mirror of
https://github.com/ROCm/composable_kernel.git
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[CK_TILE] Row/Col quant gemm (#2729)
* Add cshuffle epilogue test * add the poc implementation to the epilogue and tests * refactor cshuffle epilogue * WIP: adding tensor/tile usage to scale_tile * fix usage of tile_elementwise_inout * add gemm_quant_kernel for generalizing gemm quant kernel * Add problem specific to different quants, add QuantType to Traits * Add quant_type to quant_kernel template parameters * Create aq/bq_block_windows and views depending on QuantType * Use tile windows as inputs in cshuffle epilogue * Fix some issues in epilogue * initial new example code for new general gemm quant kernel test * Fix issues in kernel * Add verification check for rowcol Quantmode * use AccDataType instead of AQ in pipeline * fix aquant preshuffle * fix formatting * some cleanup * remove gemm_aquant_basic.cpp * remove gemm_aquant_kernel.hpp * fix tests for the renamed quant kernel * fix formatting * clean example files * fix some merge conflicts * fix preshufflequant rename issue * fix some templates after merging with develop * fix test preshuffle parameter * fix formatting * Unify bquant kernel to the common quant kernel * remove bquant kernel also from common header * fix formatting * clean up commented code * fix formatting config hpp * fix merge mistake * Non-const for movable windows * fix formatting * Fix grammar in README Co-authored-by: spolifroni-amd <Sandra.Polifroni@amd.com> * Remove #include<bit> and clean up example * fix strides * Add some descriptions for move_windows --------- Co-authored-by: Mohsen Saffari <mohsen.saffari@amd.com> Co-authored-by: spolifroni-amd <Sandra.Polifroni@amd.com>
This commit is contained in:
Sami Remes
@@ -1,679 +0,0 @@
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// SPDX-License-Identifier: MIT
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// Copyright (c) 2025, Advanced Micro Devices, Inc. All rights reserved.
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#pragma once
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#include <iostream>
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#include <string>
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#include "ck_tile/core.hpp"
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#include "ck_tile/ops/common.hpp"
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#include "ck_tile/host/concat.hpp"
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namespace ck_tile {
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struct BQuantGemmProblem
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{
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CK_TILE_HOST BQuantGemmProblem() = default;
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CK_TILE_HOST BQuantGemmProblem(index_t M_,
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index_t N_,
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index_t K_,
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index_t QK_,
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index_t stride_A_,
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index_t stride_B_,
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index_t stride_C_,
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index_t stride_BQ_)
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: M(M_),
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N(N_),
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K(K_),
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QK(QK_),
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stride_A(stride_A_),
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stride_B(stride_B_),
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stride_C(stride_C_),
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stride_BQ(stride_BQ_)
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{
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}
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index_t M;
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index_t N;
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index_t K;
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index_t QK;
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index_t stride_A;
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index_t stride_B;
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index_t stride_C;
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index_t stride_BQ;
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};
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struct BQuantGemmHostArgs : public BQuantGemmProblem
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{
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CK_TILE_HOST BQuantGemmHostArgs() = default;
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CK_TILE_HOST BQuantGemmHostArgs(const void* a_ptr_,
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const void* b_ptr_,
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void* c_ptr_,
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const void* bq_ptr_,
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index_t k_batch_,
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index_t M_,
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index_t N_,
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index_t K_,
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index_t QK_,
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index_t stride_A_,
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index_t stride_B_,
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index_t stride_C_,
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index_t stride_BQ_)
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: BQuantGemmProblem(M_, N_, K_, QK_, stride_A_, stride_B_, stride_C_, stride_BQ_),
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a_ptr(a_ptr_),
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b_ptr(b_ptr_),
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bq_ptr(bq_ptr_),
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c_ptr(c_ptr_),
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k_batch(k_batch_)
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{
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}
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const void* a_ptr;
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const void* b_ptr;
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const void* bq_ptr;
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void* c_ptr;
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index_t k_batch;
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};
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struct BQuantGemmKernelArgs
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{
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const void* a_ptr;
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const void* b_ptr;
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const void* bq_ptr;
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void* c_ptr;
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index_t M;
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index_t N;
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index_t K;
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index_t QK;
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index_t stride_A;
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index_t stride_B;
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index_t stride_C;
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index_t stride_BQ;
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index_t k_batch;
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};
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template <typename TilePartitioner_, typename GemmPipeline_, typename EpiloguePipeline_>
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struct BQuantGemmKernel
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{
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using TilePartitioner = remove_cvref_t<TilePartitioner_>;
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using GemmPipeline = remove_cvref_t<GemmPipeline_>;
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using EpiloguePipeline = remove_cvref_t<EpiloguePipeline_>;
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using ALayout = remove_cvref_t<typename GemmPipeline::ALayout>;
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using BLayout = remove_cvref_t<typename GemmPipeline::BLayout>;
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using BQLayout = remove_cvref_t<typename GemmPipeline::BQLayout>;
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using CLayout = remove_cvref_t<typename GemmPipeline::CLayout>;
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static constexpr index_t kBlockSize = GemmPipeline::BlockSize;
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using ADataType = remove_cvref_t<typename GemmPipeline::ADataType>;
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using BDataType = remove_cvref_t<typename GemmPipeline::BDataType>;
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using BQDataType = remove_cvref_t<typename GemmPipeline::BQDataType>;
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using CDataType = remove_cvref_t<typename EpiloguePipeline::ODataType>;
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static constexpr auto I0 = number<0>();
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static constexpr auto I1 = number<1>();
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static constexpr auto I2 = number<2>();
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static constexpr auto I3 = number<3>();
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[[nodiscard]] CK_TILE_HOST static const std::string GetName()
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{
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// clang-format off
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return concat('_', "gemm", gemm_prec_str<ADataType, BDataType>, GemmPipeline::GetName());
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// clang-format on
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}
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CK_TILE_HOST static constexpr auto GridSize(index_t M, index_t N, index_t KBatch)
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{
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return dim3(TilePartitioner::GridSize(M, N), 1, KBatch);
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}
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CK_TILE_HOST static constexpr auto BlockSize() { return dim3(kBlockSize); }
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CK_TILE_HOST static constexpr BQuantGemmKernelArgs
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MakeKernelArgs(const BQuantGemmHostArgs& hostArgs)
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{
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return BQuantGemmKernelArgs{hostArgs.a_ptr,
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hostArgs.b_ptr,
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hostArgs.bq_ptr,
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hostArgs.c_ptr,
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hostArgs.M,
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hostArgs.N,
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hostArgs.K,
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hostArgs.QK,
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hostArgs.stride_A,
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hostArgs.stride_B,
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hostArgs.stride_C,
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hostArgs.stride_BQ,
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hostArgs.k_batch};
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}
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CK_TILE_HOST_DEVICE static constexpr index_t GetSmemSize()
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{
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return max(GemmPipeline::GetSmemSize(), EpiloguePipeline::GetSmemSize());
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}
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struct SplitKBatchOffset
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{
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__device__ SplitKBatchOffset(const BQuantGemmKernelArgs& kargs,
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const std::size_t k_id = blockIdx.z)
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{
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constexpr auto K1 = TilePartitioner::BlockGemmShape::WarpTile::at(number<2>{});
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const index_t K_t = __builtin_amdgcn_readfirstlane(kargs.k_batch * K1);
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const index_t KRead = __builtin_amdgcn_readfirstlane((kargs.K + K_t - 1) / K_t * K1);
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if constexpr(std::is_same_v<tensor_layout::gemm::RowMajor, ALayout>)
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{
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a_k_split_offset = __builtin_amdgcn_readfirstlane(k_id * KRead);
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}
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else if constexpr(std::is_same_v<tensor_layout::gemm::ColumnMajor, ALayout>)
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{
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a_k_split_offset = __builtin_amdgcn_readfirstlane(k_id * KRead * kargs.stride_A);
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}
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if constexpr(std::is_same_v<tensor_layout::gemm::RowMajor, BLayout>)
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{
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b_k_split_offset = __builtin_amdgcn_readfirstlane(k_id * KRead * kargs.stride_B);
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}
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else if constexpr(std::is_same_v<tensor_layout::gemm::ColumnMajor, BLayout>)
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{
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b_k_split_offset = __builtin_amdgcn_readfirstlane(k_id * KRead);
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}
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if(k_id < static_cast<uint32_t>(kargs.k_batch - 1))
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{
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splitted_k = __builtin_amdgcn_readfirstlane(KRead);
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}
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else
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{
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splitted_k = __builtin_amdgcn_readfirstlane(kargs.K - KRead * (kargs.k_batch - 1));
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}
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}
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index_t a_k_split_offset;
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index_t b_k_split_offset;
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index_t splitted_k;
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};
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CK_TILE_HOST static bool IsSupportedArgument(const BQuantGemmKernelArgs& kargs)
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{
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if(kargs.k_batch != 1)
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{
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if(ck_tile::EnvIsEnabled(CK_TILE_ENV(CK_TILE_LOGGING)))
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{
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CK_TILE_ERROR("Conditions not met for Kbatch >1 !");
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}
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return false;
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}
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static_assert(std::is_same_v<BQLayout, tensor_layout::gemm::ColumnMajor>);
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if(kargs.QK % GemmPipeline::GetVectorSizeBQ() != 0)
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{
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if(ck_tile::EnvIsEnabled(CK_TILE_ENV(CK_TILE_LOGGING)))
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{
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CK_TILE_ERROR("K is not a multiple of vector load size for A tensor!");
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}
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return false;
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}
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if constexpr(std::is_same_v<ALayout, tensor_layout::gemm::RowMajor>)
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{
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if(kargs.K % (TilePartitioner::KPerBlock * kargs.k_batch) != 0 &&
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GemmPipeline::kPadK == false)
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{
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if(ck_tile::EnvIsEnabled(CK_TILE_ENV(CK_TILE_LOGGING)))
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{
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CK_TILE_ERROR("Can't support K that is not a multiple of k_batch * KPerBlock "
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"without padding!");
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}
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return false;
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}
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if(kargs.K % GemmPipeline::GetVectorSizeA() != 0)
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{
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if(ck_tile::EnvIsEnabled(CK_TILE_ENV(CK_TILE_LOGGING)))
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{
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CK_TILE_ERROR("K is not a multiple of vector load size for A tensor!");
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}
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return false;
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}
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}
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else
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{
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if(kargs.M % TilePartitioner::MPerBlock != 0 && GemmPipeline::kPadM == false)
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{
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if(ck_tile::EnvIsEnabled(CK_TILE_ENV(CK_TILE_LOGGING)))
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{
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CK_TILE_ERROR(
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"Can't support M that is not a multiple of MPerBlock without padding!");
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}
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return false;
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}
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if(kargs.M % GemmPipeline::GetVectorSizeA() != 0)
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{
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if(ck_tile::EnvIsEnabled(CK_TILE_ENV(CK_TILE_LOGGING)))
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{
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CK_TILE_ERROR("M is not a multiple of vector load size for A tensor!");
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}
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return false;
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}
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}
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if constexpr(std::is_same_v<BLayout, tensor_layout::gemm::RowMajor>)
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{
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if(kargs.N % TilePartitioner::NPerBlock != 0 && GemmPipeline::kPadN == false)
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{
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if(ck_tile::EnvIsEnabled(CK_TILE_ENV(CK_TILE_LOGGING)))
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{
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CK_TILE_ERROR(
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"Can't support N that is not a multiple of NPerBlock without padding!");
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}
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return false;
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}
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if(kargs.N % GemmPipeline::GetVectorSizeB() != 0)
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{
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if(ck_tile::EnvIsEnabled(CK_TILE_ENV(CK_TILE_LOGGING)))
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{
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CK_TILE_ERROR("N is not a multiple of vector load size for B tensor!");
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}
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return false;
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}
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}
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else
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{
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if(kargs.K % (TilePartitioner::KPerBlock * kargs.k_batch) != 0 &&
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GemmPipeline::kPadK == false)
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{
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if(ck_tile::EnvIsEnabled(CK_TILE_ENV(CK_TILE_LOGGING)))
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{
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CK_TILE_ERROR("Can't support K that is not a multiple of k_batch * KPerBlock "
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"without padding!");
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}
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return false;
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}
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if(kargs.K % GemmPipeline::GetVectorSizeB() != 0)
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{
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if(ck_tile::EnvIsEnabled(CK_TILE_ENV(CK_TILE_LOGGING)))
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{
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CK_TILE_ERROR("K is not a multiple of vector load size for B tensor!");
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}
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return false;
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}
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}
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if constexpr(std::is_same_v<CLayout, tensor_layout::gemm::RowMajor>)
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{
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if(kargs.N % TilePartitioner::NPerBlock != 0 && GemmPipeline::kPadN == false)
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{
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if(ck_tile::EnvIsEnabled(CK_TILE_ENV(CK_TILE_LOGGING)))
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{
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CK_TILE_ERROR(
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"Can't support N that is not a multiple of NPerBlock without padding!");
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}
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return false;
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}
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if(kargs.N % EpiloguePipeline::GetVectorSizeC() != 0)
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{
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if(ck_tile::EnvIsEnabled(CK_TILE_ENV(CK_TILE_LOGGING)))
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{
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CK_TILE_ERROR("N is not a multiple of vector load size for C tensor!");
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}
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return false;
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}
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}
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else
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{
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if(kargs.M % TilePartitioner::MPerBlock != 0 && GemmPipeline::kPadM == false)
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{
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if(ck_tile::EnvIsEnabled(CK_TILE_ENV(CK_TILE_LOGGING)))
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{
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CK_TILE_ERROR(
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"Can't support M that is not a multiple of MPerBlock without padding!");
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}
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return false;
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}
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if(kargs.M % EpiloguePipeline::GetVectorSizeC() != 0)
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{
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if(ck_tile::EnvIsEnabled(CK_TILE_ENV(CK_TILE_LOGGING)))
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{
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CK_TILE_ERROR("M is not a multiple of vector load size for C tensor!");
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}
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return false;
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}
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}
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return true;
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}
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template <memory_operation_enum DstInMemOp = memory_operation_enum::set>
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CK_TILE_DEVICE static auto MakeGemmTensorViews(const ADataType* a_ptr,
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const BDataType* b_ptr,
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const BQDataType* bq_ptr,
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CDataType* c_ptr,
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const BQuantGemmKernelArgs& kargs,
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const SplitKBatchOffset& splitk_batch_offset)
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{
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static_assert(!TilePartitioner::BlockGemmShape::PermuteA, "Not implemented!");
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const auto& a_tensor_view = [&]() {
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if constexpr(std::is_same_v<ALayout, tensor_layout::gemm::RowMajor>)
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{
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return make_naive_tensor_view<address_space_enum::global>(
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a_ptr,
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make_tuple(kargs.M, splitk_batch_offset.splitted_k),
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make_tuple(kargs.stride_A, 1),
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number<GemmPipeline::GetVectorSizeA()>{},
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number<1>{});
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}
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else
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{
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return make_naive_tensor_view<address_space_enum::global>(
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a_ptr,
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make_tuple(splitk_batch_offset.splitted_k, kargs.M),
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make_tuple(kargs.stride_A, 1),
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number<GemmPipeline::GetVectorSizeA()>{},
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number<1>{});
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}
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}();
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const auto& bq_tensor_view = [&]() {
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static_assert(std::is_same_v<BQLayout, tensor_layout::gemm::ColumnMajor>);
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return make_naive_tensor_view<address_space_enum::global>(
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bq_ptr,
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make_tuple(kargs.N, kargs.QK),
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make_tuple(kargs.stride_BQ, 1),
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number<GemmPipeline::GetVectorSizeBQ()>{},
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number<1>{});
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}();
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const auto& b_tensor_view = [&]() {
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if constexpr(std::is_same_v<BLayout, tensor_layout::gemm::RowMajor>)
|
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{
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if constexpr(TilePartitioner::BlockGemmShape::PermuteB)
|
||||
{
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constexpr index_t K1 = GemmPipeline::GetSmemPackB();
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const index_t K0 = splitk_batch_offset.splitted_k / K1;
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constexpr index_t VectorSizeB = std::min(K1, GemmPipeline::GetVectorSizeB());
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const auto b_k0_n_k1_desc =
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make_naive_tensor_descriptor(make_tuple(K0, kargs.N, K1),
|
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make_tuple(kargs.N * K1, K1, I1),
|
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number<VectorSizeB>{},
|
||||
number<1>{});
|
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const auto b_n_k_desc = transform_tensor_descriptor(
|
||||
b_k0_n_k1_desc,
|
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make_tuple(make_merge_transform(make_tuple(K0, K1)),
|
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make_pass_through_transform(kargs.N)),
|
||||
make_tuple(sequence<0, 2>{}, sequence<1>{}),
|
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make_tuple(sequence<0>{}, sequence<1>{}));
|
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return make_tensor_view<address_space_enum::global>(b_ptr, b_n_k_desc);
|
||||
}
|
||||
else
|
||||
{
|
||||
return make_naive_tensor_view<address_space_enum::global>(
|
||||
b_ptr,
|
||||
make_tuple(splitk_batch_offset.splitted_k, kargs.N),
|
||||
make_tuple(kargs.stride_B, 1),
|
||||
number<GemmPipeline::GetVectorSizeB()>{},
|
||||
number<1>{});
|
||||
}
|
||||
}
|
||||
else
|
||||
{
|
||||
if constexpr(TilePartitioner::BlockGemmShape::PermuteB)
|
||||
{
|
||||
constexpr index_t K1 = GemmPipeline::GetSmemPackB();
|
||||
const index_t K0 = splitk_batch_offset.splitted_k / K1;
|
||||
constexpr index_t VectorSizeB = std::min(K1, GemmPipeline::GetVectorSizeB());
|
||||
const auto b_k0_n_k1_desc =
|
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make_naive_tensor_descriptor(make_tuple(K0, kargs.N, K1),
|
||||
make_tuple(kargs.N * K1, K1, I1),
|
||||
number<VectorSizeB>{},
|
||||
number<1>{});
|
||||
const auto b_n_k_desc = transform_tensor_descriptor(
|
||||
b_k0_n_k1_desc,
|
||||
make_tuple(make_merge_transform(make_tuple(K0, K1)),
|
||||
make_pass_through_transform(kargs.N)),
|
||||
make_tuple(sequence<0, 2>{}, sequence<1>{}),
|
||||
make_tuple(sequence<1>{}, sequence<0>{}));
|
||||
return make_tensor_view<address_space_enum::global>(b_ptr, b_n_k_desc);
|
||||
}
|
||||
else
|
||||
{
|
||||
return make_naive_tensor_view<address_space_enum::global>(
|
||||
b_ptr,
|
||||
make_tuple(kargs.N, splitk_batch_offset.splitted_k),
|
||||
make_tuple(kargs.stride_B, 1),
|
||||
number<GemmPipeline::GetVectorSizeB()>{},
|
||||
number<1>{});
|
||||
}
|
||||
}
|
||||
}();
|
||||
|
||||
// TODO: enable vector write for C in ColMajor
|
||||
const auto& c_tensor_view = [&]() {
|
||||
if constexpr(std::is_same_v<CLayout, tensor_layout::gemm::RowMajor>)
|
||||
{
|
||||
return make_naive_tensor_view<address_space_enum::global, DstInMemOp>(
|
||||
c_ptr,
|
||||
make_tuple(kargs.M, kargs.N),
|
||||
make_tuple(kargs.stride_C, 1),
|
||||
number<EpiloguePipeline::GetVectorSizeC()>{},
|
||||
number<1>{});
|
||||
}
|
||||
else
|
||||
{
|
||||
return make_naive_tensor_view<address_space_enum::global, DstInMemOp>(
|
||||
c_ptr,
|
||||
make_tuple(kargs.M, kargs.N),
|
||||
make_tuple(1, kargs.stride_C),
|
||||
number<1>{},
|
||||
number<1>{});
|
||||
}
|
||||
}();
|
||||
|
||||
return make_tuple(a_tensor_view, bq_tensor_view, b_tensor_view, c_tensor_view);
|
||||
}
|
||||
|
||||
template <typename TensorView>
|
||||
CK_TILE_DEVICE static auto MakeGemmPadViews(const TensorView& views)
|
||||
{
|
||||
const auto& a_pad_view = [&]() {
|
||||
const auto& a_tensor_view = views.at(I0);
|
||||
if constexpr(std::is_same_v<ALayout, tensor_layout::gemm::RowMajor>)
|
||||
{
|
||||
return pad_tensor_view(a_tensor_view,
|
||||
make_tuple(number<TilePartitioner::MPerBlock>{},
|
||||
number<TilePartitioner::KPerBlock>{}),
|
||||
sequence<false, GemmPipeline::kPadK>{});
|
||||
}
|
||||
else
|
||||
{
|
||||
return pad_tensor_view(a_tensor_view,
|
||||
make_tuple(number<TilePartitioner::KPerBlock>{},
|
||||
number<TilePartitioner::MPerBlock>{}),
|
||||
sequence<false, GemmPipeline::kPadM>{});
|
||||
}
|
||||
}();
|
||||
|
||||
const auto& bq_pad_view = [&]() {
|
||||
const auto& bq_tensor_view = views.at(I1);
|
||||
static_assert(std::is_same_v<BQLayout, tensor_layout::gemm::ColumnMajor>);
|
||||
return pad_tensor_view(
|
||||
bq_tensor_view,
|
||||
make_tuple(number<TilePartitioner::NPerBlock>{},
|
||||
number<TilePartitioner::KPerBlock / GemmPipeline::QuantGroupSize>{}),
|
||||
// TODO: Add support for padding.
|
||||
sequence<false, false>{});
|
||||
}();
|
||||
|
||||
const auto& b_pad_view = [&]() {
|
||||
const auto& b_tensor_view = views.at(I2);
|
||||
if constexpr(std::is_same_v<BLayout, tensor_layout::gemm::ColumnMajor>)
|
||||
{
|
||||
return pad_tensor_view(b_tensor_view,
|
||||
make_tuple(number<TilePartitioner::NPerBlock>{},
|
||||
number<TilePartitioner::KPerBlock>{}),
|
||||
sequence<false, GemmPipeline::kPadK>{});
|
||||
}
|
||||
else
|
||||
{
|
||||
return pad_tensor_view(b_tensor_view,
|
||||
make_tuple(number<TilePartitioner::KPerBlock>{},
|
||||
number<TilePartitioner::NPerBlock>{}),
|
||||
sequence<false, GemmPipeline::kPadN>{});
|
||||
}
|
||||
}();
|
||||
|
||||
// TODO vector write in for C in ColMajor
|
||||
const auto& c_pad_view = [&]() {
|
||||
const auto& c_tensor_view = views.at(I3);
|
||||
if constexpr(std::is_same_v<CLayout, tensor_layout::gemm::RowMajor>)
|
||||
{
|
||||
return pad_tensor_view(c_tensor_view,
|
||||
make_tuple(number<TilePartitioner::MPerBlock>{},
|
||||
number<TilePartitioner::NPerBlock>{}),
|
||||
sequence<false, GemmPipeline::kPadN>{});
|
||||
}
|
||||
else
|
||||
{
|
||||
return pad_tensor_view(c_tensor_view,
|
||||
make_tuple(number<TilePartitioner::MPerBlock>{},
|
||||
number<TilePartitioner::NPerBlock>{}),
|
||||
sequence<GemmPipeline::kPadM, false>{});
|
||||
}
|
||||
}();
|
||||
|
||||
return make_tuple(a_pad_view, bq_pad_view, b_pad_view, c_pad_view);
|
||||
}
|
||||
|
||||
template <typename PadView>
|
||||
CK_TILE_DEVICE static auto
|
||||
MakeGemmTileWindows(const PadView& views, const index_t i_m, const index_t i_n)
|
||||
{
|
||||
const auto& a_pad_view = views.at(I0);
|
||||
const auto& bq_pad_view = views.at(I1);
|
||||
const auto& b_pad_view = views.at(I2);
|
||||
const auto& c_pad_view = views.at(I3);
|
||||
|
||||
const auto& a_block_window = [&]() {
|
||||
if constexpr(std::is_same_v<ALayout, tensor_layout::gemm::RowMajor>)
|
||||
{
|
||||
return make_tile_window(a_pad_view,
|
||||
make_tuple(number<TilePartitioner::MPerBlock>{},
|
||||
number<TilePartitioner::KPerBlock>{}),
|
||||
{i_m, 0});
|
||||
}
|
||||
else
|
||||
{
|
||||
return make_tile_window(a_pad_view,
|
||||
make_tuple(number<TilePartitioner::KPerBlock>{},
|
||||
number<TilePartitioner::MPerBlock>{}),
|
||||
{0, i_m});
|
||||
}
|
||||
}();
|
||||
|
||||
const auto& bq_block_window = [&]() {
|
||||
static_assert(std::is_same_v<BQLayout, tensor_layout::gemm::ColumnMajor>);
|
||||
return make_tile_window(
|
||||
bq_pad_view,
|
||||
make_tuple(number<TilePartitioner::NPerBlock>{},
|
||||
number<TilePartitioner::KPerBlock / GemmPipeline::QuantGroupSize>{}),
|
||||
{i_n, 0});
|
||||
}();
|
||||
|
||||
const auto& b_block_window = [&]() {
|
||||
if constexpr(std::is_same_v<BLayout, tensor_layout::gemm::ColumnMajor>)
|
||||
{
|
||||
return make_tile_window(b_pad_view,
|
||||
make_tuple(number<TilePartitioner::NPerBlock>{},
|
||||
number<TilePartitioner::KPerBlock>{}),
|
||||
{i_n, 0});
|
||||
}
|
||||
else
|
||||
{
|
||||
return make_tile_window(b_pad_view,
|
||||
make_tuple(number<TilePartitioner::KPerBlock>{},
|
||||
number<TilePartitioner::NPerBlock>{}),
|
||||
{0, i_n});
|
||||
}
|
||||
}();
|
||||
|
||||
auto c_block_window = make_tile_window(
|
||||
c_pad_view,
|
||||
make_tuple(number<TilePartitioner::MPerBlock>{}, number<TilePartitioner::NPerBlock>{}),
|
||||
{i_m, i_n});
|
||||
|
||||
return make_tuple(a_block_window, bq_block_window, b_block_window, c_block_window);
|
||||
}
|
||||
|
||||
/**
|
||||
* @brief Runs single GEMM problem cooperatively by whole workgroup.
|
||||
*
|
||||
* @param a_ptr input A pointer
|
||||
* @param b_ptr input B pointer
|
||||
* @param bq_ptr input BQ pointer
|
||||
* @param c_ptr output C pointer
|
||||
* @param smem_ptr_0 The start memory pointer of the shared memory block.
|
||||
* @param kargs GEMM kernel arguments
|
||||
* @param splitk_batch_offset splitk_batch_offset Utility structure used to calculate k batch.
|
||||
* @param block_idx_m The GEMM's output M dimension tile index processed by this workgroup.
|
||||
* @param block_idx_n The GEMM's output N dimension tile index processed by this workgroup.
|
||||
*
|
||||
* @tparam DstInMemOp Destination memory operation (default: set).
|
||||
*/
|
||||
template <memory_operation_enum DstInMemOp = memory_operation_enum::set>
|
||||
CK_TILE_DEVICE static void RunGemm(const ADataType* a_ptr,
|
||||
const BDataType* b_ptr,
|
||||
const BQDataType* bq_ptr,
|
||||
CDataType* c_ptr,
|
||||
void* smem_ptr_0,
|
||||
const BQuantGemmKernelArgs& kargs,
|
||||
const SplitKBatchOffset& splitk_batch_offset,
|
||||
const index_t block_idx_m,
|
||||
const index_t block_idx_n)
|
||||
{
|
||||
// Create Gemm tensor views, pad views and tile windows
|
||||
const auto& gemm_tensor_views_tuple = MakeGemmTensorViews<DstInMemOp>(
|
||||
a_ptr, b_ptr, bq_ptr, c_ptr, kargs, splitk_batch_offset);
|
||||
|
||||
const auto& gemm_pad_views = MakeGemmPadViews(gemm_tensor_views_tuple);
|
||||
auto gemm_tile_windows = MakeGemmTileWindows(gemm_pad_views, block_idx_m, block_idx_n);
|
||||
|
||||
const index_t num_loop = __builtin_amdgcn_readfirstlane(
|
||||
TilePartitioner::GetLoopNum(splitk_batch_offset.splitted_k));
|
||||
|
||||
// Run GEMM cooperatively by whole workgroup.
|
||||
const auto& a_block_window = gemm_tile_windows.at(I0);
|
||||
const auto& bq_block_window = gemm_tile_windows.at(I1);
|
||||
const auto& b_block_window = gemm_tile_windows.at(I2);
|
||||
|
||||
const auto& c_block_tile = GemmPipeline{}.template operator()(
|
||||
a_block_window, b_block_window, bq_block_window, num_loop, smem_ptr_0);
|
||||
|
||||
// Run Epilogue Pipeline
|
||||
auto& c_block_window = gemm_tile_windows.at(I3);
|
||||
|
||||
EpiloguePipeline{}.template
|
||||
operator()<decltype(c_block_window), decltype(c_block_tile), decltype(c_block_window)>(
|
||||
c_block_window, c_block_tile, c_block_window, smem_ptr_0);
|
||||
}
|
||||
|
||||
CK_TILE_DEVICE void operator()(BQuantGemmKernelArgs kargs) const
|
||||
{
|
||||
const auto blockId = __builtin_amdgcn_readfirstlane(blockIdx.x);
|
||||
const auto [iM, iN] = TilePartitioner{kargs.M, kargs.N}.GetOutputTileIndex(blockId);
|
||||
const index_t i_m = __builtin_amdgcn_readfirstlane(iM * TilePartitioner::MPerBlock);
|
||||
const index_t i_n = __builtin_amdgcn_readfirstlane(iN * TilePartitioner::NPerBlock);
|
||||
|
||||
const SplitKBatchOffset splitk_batch_offset(kargs);
|
||||
// options
|
||||
const ADataType* a_ptr = static_cast<const ADataType*>(kargs.a_ptr);
|
||||
const BDataType* b_ptr = static_cast<const BDataType*>(kargs.b_ptr);
|
||||
const BQDataType* bq_ptr = static_cast<const BQDataType*>(kargs.bq_ptr);
|
||||
CDataType* c_ptr = static_cast<CDataType*>(kargs.c_ptr);
|
||||
|
||||
// allocate LDS
|
||||
__shared__ char smem_ptr_0[GetSmemSize()];
|
||||
|
||||
assert(kargs.k_batch == 1);
|
||||
RunGemm(a_ptr, b_ptr, bq_ptr, c_ptr, smem_ptr_0, kargs, splitk_batch_offset, i_m, i_n);
|
||||
}
|
||||
};
|
||||
|
||||
} // namespace ck_tile
|
||||
@@ -12,117 +12,218 @@
|
||||
#include "ck_tile/core/numeric/integer.hpp"
|
||||
#include "ck_tile/core/numeric/math.hpp"
|
||||
#include "ck_tile/host/concat.hpp"
|
||||
#include "ck_tile/ops/gemm_group_quant/pipeline/tile_gemm_quant_traits.hpp"
|
||||
|
||||
namespace ck_tile {
|
||||
|
||||
struct AQuantGemmProblem
|
||||
namespace detail {
|
||||
// Helper templates for safe type extraction
|
||||
template <typename T, typename Default>
|
||||
struct get_aq_layout_or
|
||||
{
|
||||
CK_TILE_HOST AQuantGemmProblem() = default;
|
||||
CK_TILE_HOST AQuantGemmProblem(index_t M_,
|
||||
index_t N_,
|
||||
index_t K_,
|
||||
index_t QK_,
|
||||
index_t stride_A_,
|
||||
index_t stride_B_,
|
||||
index_t stride_C_,
|
||||
index_t stride_AQ_)
|
||||
using type = Default;
|
||||
};
|
||||
|
||||
template <typename T, typename Default>
|
||||
requires requires { typename T::AQLayout; }
|
||||
struct get_aq_layout_or<T, Default>
|
||||
{
|
||||
using type = typename T::AQLayout;
|
||||
};
|
||||
|
||||
template <typename T, typename Default>
|
||||
struct get_bq_layout_or
|
||||
{
|
||||
using type = Default;
|
||||
};
|
||||
|
||||
template <typename T, typename Default>
|
||||
requires requires { typename T::BQLayout; }
|
||||
struct get_bq_layout_or<T, Default>
|
||||
{
|
||||
using type = typename T::BQLayout;
|
||||
};
|
||||
|
||||
template <typename T, typename Default>
|
||||
struct get_aq_data_type_or
|
||||
{
|
||||
using type = Default;
|
||||
};
|
||||
|
||||
template <typename T, typename Default>
|
||||
requires requires { typename T::AQDataType; }
|
||||
struct get_aq_data_type_or<T, Default>
|
||||
{
|
||||
using type = typename T::AQDataType;
|
||||
};
|
||||
|
||||
template <typename T, typename Default>
|
||||
struct get_bq_data_type_or
|
||||
{
|
||||
using type = Default;
|
||||
};
|
||||
|
||||
template <typename T, typename Default>
|
||||
requires requires { typename T::BQDataType; }
|
||||
struct get_bq_data_type_or<T, Default>
|
||||
{
|
||||
using type = typename T::BQDataType;
|
||||
};
|
||||
|
||||
template <typename T, typename Default>
|
||||
struct get_preshuffle_or
|
||||
{
|
||||
using type = Default;
|
||||
};
|
||||
|
||||
template <typename T, typename Default>
|
||||
requires requires { typename T::PreshuffleQuant; }
|
||||
struct get_preshuffle_or<T, Default>
|
||||
{
|
||||
using type = typename T::PreshuffleQuant;
|
||||
};
|
||||
} // namespace detail
|
||||
|
||||
struct QuantGemmProblem
|
||||
{
|
||||
CK_TILE_HOST QuantGemmProblem() = default;
|
||||
CK_TILE_HOST QuantGemmProblem(index_t M_,
|
||||
index_t N_,
|
||||
index_t K_,
|
||||
index_t QK_A_,
|
||||
index_t QK_B_,
|
||||
index_t stride_A_,
|
||||
index_t stride_B_,
|
||||
index_t stride_C_,
|
||||
index_t stride_AQ_,
|
||||
index_t stride_BQ_)
|
||||
: M(M_),
|
||||
N(N_),
|
||||
K(K_),
|
||||
QK(QK_),
|
||||
QK_A(QK_A_),
|
||||
QK_B(QK_B_),
|
||||
stride_A(stride_A_),
|
||||
stride_B(stride_B_),
|
||||
stride_C(stride_C_),
|
||||
stride_AQ(stride_AQ_)
|
||||
stride_AQ(stride_AQ_),
|
||||
stride_BQ(stride_BQ_)
|
||||
{
|
||||
}
|
||||
|
||||
index_t M;
|
||||
index_t N;
|
||||
index_t K;
|
||||
index_t QK;
|
||||
index_t QK_A;
|
||||
index_t QK_B;
|
||||
index_t stride_A;
|
||||
index_t stride_B;
|
||||
index_t stride_C;
|
||||
index_t stride_AQ;
|
||||
index_t stride_BQ;
|
||||
};
|
||||
|
||||
struct AQuantGemmHostArgs : public AQuantGemmProblem
|
||||
struct QuantGemmHostArgs : public QuantGemmProblem
|
||||
{
|
||||
CK_TILE_HOST AQuantGemmHostArgs() = default;
|
||||
CK_TILE_HOST AQuantGemmHostArgs(const void* a_ptr_,
|
||||
const void* b_ptr_,
|
||||
void* c_ptr_,
|
||||
const void* aq_ptr_,
|
||||
index_t k_batch_,
|
||||
index_t M_,
|
||||
index_t N_,
|
||||
index_t K_,
|
||||
index_t QK_,
|
||||
index_t stride_A_,
|
||||
index_t stride_B_,
|
||||
index_t stride_C_,
|
||||
index_t stride_AQ_)
|
||||
: AQuantGemmProblem(M_, N_, K_, QK_, stride_A_, stride_B_, stride_C_, stride_AQ_),
|
||||
CK_TILE_HOST QuantGemmHostArgs() = default;
|
||||
CK_TILE_HOST QuantGemmHostArgs(const void* a_ptr_,
|
||||
const void* b_ptr_,
|
||||
void* c_ptr_,
|
||||
const void* aq_ptr_,
|
||||
const void* bq_ptr_,
|
||||
index_t k_batch_,
|
||||
index_t M_,
|
||||
index_t N_,
|
||||
index_t K_,
|
||||
index_t QK_A_,
|
||||
index_t QK_B_,
|
||||
index_t stride_A_,
|
||||
index_t stride_B_,
|
||||
index_t stride_C_,
|
||||
index_t stride_AQ_,
|
||||
index_t stride_BQ_)
|
||||
: QuantGemmProblem(
|
||||
M_, N_, K_, QK_A_, QK_B_, stride_A_, stride_B_, stride_C_, stride_AQ_, stride_BQ_),
|
||||
a_ptr(a_ptr_),
|
||||
b_ptr(b_ptr_),
|
||||
aq_ptr(aq_ptr_),
|
||||
bq_ptr(bq_ptr_),
|
||||
c_ptr(c_ptr_),
|
||||
k_batch(k_batch_)
|
||||
{
|
||||
}
|
||||
|
||||
const void* a_ptr;
|
||||
const void* b_ptr;
|
||||
const void* aq_ptr;
|
||||
void* c_ptr;
|
||||
index_t k_batch;
|
||||
const void* a_ptr = nullptr;
|
||||
const void* b_ptr = nullptr;
|
||||
const void* aq_ptr = nullptr;
|
||||
const void* bq_ptr = nullptr;
|
||||
void* c_ptr = nullptr;
|
||||
index_t k_batch = 0;
|
||||
};
|
||||
|
||||
struct AQuantGemmKernelArgs
|
||||
struct QuantGemmKernelArgs
|
||||
{
|
||||
const void* a_ptr;
|
||||
const void* b_ptr;
|
||||
const void* aq_ptr;
|
||||
const void* bq_ptr;
|
||||
void* c_ptr;
|
||||
index_t M;
|
||||
index_t N;
|
||||
index_t K;
|
||||
index_t QK;
|
||||
index_t QK_A;
|
||||
index_t QK_B;
|
||||
index_t stride_A;
|
||||
index_t stride_B;
|
||||
index_t stride_C;
|
||||
index_t stride_AQ;
|
||||
index_t stride_BQ;
|
||||
index_t k_batch;
|
||||
};
|
||||
|
||||
template <typename TilePartitioner_, typename GemmPipeline_, typename EpiloguePipeline_>
|
||||
struct AQuantGemmKernel
|
||||
template <typename TilePartitioner_,
|
||||
typename GemmPipeline_,
|
||||
typename EpiloguePipeline_,
|
||||
QuantType QuantType_>
|
||||
struct QuantGemmKernel
|
||||
{
|
||||
using TilePartitioner = remove_cvref_t<TilePartitioner_>;
|
||||
using GemmPipeline = remove_cvref_t<GemmPipeline_>;
|
||||
using EpiloguePipeline = remove_cvref_t<EpiloguePipeline_>;
|
||||
using ALayout = remove_cvref_t<typename GemmPipeline::ALayout>;
|
||||
using AQLayout = remove_cvref_t<typename GemmPipeline::AQLayout>;
|
||||
using BLayout = remove_cvref_t<typename GemmPipeline::BLayout>;
|
||||
using CLayout = remove_cvref_t<typename GemmPipeline::CLayout>;
|
||||
using TilePartitioner = remove_cvref_t<TilePartitioner_>;
|
||||
using GemmPipeline = remove_cvref_t<GemmPipeline_>;
|
||||
using EpiloguePipeline = remove_cvref_t<EpiloguePipeline_>;
|
||||
using ALayout = remove_cvref_t<typename GemmPipeline::ALayout>;
|
||||
using BLayout = remove_cvref_t<typename GemmPipeline::BLayout>;
|
||||
using CLayout = remove_cvref_t<typename GemmPipeline::CLayout>;
|
||||
|
||||
using AQLayout = remove_cvref_t<
|
||||
typename detail::get_aq_layout_or<GemmPipeline, typename GemmPipeline::ALayout>::type>;
|
||||
using BQLayout = remove_cvref_t<
|
||||
typename detail::get_bq_layout_or<GemmPipeline, typename GemmPipeline::BLayout>::type>;
|
||||
|
||||
static constexpr index_t kBlockSize = GemmPipeline::BlockSize;
|
||||
static constexpr bool PreshuffleQuant = GemmPipeline::PreshuffleQuant;
|
||||
static constexpr bool PreshuffleQuant = remove_cvref_t<
|
||||
typename detail::get_preshuffle_or<GemmPipeline, std::false_type>::type>::value;
|
||||
|
||||
using ADataType = remove_cvref_t<typename GemmPipeline::ADataType>;
|
||||
using AQDataType = remove_cvref_t<typename GemmPipeline::AQDataType>;
|
||||
using BDataType = remove_cvref_t<typename GemmPipeline::BDataType>;
|
||||
using CDataType = remove_cvref_t<typename EpiloguePipeline::ODataType>;
|
||||
using ADataType = remove_cvref_t<typename GemmPipeline::ADataType>;
|
||||
using BDataType = remove_cvref_t<typename GemmPipeline::BDataType>;
|
||||
using CDataType = remove_cvref_t<typename EpiloguePipeline::ODataType>;
|
||||
using AccDataType = remove_cvref_t<typename EpiloguePipeline::AccDataType>;
|
||||
|
||||
static constexpr auto I0 = number<0>();
|
||||
static constexpr auto I1 = number<1>();
|
||||
static constexpr auto I2 = number<2>();
|
||||
static constexpr auto I3 = number<3>();
|
||||
using AQDataType =
|
||||
remove_cvref_t<typename detail::get_aq_data_type_or<GemmPipeline, AccDataType>::type>;
|
||||
using BQDataType =
|
||||
remove_cvref_t<typename detail::get_bq_data_type_or<GemmPipeline, AccDataType>::type>;
|
||||
|
||||
static constexpr auto I0 = number<0>(); // A Tensor
|
||||
static constexpr auto I1 = number<1>(); // AQ Tensor
|
||||
static constexpr auto I2 = number<2>(); // B Tensor
|
||||
static constexpr auto I3 = number<3>(); // BQ Tensor
|
||||
static constexpr auto I4 = number<4>(); // C Tensor
|
||||
|
||||
static constexpr auto kQuantType = QuantType_;
|
||||
|
||||
[[nodiscard]] CK_TILE_HOST static const std::string GetName()
|
||||
{
|
||||
// clang-format off
|
||||
return concat('_', "gemm", gemm_prec_str<ADataType, BDataType>, GemmPipeline::GetName());
|
||||
return concat('_', "gemm_quant", gemm_prec_str<ADataType, BDataType>, GemmPipeline::GetName());
|
||||
// clang-format on
|
||||
}
|
||||
|
||||
@@ -133,22 +234,25 @@ struct AQuantGemmKernel
|
||||
|
||||
CK_TILE_HOST static constexpr auto BlockSize() { return dim3(kBlockSize); }
|
||||
|
||||
CK_TILE_HOST static constexpr AQuantGemmKernelArgs
|
||||
MakeKernelArgs(const AQuantGemmHostArgs& hostArgs)
|
||||
CK_TILE_HOST static constexpr QuantGemmKernelArgs
|
||||
MakeKernelArgs(const QuantGemmHostArgs& hostArgs)
|
||||
{
|
||||
return AQuantGemmKernelArgs{hostArgs.a_ptr,
|
||||
hostArgs.b_ptr,
|
||||
hostArgs.aq_ptr,
|
||||
hostArgs.c_ptr,
|
||||
hostArgs.M,
|
||||
hostArgs.N,
|
||||
hostArgs.K,
|
||||
hostArgs.QK,
|
||||
hostArgs.stride_A,
|
||||
hostArgs.stride_B,
|
||||
hostArgs.stride_C,
|
||||
hostArgs.stride_AQ,
|
||||
hostArgs.k_batch};
|
||||
return QuantGemmKernelArgs{hostArgs.a_ptr,
|
||||
hostArgs.b_ptr,
|
||||
hostArgs.aq_ptr,
|
||||
hostArgs.bq_ptr,
|
||||
hostArgs.c_ptr,
|
||||
hostArgs.M,
|
||||
hostArgs.N,
|
||||
hostArgs.K,
|
||||
hostArgs.QK_A,
|
||||
hostArgs.QK_B,
|
||||
hostArgs.stride_A,
|
||||
hostArgs.stride_B,
|
||||
hostArgs.stride_C,
|
||||
hostArgs.stride_AQ,
|
||||
hostArgs.stride_BQ,
|
||||
hostArgs.k_batch};
|
||||
}
|
||||
|
||||
CK_TILE_HOST_DEVICE static constexpr index_t GetSmemSize()
|
||||
@@ -158,7 +262,7 @@ struct AQuantGemmKernel
|
||||
|
||||
struct SplitKBatchOffset
|
||||
{
|
||||
__device__ SplitKBatchOffset(const AQuantGemmKernelArgs& kargs,
|
||||
__device__ SplitKBatchOffset(const QuantGemmKernelArgs& kargs,
|
||||
const std::size_t k_id = blockIdx.z)
|
||||
{
|
||||
constexpr auto K1 = TilePartitioner::BlockGemmShape::WarpTile::at(I2);
|
||||
@@ -198,7 +302,7 @@ struct AQuantGemmKernel
|
||||
index_t splitted_k;
|
||||
};
|
||||
|
||||
CK_TILE_HOST static bool IsSupportedArgument(const AQuantGemmKernelArgs& kargs)
|
||||
CK_TILE_HOST static bool IsSupportedArgument(const QuantGemmKernelArgs& kargs)
|
||||
{
|
||||
if(kargs.k_batch != 1)
|
||||
{
|
||||
@@ -209,14 +313,31 @@ struct AQuantGemmKernel
|
||||
return false;
|
||||
}
|
||||
|
||||
static_assert(std::is_same_v<AQLayout, tensor_layout::gemm::RowMajor>);
|
||||
if(kargs.QK % GemmPipeline::GetVectorSizeAQ() != 0)
|
||||
if constexpr(kQuantType == QuantType::AQuantGrouped)
|
||||
{
|
||||
if(ck_tile::EnvIsEnabled(CK_TILE_ENV(CK_TILE_LOGGING)))
|
||||
static_assert(std::is_same_v<AQLayout, tensor_layout::gemm::RowMajor>);
|
||||
if(kargs.QK_A % GemmPipeline::GetVectorSizeAQ() != 0)
|
||||
{
|
||||
CK_TILE_ERROR("K is not a multiple of vector load size for A tensor!");
|
||||
if(ck_tile::EnvIsEnabled(CK_TILE_ENV(CK_TILE_LOGGING)))
|
||||
{
|
||||
CK_TILE_ERROR("K_A is not a multiple of vector load size for A tensor!");
|
||||
}
|
||||
return false;
|
||||
}
|
||||
}
|
||||
|
||||
// NOTE: no kernel currently uses BQuant like this:
|
||||
if constexpr(kQuantType == QuantType::BQuantGrouped)
|
||||
{
|
||||
static_assert(std::is_same_v<BQLayout, tensor_layout::gemm::ColumnMajor>);
|
||||
if(kargs.QK_B % GemmPipeline::GetVectorSizeBQ() != 0)
|
||||
{
|
||||
if(ck_tile::EnvIsEnabled(CK_TILE_ENV(CK_TILE_LOGGING)))
|
||||
{
|
||||
CK_TILE_ERROR("K_B is not a multiple of vector load size for B tensor!");
|
||||
}
|
||||
return false;
|
||||
}
|
||||
return false;
|
||||
}
|
||||
|
||||
if constexpr(std::is_same_v<ALayout, tensor_layout::gemm::RowMajor>)
|
||||
@@ -350,8 +471,9 @@ struct AQuantGemmKernel
|
||||
CK_TILE_DEVICE static auto MakeGemmTensorViews(const ADataType* a_ptr,
|
||||
const BDataType* b_ptr,
|
||||
const AQDataType* aq_ptr,
|
||||
const BQDataType* bq_ptr,
|
||||
CDataType* c_ptr,
|
||||
const AQuantGemmKernelArgs& kargs,
|
||||
const QuantGemmKernelArgs& kargs,
|
||||
const SplitKBatchOffset& splitk_batch_offset)
|
||||
{
|
||||
static_assert(!TilePartitioner::BlockGemmShape::PermuteA, "Not implemented!");
|
||||
@@ -380,71 +502,85 @@ struct AQuantGemmKernel
|
||||
return ck_tile::integer_least_multiple(length, alignment) - length;
|
||||
};
|
||||
|
||||
const auto& make_preshuffled_aq_tensor_view = [&]() {
|
||||
const auto aq_x = kargs.M * GemmPipeline::KPerBlockAQ;
|
||||
const auto aq_y = kargs.QK / GemmPipeline::KPerBlockAQ;
|
||||
|
||||
const auto aq_desc =
|
||||
make_naive_tensor_descriptor(make_tuple(aq_y, aq_x),
|
||||
make_tuple(aq_x, 1),
|
||||
number<GemmPipeline::GetVectorSizeAQ()>{},
|
||||
number<1>{});
|
||||
|
||||
const auto block_tile_size = GemmPipeline::MPerBlock * GemmPipeline::KPerBlockAQ;
|
||||
const auto aq_pad0_desc = transform_tensor_descriptor(
|
||||
aq_desc,
|
||||
make_tuple(make_pass_through_transform(aq_y),
|
||||
make_right_pad_transform(aq_x, get_padding_size(aq_x, block_tile_size))),
|
||||
make_tuple(sequence<0>{}, sequence<1>{}),
|
||||
make_tuple(sequence<0>{}, sequence<1>{}));
|
||||
|
||||
const auto pad_aq_x = aq_pad0_desc.get_lengths()[I1];
|
||||
const auto wave_tile_size =
|
||||
TilePartitioner::BlockGemmShape::WarpTile::at(I0) * GemmPipeline::KPerBlockAQ;
|
||||
const auto wave_tile_count_x = ck_tile::integer_divide_ceil(pad_aq_x, wave_tile_size);
|
||||
const auto aq_unmerge_pad0_desc = transform_tensor_descriptor(
|
||||
aq_pad0_desc,
|
||||
make_tuple(make_pass_through_transform(aq_y),
|
||||
make_unmerge_transform(make_tuple(wave_tile_count_x, wave_tile_size))),
|
||||
make_tuple(sequence<0>{}, sequence<1>{}),
|
||||
make_tuple(sequence<0>{}, sequence<1, 2>{}));
|
||||
|
||||
const auto aq_pad1_desc = transform_tensor_descriptor(
|
||||
aq_unmerge_pad0_desc,
|
||||
make_tuple(make_pass_through_transform(aq_y),
|
||||
make_pass_through_transform(wave_tile_count_x),
|
||||
make_right_pad_transform(
|
||||
wave_tile_size, get_padding_size(wave_tile_size, get_warp_size()))),
|
||||
make_tuple(sequence<0>{}, sequence<1>{}, sequence<2>{}),
|
||||
make_tuple(sequence<0>{}, sequence<1>{}, sequence<2>{}));
|
||||
|
||||
const auto pad_wave_size =
|
||||
ck_tile::integer_least_multiple(wave_tile_size, get_warp_size());
|
||||
const auto aq_merge_pad1_desc = transform_tensor_descriptor(
|
||||
aq_pad1_desc,
|
||||
make_tuple(make_merge_transform(make_tuple(aq_y, wave_tile_count_x)),
|
||||
make_pass_through_transform(pad_wave_size)),
|
||||
make_tuple(sequence<0, 1>{}, sequence<2>{}),
|
||||
make_tuple(sequence<0>{}, sequence<1>{}));
|
||||
|
||||
return make_tensor_view<address_space_enum::global>(aq_ptr, aq_merge_pad1_desc);
|
||||
};
|
||||
|
||||
const auto& aq_tensor_view = [&]() {
|
||||
static_assert(std::is_same_v<AQLayout, tensor_layout::gemm::RowMajor>);
|
||||
if constexpr(PreshuffleQuant)
|
||||
if constexpr(kQuantType == QuantType::AQuantGrouped && PreshuffleQuant)
|
||||
{
|
||||
return make_preshuffled_aq_tensor_view();
|
||||
static_assert(std::is_same_v<AQLayout, tensor_layout::gemm::RowMajor>);
|
||||
const auto aq_x = kargs.M * GemmPipeline::KPerBlockAQ;
|
||||
const auto aq_y = kargs.QK_A / GemmPipeline::KPerBlockAQ;
|
||||
|
||||
const auto aq_desc =
|
||||
make_naive_tensor_descriptor(make_tuple(aq_y, aq_x),
|
||||
make_tuple(aq_x, 1),
|
||||
number<GemmPipeline::GetVectorSizeAQ()>{},
|
||||
number<1>{});
|
||||
|
||||
const auto block_tile_size = GemmPipeline::MPerBlock * GemmPipeline::KPerBlockAQ;
|
||||
const auto aq_pad0_desc = transform_tensor_descriptor(
|
||||
aq_desc,
|
||||
make_tuple(
|
||||
make_pass_through_transform(aq_y),
|
||||
make_right_pad_transform(aq_x, get_padding_size(aq_x, block_tile_size))),
|
||||
make_tuple(sequence<0>{}, sequence<1>{}),
|
||||
make_tuple(sequence<0>{}, sequence<1>{}));
|
||||
|
||||
const auto pad_aq_x = aq_pad0_desc.get_lengths()[I1];
|
||||
const auto wave_tile_size =
|
||||
TilePartitioner::BlockGemmShape::WarpTile::at(I0) * GemmPipeline::KPerBlockAQ;
|
||||
const auto wave_tile_count_x =
|
||||
ck_tile::integer_divide_ceil(pad_aq_x, wave_tile_size);
|
||||
const auto aq_unmerge_pad0_desc = transform_tensor_descriptor(
|
||||
aq_pad0_desc,
|
||||
make_tuple(
|
||||
make_pass_through_transform(aq_y),
|
||||
make_unmerge_transform(make_tuple(wave_tile_count_x, wave_tile_size))),
|
||||
make_tuple(sequence<0>{}, sequence<1>{}),
|
||||
make_tuple(sequence<0>{}, sequence<1, 2>{}));
|
||||
|
||||
const auto aq_pad1_desc = transform_tensor_descriptor(
|
||||
aq_unmerge_pad0_desc,
|
||||
make_tuple(
|
||||
make_pass_through_transform(aq_y),
|
||||
make_pass_through_transform(wave_tile_count_x),
|
||||
make_right_pad_transform(
|
||||
wave_tile_size, get_padding_size(wave_tile_size, get_warp_size()))),
|
||||
make_tuple(sequence<0>{}, sequence<1>{}, sequence<2>{}),
|
||||
make_tuple(sequence<0>{}, sequence<1>{}, sequence<2>{}));
|
||||
|
||||
const auto pad_wave_size =
|
||||
ck_tile::integer_least_multiple(wave_tile_size, get_warp_size());
|
||||
const auto aq_merge_pad1_desc = transform_tensor_descriptor(
|
||||
aq_pad1_desc,
|
||||
make_tuple(make_merge_transform(make_tuple(aq_y, wave_tile_count_x)),
|
||||
make_pass_through_transform(pad_wave_size)),
|
||||
make_tuple(sequence<0, 1>{}, sequence<2>{}),
|
||||
make_tuple(sequence<0>{}, sequence<1>{}));
|
||||
|
||||
return make_tensor_view<address_space_enum::global>(aq_ptr, aq_merge_pad1_desc);
|
||||
}
|
||||
else
|
||||
else if constexpr(kQuantType == QuantType::AQuantGrouped && !PreshuffleQuant)
|
||||
{
|
||||
static_assert(std::is_same_v<AQLayout, tensor_layout::gemm::RowMajor>);
|
||||
return make_naive_tensor_view<address_space_enum::global>(
|
||||
aq_ptr,
|
||||
make_tuple(kargs.M, kargs.QK),
|
||||
make_tuple(kargs.M, kargs.QK_A),
|
||||
make_tuple(kargs.stride_AQ, 1),
|
||||
number<GemmPipeline::GetVectorSizeAQ()>{},
|
||||
number<1>{});
|
||||
}
|
||||
else if constexpr(kQuantType == QuantType::RowColQuant)
|
||||
{
|
||||
return make_naive_tensor_view<address_space_enum::global>(
|
||||
aq_ptr,
|
||||
make_tuple(kargs.M, kargs.N),
|
||||
make_tuple(1, 0), // broadcasting over n
|
||||
number<1>{},
|
||||
number<1>{});
|
||||
}
|
||||
else
|
||||
{
|
||||
return nullptr; // TODO: use some other "empty" type for this
|
||||
}
|
||||
}();
|
||||
|
||||
const auto& b_tensor_view = [&]() {
|
||||
@@ -510,6 +646,32 @@ struct AQuantGemmKernel
|
||||
}
|
||||
}();
|
||||
|
||||
const auto& bq_tensor_view = [&]() {
|
||||
if constexpr(kQuantType == QuantType::RowColQuant)
|
||||
{
|
||||
return make_naive_tensor_view<address_space_enum::global>(
|
||||
bq_ptr,
|
||||
make_tuple(kargs.M, kargs.N),
|
||||
make_tuple(0, 1), // broadcasting over m
|
||||
number<1>{},
|
||||
number<1>{});
|
||||
}
|
||||
else if constexpr(kQuantType == QuantType::BQuantGrouped)
|
||||
{
|
||||
static_assert(std::is_same_v<BQLayout, tensor_layout::gemm::ColumnMajor>);
|
||||
return make_naive_tensor_view<address_space_enum::global>(
|
||||
bq_ptr,
|
||||
make_tuple(kargs.N, kargs.QK_B),
|
||||
make_tuple(kargs.stride_BQ, 1),
|
||||
number<GemmPipeline::GetVectorSizeBQ()>{},
|
||||
number<1>{});
|
||||
}
|
||||
else
|
||||
{
|
||||
return nullptr; // TODO: use some other "empty" type for this
|
||||
}
|
||||
}();
|
||||
|
||||
// TODO: enable vector write for C in ColMajor
|
||||
const auto& c_tensor_view = [&]() {
|
||||
if constexpr(std::is_same_v<CLayout, tensor_layout::gemm::RowMajor>)
|
||||
@@ -532,7 +694,8 @@ struct AQuantGemmKernel
|
||||
}
|
||||
}();
|
||||
|
||||
return make_tuple(a_tensor_view, aq_tensor_view, b_tensor_view, c_tensor_view);
|
||||
return make_tuple(
|
||||
a_tensor_view, aq_tensor_view, b_tensor_view, bq_tensor_view, c_tensor_view);
|
||||
}
|
||||
|
||||
template <typename TensorView>
|
||||
@@ -556,6 +719,7 @@ struct AQuantGemmKernel
|
||||
}
|
||||
}();
|
||||
|
||||
// no padding
|
||||
const auto& aq_pad_view = [&]() { return views.at(I1); }();
|
||||
|
||||
const auto& b_pad_view = [&]() {
|
||||
@@ -576,9 +740,12 @@ struct AQuantGemmKernel
|
||||
}
|
||||
}();
|
||||
|
||||
// no padding
|
||||
const auto& bq_pad_view = [&]() { return views.at(I3); }();
|
||||
|
||||
// TODO vector write in for C in ColMajor
|
||||
const auto& c_pad_view = [&]() {
|
||||
const auto& c_tensor_view = views.at(I3);
|
||||
const auto& c_tensor_view = views.at(I4);
|
||||
if constexpr(std::is_same_v<CLayout, tensor_layout::gemm::RowMajor>)
|
||||
{
|
||||
return pad_tensor_view(c_tensor_view,
|
||||
@@ -595,7 +762,7 @@ struct AQuantGemmKernel
|
||||
}
|
||||
}();
|
||||
|
||||
return make_tuple(a_pad_view, aq_pad_view, b_pad_view, c_pad_view);
|
||||
return make_tuple(a_pad_view, aq_pad_view, b_pad_view, bq_pad_view, c_pad_view);
|
||||
}
|
||||
|
||||
template <typename PadView>
|
||||
@@ -605,7 +772,8 @@ struct AQuantGemmKernel
|
||||
const auto& a_pad_view = views.at(I0);
|
||||
const auto& aq_pad_view = views.at(I1);
|
||||
const auto& b_pad_view = views.at(I2);
|
||||
const auto& c_pad_view = views.at(I3);
|
||||
const auto& bq_pad_view = views.at(I3);
|
||||
const auto& c_pad_view = views.at(I4);
|
||||
|
||||
const auto& a_block_window = [&]() {
|
||||
if constexpr(std::is_same_v<ALayout, tensor_layout::gemm::RowMajor>)
|
||||
@@ -625,14 +793,13 @@ struct AQuantGemmKernel
|
||||
}();
|
||||
|
||||
const auto& aq_block_window = [&]() {
|
||||
static_assert(std::is_same_v<AQLayout, tensor_layout::gemm::RowMajor>);
|
||||
constexpr auto block_m = TilePartitioner::MPerBlock;
|
||||
constexpr auto block_k = TilePartitioner::KPerBlock;
|
||||
constexpr auto warp_m = TilePartitioner::BlockGemmShape::WarpTile::at(I0);
|
||||
constexpr auto aqk_per_block =
|
||||
TilePartitioner::KPerBlock / GemmPipeline::QuantGroupSize;
|
||||
if constexpr(PreshuffleQuant)
|
||||
if constexpr(kQuantType == QuantType::AQuantGrouped && PreshuffleQuant)
|
||||
{
|
||||
static_assert(std::is_same_v<AQLayout, tensor_layout::gemm::RowMajor>);
|
||||
constexpr auto block_m = TilePartitioner::MPerBlock;
|
||||
constexpr auto warp_m = TilePartitioner::BlockGemmShape::WarpTile::at(I0);
|
||||
constexpr auto aqk_per_block =
|
||||
TilePartitioner::KPerBlock / GemmPipeline::QuantGroupSize;
|
||||
constexpr auto tile_window_width =
|
||||
ck_tile::integer_least_multiple(warp_m * aqk_per_block, get_warp_size());
|
||||
constexpr auto tile_window_height = block_m / warp_m;
|
||||
@@ -642,13 +809,27 @@ struct AQuantGemmKernel
|
||||
make_tuple(number<tile_window_height>{}, number<tile_window_width>{}),
|
||||
{block_m_idx * tile_window_height, 0});
|
||||
}
|
||||
else
|
||||
else if constexpr(kQuantType == QuantType::AQuantGrouped && !PreshuffleQuant)
|
||||
{
|
||||
static_assert(std::is_same_v<AQLayout, tensor_layout::gemm::RowMajor>);
|
||||
constexpr auto block_m = TilePartitioner::MPerBlock;
|
||||
constexpr auto block_k = TilePartitioner::KPerBlock;
|
||||
return make_tile_window(
|
||||
aq_pad_view,
|
||||
make_tuple(number<block_m>{}, number<block_k / GemmPipeline::QuantGroupSize>{}),
|
||||
{i_m, 0});
|
||||
}
|
||||
else if constexpr(kQuantType == QuantType::RowColQuant)
|
||||
{
|
||||
return make_tile_window(aq_pad_view,
|
||||
make_tuple(number<TilePartitioner::MPerBlock>{},
|
||||
number<TilePartitioner::NPerBlock>{}),
|
||||
{i_m, i_n});
|
||||
}
|
||||
else
|
||||
{
|
||||
return nullptr; // TODO: use some other "empty" type?
|
||||
}
|
||||
}();
|
||||
|
||||
const auto& b_block_window = [&]() {
|
||||
@@ -668,12 +849,36 @@ struct AQuantGemmKernel
|
||||
}
|
||||
}();
|
||||
|
||||
const auto& bq_block_window = [&]() {
|
||||
if constexpr(kQuantType == QuantType::RowColQuant)
|
||||
{
|
||||
return make_tile_window(bq_pad_view,
|
||||
make_tuple(number<TilePartitioner::MPerBlock>{},
|
||||
number<TilePartitioner::NPerBlock>{}),
|
||||
{i_m, i_n});
|
||||
}
|
||||
else if constexpr(kQuantType == QuantType::BQuantGrouped)
|
||||
{
|
||||
static_assert(std::is_same_v<BQLayout, tensor_layout::gemm::ColumnMajor>);
|
||||
return make_tile_window(
|
||||
bq_pad_view,
|
||||
make_tuple(number<TilePartitioner::NPerBlock>{},
|
||||
number<TilePartitioner::KPerBlock / GemmPipeline::QuantGroupSize>{}),
|
||||
{i_n, 0});
|
||||
}
|
||||
else
|
||||
{
|
||||
return nullptr; // TODO: use some other "empty" type here
|
||||
}
|
||||
}();
|
||||
|
||||
auto c_block_window = make_tile_window(
|
||||
c_pad_view,
|
||||
make_tuple(number<TilePartitioner::MPerBlock>{}, number<TilePartitioner::NPerBlock>{}),
|
||||
{i_m, i_n});
|
||||
|
||||
return make_tuple(a_block_window, aq_block_window, b_block_window, c_block_window);
|
||||
return make_tuple(
|
||||
a_block_window, aq_block_window, b_block_window, bq_block_window, c_block_window);
|
||||
}
|
||||
|
||||
/**
|
||||
@@ -695,16 +900,17 @@ struct AQuantGemmKernel
|
||||
CK_TILE_DEVICE static void RunGemm(const ADataType* a_ptr,
|
||||
const BDataType* b_ptr,
|
||||
const AQDataType* aq_ptr,
|
||||
const BQDataType* bq_ptr,
|
||||
CDataType* c_ptr,
|
||||
void* smem_ptr_0,
|
||||
const AQuantGemmKernelArgs& kargs,
|
||||
const QuantGemmKernelArgs& kargs,
|
||||
const SplitKBatchOffset& splitk_batch_offset,
|
||||
const index_t block_idx_m,
|
||||
const index_t block_idx_n)
|
||||
{
|
||||
// Create Gemm tensor views, pad views and tile windows
|
||||
const auto& gemm_tensor_views_tuple = MakeGemmTensorViews<DstInMemOp>(
|
||||
a_ptr, b_ptr, aq_ptr, c_ptr, kargs, splitk_batch_offset);
|
||||
a_ptr, b_ptr, aq_ptr, bq_ptr, c_ptr, kargs, splitk_batch_offset);
|
||||
|
||||
const auto& gemm_pad_views = MakeGemmPadViews(gemm_tensor_views_tuple);
|
||||
auto gemm_tile_windows = MakeGemmTileWindows(gemm_pad_views, block_idx_m, block_idx_n);
|
||||
@@ -713,22 +919,51 @@ struct AQuantGemmKernel
|
||||
TilePartitioner::GetLoopNum(splitk_batch_offset.splitted_k));
|
||||
|
||||
// Run GEMM cooperatively by whole workgroup.
|
||||
const auto& a_block_window = gemm_tile_windows.at(I0);
|
||||
const auto& aq_block_window = gemm_tile_windows.at(I1);
|
||||
const auto& b_block_window = gemm_tile_windows.at(I2);
|
||||
const auto& a_block_window = gemm_tile_windows.at(I0);
|
||||
const auto& b_block_window = gemm_tile_windows.at(I2);
|
||||
|
||||
const auto& c_block_tile = GemmPipeline{}.template operator()(
|
||||
a_block_window, b_block_window, aq_block_window, kargs.M, num_loop, smem_ptr_0);
|
||||
const auto& c_block_tile = [&]() {
|
||||
if constexpr(kQuantType == QuantType::AQuantGrouped)
|
||||
{
|
||||
const auto& aq_block_window = gemm_tile_windows.at(I1);
|
||||
return GemmPipeline{}.template operator()(
|
||||
a_block_window, b_block_window, aq_block_window, kargs.M, num_loop, smem_ptr_0);
|
||||
}
|
||||
else if constexpr(kQuantType == QuantType::BQuantGrouped)
|
||||
{
|
||||
const auto& bq_block_window = gemm_tile_windows.at(I3);
|
||||
return GemmPipeline{}.template operator()(
|
||||
a_block_window, b_block_window, bq_block_window, num_loop, smem_ptr_0);
|
||||
}
|
||||
else if constexpr(kQuantType == QuantType::RowColQuant)
|
||||
{
|
||||
return GemmPipeline{}.template operator()(
|
||||
a_block_window, b_block_window, num_loop, smem_ptr_0);
|
||||
}
|
||||
}();
|
||||
|
||||
// Run Epilogue Pipeline
|
||||
auto& c_block_window = gemm_tile_windows.at(I3);
|
||||
auto& c_block_window = gemm_tile_windows.at(I4);
|
||||
|
||||
EpiloguePipeline{}.template
|
||||
operator()<decltype(c_block_window), decltype(c_block_tile), decltype(c_block_window)>(
|
||||
c_block_window, c_block_tile, c_block_window, smem_ptr_0);
|
||||
if constexpr(kQuantType == QuantType::AQuantGrouped ||
|
||||
kQuantType == QuantType::BQuantGrouped)
|
||||
{
|
||||
EpiloguePipeline{}(c_block_window, c_block_tile, c_block_window, smem_ptr_0);
|
||||
}
|
||||
else if constexpr(kQuantType == QuantType::RowColQuant)
|
||||
{
|
||||
const auto& aq_block_window = gemm_tile_windows.at(I1);
|
||||
const auto& bq_block_window = gemm_tile_windows.at(I3);
|
||||
EpiloguePipeline{}(c_block_window,
|
||||
c_block_tile,
|
||||
c_block_window,
|
||||
smem_ptr_0,
|
||||
aq_block_window,
|
||||
bq_block_window);
|
||||
}
|
||||
}
|
||||
|
||||
CK_TILE_DEVICE void operator()(AQuantGemmKernelArgs kargs) const
|
||||
CK_TILE_DEVICE void operator()(QuantGemmKernelArgs kargs) const
|
||||
{
|
||||
const auto blockId = __builtin_amdgcn_readfirstlane(blockIdx.x);
|
||||
const auto [iM, iN] = TilePartitioner{kargs.M, kargs.N}.GetOutputTileIndex(blockId);
|
||||
@@ -740,13 +975,15 @@ struct AQuantGemmKernel
|
||||
const ADataType* a_ptr = static_cast<const ADataType*>(kargs.a_ptr);
|
||||
const BDataType* b_ptr = static_cast<const BDataType*>(kargs.b_ptr);
|
||||
const AQDataType* aq_ptr = static_cast<const AQDataType*>(kargs.aq_ptr);
|
||||
const BQDataType* bq_ptr = static_cast<const BQDataType*>(kargs.bq_ptr);
|
||||
CDataType* c_ptr = static_cast<CDataType*>(kargs.c_ptr);
|
||||
|
||||
// allocate LDS
|
||||
__shared__ char smem_ptr_0[GetSmemSize()];
|
||||
|
||||
assert(kargs.k_batch == 1);
|
||||
RunGemm(a_ptr, b_ptr, aq_ptr, c_ptr, smem_ptr_0, kargs, splitk_batch_offset, i_m, i_n);
|
||||
RunGemm(
|
||||
a_ptr, b_ptr, aq_ptr, bq_ptr, c_ptr, smem_ptr_0, kargs, splitk_batch_offset, i_m, i_n);
|
||||
}
|
||||
};
|
||||
|
||||
Reference in New Issue
Block a user