nk_mn_mem_v1_default_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Col,
|
||||
Tuple<Row, Col>,
|
||||
Row,
|
||||
I8,
|
||||
I8,
|
||||
Tuple<F32, F32>,
|
||||
BF16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
MultiplyMultiply>>>& instances);
|
||||
|
||||
void add_device_gemm_multiply_multiply_xdl_i8_i8_bf16_mk_nk_mn_mem_v1_kpadding_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Col,
|
||||
Tuple<Row, Col>,
|
||||
Row,
|
||||
I8,
|
||||
I8,
|
||||
Tuple<F32, F32>,
|
||||
BF16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
MultiplyMultiply>>>& instances);
|
||||
|
||||
void add_device_gemm_multiply_multiply_xdl_i8_i8_bf16_mk_nk_mn_mem_v2_default_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Col,
|
||||
Tuple<Row, Col>,
|
||||
Row,
|
||||
I8,
|
||||
I8,
|
||||
Tuple<F32, F32>,
|
||||
BF16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
MultiplyMultiply>>>& instances);
|
||||
|
||||
void add_device_gemm_multiply_multiply_xdl_i8_i8_bf16_mk_nk_mn_mem_v2_kpadding_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Col,
|
||||
Tuple<Row, Col>,
|
||||
Row,
|
||||
I8,
|
||||
I8,
|
||||
Tuple<F32, F32>,
|
||||
BF16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
MultiplyMultiply>>>& instances);
|
||||
|
||||
#endif
|
||||
|
||||
template <typename ADataType,
|
||||
typename BDataType,
|
||||
typename CDataType,
|
||||
@@ -155,6 +236,30 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGemmMu
|
||||
op_ptrs);
|
||||
}
|
||||
}
|
||||
#endif
|
||||
#if(defined(CK_ENABLE_BF16) || defined(CK_ENABLE_INT8))
|
||||
if constexpr(is_same_v<ADataType, int8_t> && is_same_v<BDataType, int8_t> &&
|
||||
is_same_v<CDataType, bhalf_t>)
|
||||
{
|
||||
if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Col> &&
|
||||
is_same_v<CLayout, Row>)
|
||||
{
|
||||
add_device_gemm_multiply_multiply_xdl_i8_i8_bf16_mk_nk_mn_comp_default_instances(
|
||||
op_ptrs);
|
||||
add_device_gemm_multiply_multiply_xdl_i8_i8_bf16_mk_nk_mn_comp_kpadding_instances(
|
||||
op_ptrs);
|
||||
|
||||
add_device_gemm_multiply_multiply_xdl_i8_i8_bf16_mk_nk_mn_mem_v1_default_instances(
|
||||
op_ptrs);
|
||||
add_device_gemm_multiply_multiply_xdl_i8_i8_bf16_mk_nk_mn_mem_v1_kpadding_instances(
|
||||
op_ptrs);
|
||||
|
||||
add_device_gemm_multiply_multiply_xdl_i8_i8_bf16_mk_nk_mn_mem_v2_default_instances(
|
||||
op_ptrs);
|
||||
add_device_gemm_multiply_multiply_xdl_i8_i8_bf16_mk_nk_mn_mem_v2_kpadding_instances(
|
||||
op_ptrs);
|
||||
}
|
||||
}
|
||||
#endif
|
||||
return op_ptrs;
|
||||
}
|
||||
|
||||
@@ -8,9 +8,19 @@ list(APPEND GEMM_MULTIPLY_MULTIPLY_INSTANCES
|
||||
device_gemm_multiply_multiply_xdl_f8_f8_bf16/device_gemm_multiply_multiply_xdl_f8_f8_bf16_mk_nk_mn_mem_v1_kpadding_instance.cpp
|
||||
device_gemm_multiply_multiply_xdl_f8_f8_bf16/device_gemm_multiply_multiply_xdl_f8_f8_bf16_mk_nk_mn_mem_v2_default_instance.cpp
|
||||
device_gemm_multiply_multiply_xdl_f8_f8_bf16/device_gemm_multiply_multiply_xdl_f8_f8_bf16_mk_nk_mn_mem_v2_kpadding_instance.cpp
|
||||
|
||||
device_gemm_multiply_multiply_xdl_i8_i8_bf16/device_gemm_multiply_multiply_xdl_i8_i8_bf16_mk_nk_mn_comp_default_instance.cpp
|
||||
device_gemm_multiply_multiply_xdl_i8_i8_bf16/device_gemm_multiply_multiply_xdl_i8_i8_bf16_mk_nk_mn_comp_kpadding_instance.cpp
|
||||
device_gemm_multiply_multiply_xdl_i8_i8_bf16/device_gemm_multiply_multiply_xdl_i8_i8_bf16_mk_nk_mn_mem_v1_default_instance.cpp
|
||||
device_gemm_multiply_multiply_xdl_i8_i8_bf16/device_gemm_multiply_multiply_xdl_i8_i8_bf16_mk_nk_mn_mem_v1_kpadding_instance.cpp
|
||||
device_gemm_multiply_multiply_xdl_i8_i8_bf16/device_gemm_multiply_multiply_xdl_i8_i8_bf16_mk_nk_mn_mem_v2_default_instance.cpp
|
||||
device_gemm_multiply_multiply_xdl_i8_i8_bf16/device_gemm_multiply_multiply_xdl_i8_i8_bf16_mk_nk_mn_mem_v2_kpadding_instance.cpp
|
||||
)
|
||||
|
||||
set_source_files_properties(device_gemm_multiply_multiply_xdl_f8_f8_bf16/device_gemm_multiply_multiply_xdl_f8_f8_bf16_mk_nk_mn_comp_default_instance.cpp PROPERTIES COMPILE_OPTIONS ";-mllvm;-greedy-reverse-local-assignment=1")
|
||||
set_source_files_properties(device_gemm_multiply_multiply_xdl_f8_f8_bf16/device_gemm_multiply_multiply_xdl_f8_f8_bf16_mk_nk_mn_comp_kpadding_instance.cpp PROPERTIES COMPILE_OPTIONS ";-mllvm;-greedy-reverse-local-assignment=1")
|
||||
|
||||
set_source_files_properties(device_gemm_multiply_multiply_xdl_i8_i8_bf16/device_gemm_multiply_multiply_xdl_i8_i8_bf16_mk_nk_mn_comp_default_instance.cpp PROPERTIES COMPILE_OPTIONS ";-mllvm;-greedy-reverse-local-assignment=1")
|
||||
set_source_files_properties(device_gemm_multiply_multiply_xdl_i8_i8_bf16/device_gemm_multiply_multiply_xdl_i8_i8_bf16_mk_nk_mn_comp_kpadding_instance.cpp PROPERTIES COMPILE_OPTIONS ";-mllvm;-greedy-reverse-local-assignment=1")
|
||||
|
||||
add_instance_library(device_gemm_multiply_multiply_instance ${GEMM_MULTIPLY_MULTIPLY_INSTANCES})
|
||||
|
||||
@@ -0,0 +1,99 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include "ck/ck.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/impl/device_gemm_multiple_d_xdl_cshuffle_v3.hpp"
|
||||
|
||||
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
|
||||
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
namespace instance {
|
||||
|
||||
using I8 = int8_t;
|
||||
using I32 = int;
|
||||
using BF16 = bhalf_t;
|
||||
using F32 = float;
|
||||
|
||||
using Row = tensor_layout::gemm::RowMajor;
|
||||
using Col = tensor_layout::gemm::ColumnMajor;
|
||||
|
||||
template <index_t... Is>
|
||||
using S = Sequence<Is...>;
|
||||
|
||||
using PassThrough = element_wise::PassThrough;
|
||||
using MultiplyMultiply = element_wise::MultiplyMultiply;
|
||||
|
||||
static constexpr auto GemmDefault = GemmSpecialization::Default;
|
||||
static constexpr auto GemmKPadding = GemmSpecialization::KPadding;
|
||||
static constexpr auto GemmMNPadding = GemmSpecialization::MNPadding;
|
||||
static constexpr auto GemmMNKPadding = GemmSpecialization::MNKPadding;
|
||||
|
||||
static constexpr auto Intrawave = BlockGemmPipelineScheduler::Intrawave;
|
||||
static constexpr auto Interwave = BlockGemmPipelineScheduler::Interwave;
|
||||
|
||||
template <GemmSpecialization GemmSpec>
|
||||
using device_gemm_multiply_multiply_xdl_i8_i8_bf16_mk_nk_mn_comp_instances = std::tuple<
|
||||
// clang-format off
|
||||
//################################| ALayout| BLayout| DsLayout| ELayout|AData| BData| DsData| EData| AccData| Cshuffle| A| B| C| GEMM| Block| MPer| NPer| KPer| AK1| BK1|MPer| NPer| MXdl| NXdl| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CBlockTransferClusterLengths| CBlockTransfer| Block-wiseGemm| Block-wiseGemm|
|
||||
//################################| | | | | Type| Type| Type| Type| Type| Type| Elementwise| Elementwise| Elementwise|Specialization| Size| Block| Block| Block| | | XDL| XDL| Per| Per| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave| _MBlock_MXdlPerWave_MWaveMPerXdl| ScalarPerVector| Pipeline| Pipeline|
|
||||
//################################| | | | | | | | | | | Operation| Operation| Operation| | | | | | | | | | Wave| Wave| Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | PerShuffle| PerShuffle| _NBlock_NXdlPerWave_NWaveNPerXdl| _NWaveNPerXdl| Scheduler| Verision|
|
||||
//################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
|
||||
|
||||
// Compute friendly
|
||||
DeviceGemmMultiD_Xdl_CShuffle_V3< Row, Col, Tuple<Row, Col>, Row, I8, I8, Tuple<F32, F32>, BF16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 256, 256, 256, 64, 16, 16, 32, 32, 4, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, 1, 1, S<1, 32, 1, 8>, S<8, 8, 1>, BlockGemmPipelineScheduler::Intrawave, BlockGemmPipelineVersion::v4, I8>,
|
||||
DeviceGemmMultiD_Xdl_CShuffle_V3< Row, Col, Tuple<Row, Col>, Row, I8, I8, Tuple<F32, F32>, BF16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 256, 128, 128, 128, 16, 16, 32, 32, 2, 2, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, 1, 1, S<1, 32, 1, 8>, S<8, 8, 1>, BlockGemmPipelineScheduler::Intrawave, BlockGemmPipelineVersion::v4, I8>,
|
||||
DeviceGemmMultiD_Xdl_CShuffle_V3< Row, Col, Tuple<Row, Col>, Row, I8, I8, Tuple<F32, F32>, BF16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 256, 128, 128, 64, 16, 16, 32, 32, 2, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, 1, 1, S<1, 32, 1, 8>, S<8, 8, 1>, BlockGemmPipelineScheduler::Intrawave, BlockGemmPipelineVersion::v4, I8>,
|
||||
DeviceGemmMultiD_Xdl_CShuffle_V3< Row, Col, Tuple<Row, Col>, Row, I8, I8, Tuple<F32, F32>, BF16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 256, 256, 256, 128, 16, 16, 16, 16, 8, 8, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, 1, 2, S<1, 32, 1, 8>, S<8, 8, 1>, BlockGemmPipelineScheduler::Intrawave, BlockGemmPipelineVersion::v3, I8>,
|
||||
DeviceGemmMultiD_Xdl_CShuffle_V3< Row, Col, Tuple<Row, Col>, Row, I8, I8, Tuple<F32, F32>, BF16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 256, 256, 256, 64, 16, 16, 16, 16, 8, 8, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, 1, 2, S<1, 32, 1, 8>, S<8, 8, 1>, BlockGemmPipelineScheduler::Intrawave, BlockGemmPipelineVersion::v3, I8>,
|
||||
DeviceGemmMultiD_Xdl_CShuffle_V3< Row, Col, Tuple<Row, Col>, Row, I8, I8, Tuple<F32, F32>, BF16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 256, 224, 256, 128, 16, 16, 16, 16, 7, 8, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, 1, 2, S<1, 32, 1, 8>, S<8, 8, 1>, BlockGemmPipelineScheduler::Intrawave, BlockGemmPipelineVersion::v3, I8>,
|
||||
DeviceGemmMultiD_Xdl_CShuffle_V3< Row, Col, Tuple<Row, Col>, Row, I8, I8, Tuple<F32, F32>, BF16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 256, 256, 224, 128, 16, 16, 16, 16, 8, 7, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, 2, 1, S<1, 64, 1, 4>, S<8, 8, 1>, BlockGemmPipelineScheduler::Intrawave, BlockGemmPipelineVersion::v3, I8>,
|
||||
DeviceGemmMultiD_Xdl_CShuffle_V3< Row, Col, Tuple<Row, Col>, Row, I8, I8, Tuple<F32, F32>, BF16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 256, 128, 128, 128, 16, 16, 32, 32, 2, 2, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, 1, 1, S<1, 32, 1, 8>, S<8, 8, 1>, BlockGemmPipelineScheduler::Intrawave, BlockGemmPipelineVersion::v3, I8>,
|
||||
DeviceGemmMultiD_Xdl_CShuffle_V3< Row, Col, Tuple<Row, Col>, Row, I8, I8, Tuple<F32, F32>, BF16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 256, 128, 128, 128, 16, 16, 32, 32, 2, 2, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, 1, 1, S<1, 32, 1, 8>, S<8, 8, 1>, BlockGemmPipelineScheduler::Intrawave, BlockGemmPipelineVersion::v5, I8>,
|
||||
DeviceGemmMultiD_Xdl_CShuffle_V3< Row, Col, Tuple<Row, Col>, Row, I8, I8, Tuple<F32, F32>, BF16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 256, 128, 256, 64, 16, 16, 32, 32, 2, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, 1, 1, S<1, 32, 1, 8>, S<8, 8, 1>, BlockGemmPipelineScheduler::Interwave, BlockGemmPipelineVersion::v1, I8>,
|
||||
DeviceGemmMultiD_Xdl_CShuffle_V3< Row, Col, Tuple<Row, Col>, Row, I8, I8, Tuple<F32, F32>, BF16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 256, 256, 128, 64, 16, 16, 32, 32, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, 1, 1, S<1, 32, 1, 8>, S<8, 8, 1>, BlockGemmPipelineScheduler::Interwave, BlockGemmPipelineVersion::v1, I8>,
|
||||
DeviceGemmMultiD_Xdl_CShuffle_V3< Row, Col, Tuple<Row, Col>, Row, I8, I8, Tuple<F32, F32>, BF16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 256, 128, 128, 128, 16, 16, 32, 32, 2, 2, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, 1, 1, S<1, 32, 1, 8>, S<8, 8, 1>, BlockGemmPipelineScheduler::Interwave, BlockGemmPipelineVersion::v1, I8>,
|
||||
DeviceGemmMultiD_Xdl_CShuffle_V3< Row, Col, Tuple<Row, Col>, Row, I8, I8, Tuple<F32, F32>, BF16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 256, 128, 64, 128, 16, 16, 32, 32, 2, 1, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, 1, 1, S<1, 32, 1, 8>, S<8, 8, 1>, BlockGemmPipelineScheduler::Intrawave, BlockGemmPipelineVersion::v3, I8>,
|
||||
DeviceGemmMultiD_Xdl_CShuffle_V3< Row, Col, Tuple<Row, Col>, Row, I8, I8, Tuple<F32, F32>, BF16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 256, 64, 128, 128, 16, 16, 32, 32, 1, 2, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, 1, 1, S<1, 32, 1, 8>, S<8, 8, 1>, BlockGemmPipelineScheduler::Intrawave, BlockGemmPipelineVersion::v3, I8>,
|
||||
DeviceGemmMultiD_Xdl_CShuffle_V3< Row, Col, Tuple<Row, Col>, Row, I8, I8, Tuple<F32, F32>, BF16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 256, 64, 64, 128, 16, 16, 32, 32, 1, 1, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, 1, 1, S<1, 32, 1, 8>, S<8, 8, 1>, BlockGemmPipelineScheduler::Intrawave, BlockGemmPipelineVersion::v3, I8>
|
||||
// clang-format oI
|
||||
>;
|
||||
|
||||
template <BlockGemmPipelineScheduler BlkGemmPipeSched, GemmSpecialization GemmSpec>
|
||||
using device_gemm_multiply_multiply_xdl_i8_i8_bf16_mk_nk_mn_mem_instances = std::tuple<
|
||||
// clang-format off
|
||||
//################################| ALayout| BLayout| DsLayout| ELayout|AData| BData| DsData| EData| AccData| Cshuffle| A| B| C| GEMM| Block| MPer| NPer| KPer| AK1| BK1|MPer| NPer| MXdl| NXdl| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CBlockTransferClusterLengths| CBlockTransfer| Block-wiseGemm| Block-wiseGemm|
|
||||
//################################| | | | | Type| Type| Type| Type| Type| Type| Elementwise| Elementwise| Elementwise|Specialization| Size| Block| Block| Block| | | XDL| XDL| Per| Per| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave| _MBlock_MXdlPerWave_MWaveMPerXdl| ScalarPerVector| Pipeline| Pipeline|
|
||||
//################################| | | | | | | | | | | Operation| Operation| Operation| | | | | | | | | | Wave| Wave| Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | PerShuffle| PerShuffle| _NBlock_NXdlPerWave_NWaveNPerXdl| _NWaveNPerXdl| Scheduler| Verision|
|
||||
//################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
|
||||
|
||||
// Latency friendly
|
||||
DeviceGemmMultiD_Xdl_CShuffle_V3< Row, Col, Tuple<Row, Col>, Row, I8, I8, Tuple<F32, F32>, BF16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 128, 32, 16, 128, 16, 16, 16, 16, 1, 1, S<8, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, S<8, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, 1, 1, S<1, 16, 1, 8>, S<2, 2, 1>, BlkGemmPipeSched, BlockGemmPipelineVersion::v1, I8>,
|
||||
DeviceGemmMultiD_Xdl_CShuffle_V3< Row, Col, Tuple<Row, Col>, Row, I8, I8, Tuple<F32, F32>, BF16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 64, 16, 16, 128, 16, 16, 16, 16, 1, 1, S<8, 8, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, S<8, 8, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, 1, 1, S<1, 16, 1, 4>, S<4, 4, 1>, BlkGemmPipeSched, BlockGemmPipelineVersion::v1, I8>,
|
||||
DeviceGemmMultiD_Xdl_CShuffle_V3< Row, Col, Tuple<Row, Col>, Row, I8, I8, Tuple<F32, F32>, BF16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 128, 16, 32, 128, 16, 16, 16, 16, 1, 1, S<8, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, S<8, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, 1, 1, S<1, 16, 1, 8>, S<4, 4, 1>, BlkGemmPipeSched, BlockGemmPipelineVersion::v1, I8>,
|
||||
// Memory friendly
|
||||
DeviceGemmMultiD_Xdl_CShuffle_V3< Row, Col, Tuple<Row, Col>, Row, I8, I8, Tuple<F32, F32>, BF16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 256, 256, 32, 128, 16, 16, 32, 32, 2, 1, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, 1, 1, S<1, 32, 1, 8>, S<4, 4, 1>, BlkGemmPipeSched, BlockGemmPipelineVersion::v2, I8>,
|
||||
DeviceGemmMultiD_Xdl_CShuffle_V3< Row, Col, Tuple<Row, Col>, Row, I8, I8, Tuple<F32, F32>, BF16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 256, 256, 16, 128, 16, 16, 16, 16, 4, 1, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, S<8, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, 1, 1, S<1, 32, 1, 8>, S<2, 2, 1>, BlkGemmPipeSched, BlockGemmPipelineVersion::v2, I8>,
|
||||
DeviceGemmMultiD_Xdl_CShuffle_V3< Row, Col, Tuple<Row, Col>, Row, I8, I8, Tuple<F32, F32>, BF16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 128, 128, 32, 128, 16, 16, 32, 32, 2, 1, S<8, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, S<8, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, 1, 1, S<1, 16, 1, 8>, S<4, 4, 1>, BlkGemmPipeSched, BlockGemmPipelineVersion::v2, I8>,
|
||||
DeviceGemmMultiD_Xdl_CShuffle_V3< Row, Col, Tuple<Row, Col>, Row, I8, I8, Tuple<F32, F32>, BF16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 128, 128, 16, 128, 16, 16, 16, 16, 4, 1, S<8, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, S<8, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, 1, 1, S<1, 16, 1, 8>, S<2, 2, 1>, BlkGemmPipeSched, BlockGemmPipelineVersion::v2, I8>,
|
||||
DeviceGemmMultiD_Xdl_CShuffle_V3< Row, Col, Tuple<Row, Col>, Row, I8, I8, Tuple<F32, F32>, BF16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 128, 64, 32, 128, 16, 16, 32, 32, 1, 1, S<8, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, S<8, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, 1, 1, S<1, 16, 1, 8>, S<4, 4, 1>, BlkGemmPipeSched, BlockGemmPipelineVersion::v2, I8>,
|
||||
DeviceGemmMultiD_Xdl_CShuffle_V3< Row, Col, Tuple<Row, Col>, Row, I8, I8, Tuple<F32, F32>, BF16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 128, 64, 16, 128, 16, 16, 16, 16, 2, 1, S<8, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, S<8, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, 1, 1, S<1, 16, 1, 8>, S<2, 2, 1>, BlkGemmPipeSched, BlockGemmPipelineVersion::v2, I8>,
|
||||
DeviceGemmMultiD_Xdl_CShuffle_V3< Row, Col, Tuple<Row, Col>, Row, I8, I8, Tuple<F32, F32>, BF16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 128, 32, 16, 128, 16, 16, 16, 16, 1, 1, S<8, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, S<8, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, 1, 1, S<1, 16, 1, 8>, S<2, 2, 1>, BlkGemmPipeSched, BlockGemmPipelineVersion::v2, I8>,
|
||||
DeviceGemmMultiD_Xdl_CShuffle_V3< Row, Col, Tuple<Row, Col>, Row, I8, I8, Tuple<F32, F32>, BF16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 64, 16, 16, 64, 16, 16, 16, 16, 1, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, 1, 1, S<1, 16, 1, 4>, S<4, 4, 1>, BlkGemmPipeSched, BlockGemmPipelineVersion::v2, I8>,
|
||||
DeviceGemmMultiD_Xdl_CShuffle_V3< Row, Col, Tuple<Row, Col>, Row, I8, I8, Tuple<F32, F32>, BF16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 64, 16, 16, 128, 16, 16, 16, 16, 1, 1, S<8, 8, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, S<8, 8, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, 1, 1, S<1, 16, 1, 4>, S<4, 4, 1>, BlkGemmPipeSched, BlockGemmPipelineVersion::v2, I8>,
|
||||
DeviceGemmMultiD_Xdl_CShuffle_V3< Row, Col, Tuple<Row, Col>, Row, I8, I8, Tuple<F32, F32>, BF16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 128, 16, 32, 128, 16, 16, 16, 16, 1, 1, S<8, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, S<8, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, 1, 1, S<1, 16, 1, 8>, S<4, 4, 1>, BlkGemmPipeSched, BlockGemmPipelineVersion::v2, I8>,
|
||||
DeviceGemmMultiD_Xdl_CShuffle_V3< Row, Col, Tuple<Row, Col>, Row, I8, I8, Tuple<F32, F32>, BF16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 128, 16, 64, 128, 16, 16, 16, 16, 1, 2, S<8, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, S<8, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, 1, 1, S<1, 16, 1, 8>, S<4, 4, 1>, BlkGemmPipeSched, BlockGemmPipelineVersion::v2, I8>,
|
||||
DeviceGemmMultiD_Xdl_CShuffle_V3< Row, Col, Tuple<Row, Col>, Row, I8, I8, Tuple<F32, F32>, BF16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 128, 32, 64, 128, 16, 16, 32, 32, 1, 1, S<8, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, S<8, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, 1, 1, S<1, 16, 1, 8>, S<8, 8, 1>, BlkGemmPipeSched, BlockGemmPipelineVersion::v2, I8>,
|
||||
DeviceGemmMultiD_Xdl_CShuffle_V3< Row, Col, Tuple<Row, Col>, Row, I8, I8, Tuple<F32, F32>, BF16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 128, 16, 128, 128, 16, 16, 16, 16, 1, 4, S<8, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, S<8, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, 1, 1, S<1, 16, 1, 8>, S<4, 4, 1>, BlkGemmPipeSched, BlockGemmPipelineVersion::v2, I8>,
|
||||
DeviceGemmMultiD_Xdl_CShuffle_V3< Row, Col, Tuple<Row, Col>, Row, I8, I8, Tuple<F32, F32>, BF16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 128, 32, 128, 128, 16, 16, 32, 32, 1, 2, S<8, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, S<8, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, 1, 1, S<1, 16, 1, 8>, S<8, 8, 1>, BlkGemmPipeSched, BlockGemmPipelineVersion::v2, I8>,
|
||||
DeviceGemmMultiD_Xdl_CShuffle_V3< Row, Col, Tuple<Row, Col>, Row, I8, I8, Tuple<F32, F32>, BF16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 256, 16, 256, 128, 16, 16, 16, 16, 1, 4, S<8, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, S<8, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, 1, 1, S<1, 16, 1, 16>, S<4, 4, 1>, BlkGemmPipeSched, BlockGemmPipelineVersion::v2, I8>,
|
||||
DeviceGemmMultiD_Xdl_CShuffle_V3< Row, Col, Tuple<Row, Col>, Row, I8, I8, Tuple<F32, F32>, BF16, I32, I32, PassThrough, PassThrough, MultiplyMultiply, GemmSpec, 256, 32, 256, 128, 16, 16, 32, 32, 1, 2, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, 1, 1, S<1, 16, 1, 16>, S<8, 8, 1>, BlkGemmPipeSched, BlockGemmPipelineVersion::v2, I8>
|
||||
// clang-format oI
|
||||
>;
|
||||
} // namespace instance
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
@@ -0,0 +1,32 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include "device_gemm_multiply_multiply_xdl_i8_i8_bf16_mk_nk_mn.hpp"
|
||||
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
namespace instance {
|
||||
|
||||
void add_device_gemm_multiply_multiply_xdl_i8_i8_bf16_mk_nk_mn_comp_default_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Col,
|
||||
Tuple<Row, Col>,
|
||||
Row,
|
||||
I8,
|
||||
I8,
|
||||
Tuple<F32, F32>,
|
||||
BF16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
MultiplyMultiply>>>& instances)
|
||||
{
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_multiply_multiply_xdl_i8_i8_bf16_mk_nk_mn_comp_instances<GemmDefault>{});
|
||||
}
|
||||
|
||||
} // namespace instance
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
@@ -0,0 +1,32 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include "device_gemm_multiply_multiply_xdl_i8_i8_bf16_mk_nk_mn.hpp"
|
||||
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
namespace instance {
|
||||
|
||||
void add_device_gemm_multiply_multiply_xdl_i8_i8_bf16_mk_nk_mn_comp_kpadding_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Col,
|
||||
Tuple<Row, Col>,
|
||||
Row,
|
||||
I8,
|
||||
I8,
|
||||
Tuple<F32, F32>,
|
||||
BF16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
MultiplyMultiply>>>& instances)
|
||||
{
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_multiply_multiply_xdl_i8_i8_bf16_mk_nk_mn_comp_instances<GemmKPadding>{});
|
||||
}
|
||||
|
||||
} // namespace instance
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
@@ -0,0 +1,33 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include "device_gemm_multiply_multiply_xdl_i8_i8_bf16_mk_nk_mn.hpp"
|
||||
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
namespace instance {
|
||||
|
||||
void add_device_gemm_multiply_multiply_xdl_i8_i8_bf16_mk_nk_mn_mem_v1_default_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Col,
|
||||
Tuple<Row, Col>,
|
||||
Row,
|
||||
I8,
|
||||
I8,
|
||||
Tuple<F32, F32>,
|
||||
BF16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
MultiplyMultiply>>>& instances)
|
||||
{
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_multiply_multiply_xdl_i8_i8_bf16_mk_nk_mn_mem_instances<Intrawave,
|
||||
GemmDefault>{});
|
||||
}
|
||||
|
||||
} // namespace instance
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
@@ -0,0 +1,33 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include "device_gemm_multiply_multiply_xdl_i8_i8_bf16_mk_nk_mn.hpp"
|
||||
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
namespace instance {
|
||||
|
||||
void add_device_gemm_multiply_multiply_xdl_i8_i8_bf16_mk_nk_mn_mem_v1_kpadding_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Col,
|
||||
Tuple<Row, Col>,
|
||||
Row,
|
||||
I8,
|
||||
I8,
|
||||
Tuple<F32, F32>,
|
||||
BF16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
MultiplyMultiply>>>& instances)
|
||||
{
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_multiply_multiply_xdl_i8_i8_bf16_mk_nk_mn_mem_instances<Intrawave,
|
||||
GemmKPadding>{});
|
||||
}
|
||||
|
||||
} // namespace instance
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
@@ -0,0 +1,33 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include "device_gemm_multiply_multiply_xdl_i8_i8_bf16_mk_nk_mn.hpp"
|
||||
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
namespace instance {
|
||||
|
||||
void add_device_gemm_multiply_multiply_xdl_i8_i8_bf16_mk_nk_mn_mem_v2_default_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Col,
|
||||
Tuple<Row, Col>,
|
||||
Row,
|
||||
I8,
|
||||
I8,
|
||||
Tuple<F32, F32>,
|
||||
BF16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
MultiplyMultiply>>>& instances)
|
||||
{
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_multiply_multiply_xdl_i8_i8_bf16_mk_nk_mn_mem_instances<Interwave,
|
||||
GemmDefault>{});
|
||||
}
|
||||
|
||||
} // namespace instance
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
@@ -0,0 +1,33 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include "device_gemm_multiply_multiply_xdl_i8_i8_bf16_mk_nk_mn.hpp"
|
||||
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
namespace instance {
|
||||
|
||||
void add_device_gemm_multiply_multiply_xdl_i8_i8_bf16_mk_nk_mn_mem_v2_kpadding_instances(
|
||||
std::vector<std::unique_ptr<DeviceGemmMultipleDSplitK<Row,
|
||||
Col,
|
||||
Tuple<Row, Col>,
|
||||
Row,
|
||||
I8,
|
||||
I8,
|
||||
Tuple<F32, F32>,
|
||||
BF16,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
MultiplyMultiply>>>& instances)
|
||||
{
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_gemm_multiply_multiply_xdl_i8_i8_bf16_mk_nk_mn_mem_instances<Interwave,
|
||||
GemmKPadding>{});
|
||||
}
|
||||
|
||||
} // namespace instance
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
@@ -271,10 +271,12 @@ bool profile_gemm_multiply_multiply_impl(int do_verification,
|
||||
<< " TFlops, " << gb_per_sec << " GB/s, " << op_name << ", KBatch "
|
||||
<< kbatch_curr << std::endl;
|
||||
|
||||
#if defined CK_ENABLE_FP8
|
||||
#if defined CK_ENABLE_FP8 || defined CK_ENABLE_INT8
|
||||
// set softer tolerances for fp8
|
||||
if constexpr(is_same_v<ADataType, f8_t> || is_same_v<BDataType, f8_t> ||
|
||||
is_same_v<EDataType, f8_t>)
|
||||
if constexpr((is_same_v<ADataType, f8_t> || is_same_v<BDataType, f8_t> ||
|
||||
is_same_v<EDataType, f8_t>) ||
|
||||
(is_same_v<ADataType, int8_t> || is_same_v<BDataType, int8_t> ||
|
||||
is_same_v<EDataType, int8_t>))
|
||||
{
|
||||
std::string msg = "Error: Incorrect results!";
|
||||
double rtol = 1e-1;
|
||||
@@ -286,7 +288,7 @@ bool profile_gemm_multiply_multiply_impl(int do_verification,
|
||||
{
|
||||
#endif
|
||||
pass = pass & ck::utils::check_err(e_m_n_device_result, e_m_n_host_result);
|
||||
#if defined CK_ENABLE_FP8
|
||||
#if defined CK_ENABLE_FP8 || defined CK_ENABLE_INT8
|
||||
}
|
||||
#endif
|
||||
|
||||
|
||||
@@ -27,6 +27,7 @@ enum struct GemmDataType
|
||||
F16_F8_F16, // 5
|
||||
F16_F16_F16_F8, // 6
|
||||
F8_F8_BF16, // 7
|
||||
INT8_INT8_BF16, // 8
|
||||
};
|
||||
|
||||
#define OP_NAME "gemm_multiply_multiply"
|
||||
@@ -39,7 +40,7 @@ int profile_gemm_multiply_multiply(int argc, char* argv[])
|
||||
printf("arg1: tensor operation (" OP_NAME ": " OP_DESC ")\n");
|
||||
printf("arg2: data type (0: fp32; 1: fp16; 2: bf16; 3: int8; 4: f8@f16; 5: f16@f8; 6: "
|
||||
"f16->f8; 7: f8->bf16, "
|
||||
"comp f8)\n");
|
||||
"comp f8; 8: int8->bf16)\n");
|
||||
printf("arg3: matrix layout (0: A[m, k] * B[k, n] = C[m, n];\n");
|
||||
printf(" 1: A[m, k] * B[n, k] = C[m, n];\n");
|
||||
printf(" 2: A[k, m] * B[k, n] = C[m, n];\n");
|
||||
@@ -89,6 +90,8 @@ int profile_gemm_multiply_multiply(int argc, char* argv[])
|
||||
using F32 = float;
|
||||
using BF16 = ck::bhalf_t;
|
||||
using F8 = ck::f8_t;
|
||||
using I8 = int8_t;
|
||||
using I32 = int;
|
||||
|
||||
using Row = ck::tensor_layout::gemm::RowMajor;
|
||||
using Col = ck::tensor_layout::gemm::ColumnMajor;
|
||||
@@ -162,6 +165,11 @@ int profile_gemm_multiply_multiply(int argc, char* argv[])
|
||||
return profile(
|
||||
F8{}, F8{}, F8{}, F32{}, F32{}, F32{}, BF16{}, Row{}, Col{}, Row{}, Col{}, Row{});
|
||||
}
|
||||
else if(data_type == GemmDataType::INT8_INT8_BF16 && layout == GemmMatrixLayout::MK_NK_MN)
|
||||
{
|
||||
return profile(
|
||||
I8{}, I8{}, I8{}, I32{}, F32{}, F32{}, BF16{}, Row{}, Col{}, Row{}, Col{}, Row{});
|
||||
}
|
||||
else
|
||||
{
|
||||
std::cout << "this data_type & layout is not implemented" << std::endl;
|
||||
|
||||
Reference in New Issue
Block a user