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ad57f6ef0b
* Wrap ck host utitlies in CK namespace. The CK and CK-Tile source code bases are incompatible because CK is not properly using namespaces everywhere. In particular, we need to put hip_check_error in the ck namespace. Move all functions in include/ck_/host_utility that were in global namespace into the ck namespace. There may be additional namespace problems like this, and it's possible we'll have namespace clashes. But it is good design to properly guard our to code bases (CK and CKTile) so that they can both coexist. Moreover, estabilishing this compatiblity is essential if we are going to allow the builder to instantiate kernels from either template library. * Add using declarations to test code. After moving some of the untils into the ck namespace, most examples and a few tests had to be updated to recognize the new namespace declarations. We add using declarations to individual compute units for functions that were previously in the global namespace. * Add using declarations to client examples.
107 lines
4.4 KiB
C++
107 lines
4.4 KiB
C++
// SPDX-License-Identifier: MIT
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// Copyright (c) 2025, 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/tensor_layout.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_batched_gemm_multi_d_xdl.hpp"
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#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
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#include "ck/library/utility/check_err.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/reference_tensor_operation/cpu/reference_batched_gemm.hpp"
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#include "ck/library/utility/literals.hpp"
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using ::ck::DeviceMem;
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using ::ck::hip_check_error;
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using ::ck::HostTensorDescriptor;
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using ::ck::Tensor;
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template <ck::index_t... Is>
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using S = ck::Sequence<Is...>;
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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 PassThrough = ck::tensor_operation::element_wise::PassThrough;
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using ADataType = ck::int4_t;
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using BDataType = ck::int4_t;
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using AccDataType = int32_t;
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using CShuffleDataType = int32_t;
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using DsDataType = ck::Tuple<>;
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using EDataType = ck::int4_t;
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using KernelADataType = int8_t;
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using KernelBDataType = int8_t;
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using KernelEDataType = int8_t;
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using ALayout = Row;
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using BLayout = Col;
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using DsLayout = ck::Tuple<>;
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using ELayout = Row;
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using AElementOp = PassThrough;
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using BElementOp = PassThrough;
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using CDEElementOp = PassThrough;
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static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization::Default;
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using DeviceGemmInstance = ck::tensor_operation::device::DeviceBatchedGemmMultiD_Xdl
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// clang-format off
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< ALayout, //ALayout
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BLayout, //BLayout
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DsLayout, //DsLayout
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ELayout, //ELayout
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KernelADataType, //ADataType
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KernelBDataType, //BDataType
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AccDataType, //AccDataType
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CShuffleDataType, //CShuffleDataType
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DsDataType, //DsDataType
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KernelEDataType, //EDataType
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AElementOp, //AElementwiseOperation
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BElementOp, //BElementwiseOperation
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CDEElementOp, //CDEElementwiseOperation
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GemmDefault, //GEMMSpecialization
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1, // NumGemmKPrefetchStage
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256, // BlockSize
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256, // MPerBlock
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128, // NPerBlock
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64, // KPerBlock
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16, // AK1
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16, // BK1
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32, // MPerXdl
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32, // NPerXdl
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4, // MXdlPerWave
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2, // NXdlPerWave
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S<4, 64, 1>, // ABlockTransfer ThreadCluster Lengths_K0_M_K1
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S<1, 0, 2>, // ABlockTransfer ThreadCluster ArrangeOrder
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S<1, 0, 2>, // ABlockTransfer SrcAccessOrder
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2, // ABlockTransfer SrcVectorDim
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16, // ABlockTransfer SrcScalarPerVector
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16, // ABlockTransfer DstScalarPerVector_K1
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1, // ABlockLdsExtraM
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S<4, 64, 1>, // BBlockTransfer ThreadCluster Lengths_K0_N_K1
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S<1, 0, 2>, // BBlockTransfer ThreadCluster ArrangeOrder
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S<1, 0, 2>, // BBlockTransfer SrcAccessOrder
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2, // BBlockTransfer SrcVectorDim
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16, // BBlockTransfer SrcScalarPerVector
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16, // BBlockTransfer DstScalarPerVector_K1
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1, // BBlockLdsExtraN
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1, // CShuffleMXdlPerWavePerShuffle
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1, // CShuffleNXdlPerWavePerShuffle
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S<1, 64, 1, 4>, // CBlockTransferClusterLengths_MBlock_MWaveMPerXdl_NBlock_NWaveNPerXdl
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16>; // CBlockTransferScalarPerVector_NWaveNPerXdl
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// clang-format on
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#define BUILD_INT4_EXAMPLE
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#include "run_batched_gemm_example.inc"
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int main(int argc, char* argv[]) { return run_batched_gemm_example(argc, argv); }
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