mirror of
https://github.com/ROCm/composable_kernel.git
synced 2026-05-11 08:50:17 +00:00
refactor
This commit is contained in:
Chao Liu
@@ -87,9 +87,6 @@ void device_implicit_gemm_convolution_1_chwn_csrk_khwn(InDesc,
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constexpr unsigned HoPerThread = 1;
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constexpr unsigned WoPerThread = 1;
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constexpr unsigned WeiBlockCopyThreadPerDim0 = 4;
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constexpr unsigned WeiBlockCopyThreadPerDim1 = 32;
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constexpr unsigned InBlockCopy_ThreadPerDimC = 4;
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constexpr unsigned InBlockCopy_ThreadPerDimH = 4;
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constexpr unsigned InBlockCopy_ThreadPerDimW = 2;
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@@ -278,8 +275,6 @@ void device_implicit_gemm_convolution_1_chwn_csrk_khwn(InDesc,
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KPerThread,
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HoPerThread,
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WoPerThread,
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WeiBlockCopyThreadPerDim0,
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WeiBlockCopyThreadPerDim1,
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Sequence<InBlockCopy_ThreadPerDimC,
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InBlockCopy_ThreadPerDimH,
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InBlockCopy_ThreadPerDimW,
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@@ -2,6 +2,7 @@
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#include <numeric>
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#include <initializer_list>
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#include <cstdlib>
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#include <stdlib.h>
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#include "config.h"
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#include "tensor.hpp"
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#include "ConstantTensorDescriptor.hip.hpp"
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@@ -378,7 +379,7 @@ void check_error(const Tensor<T>& ref, const Tensor<T>& result)
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std::cout << "max_diff: " << max_diff << ", " << ref_value << ", " << result_value << std::endl;
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}
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int main()
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int main(int argc, char* argv[])
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{
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#if 0
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constexpr unsigned N = 1;
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@@ -571,7 +572,14 @@ int main()
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std::size_t num_thread = std::thread::hardware_concurrency();
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bool do_verification = true;
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if(argc != 3)
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{
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printf("arg1: do_verification, arg2: nrepeat\n");
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exit(1);
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}
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bool do_verification = atoi(argv[1]);
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unsigned nrepeat = atoi(argv[2]);
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if(do_verification)
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{
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@@ -587,8 +595,6 @@ int main()
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#endif
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}
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unsigned nrepeat = 200;
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#if 1
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#if 0
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device_direct_convolution_1
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@@ -23,8 +23,6 @@ template <unsigned GridSize,
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unsigned KPerThread,
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unsigned HoPerThread,
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unsigned WoPerThread,
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unsigned WeiBlockCopyThreadPerDim0,
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unsigned WeiBlockCopyThreadPerDim1,
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class InBlockCopyThreadPerDims,
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unsigned InBlockCopyDataPerRead,
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unsigned WeiBlockCopyDataPerRead,
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@@ -109,69 +107,31 @@ gridwise_implicit_gemm_convolution_1_chwn_csrk_khwn(const Float* const __restric
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constexpr auto out_khwn_thread_desc =
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make_ConstantTensorDescriptor(Sequence<KPerThread, HoPerThread, WoPerThread, NPerThread>{});
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#if 0
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if(get_thread_local_1d_id() == 0 && get_block_1d_id() == 0)
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{
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print_ConstantTensorDescriptor(in_nchw_block_desc, "in_nchw_block_desc");
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print_ConstantTensorDescriptor(in_chwn_block_desc, "in_chwn_block_desc");
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print_ConstantTensorDescriptor(wei_srck_block_desc, "wei_srck_block_desc");
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print_ConstantTensorDescriptor(out_hkwn_thread_desc, "out_hkwn_thread_desc");
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}
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#endif
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// blockwise copy
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// input: format is [C, Hi, Wi, N]
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#if 0
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constexpr auto blockwise_in_copy =
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Blockwise4dTensorCopy1<BlockSize,
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Float,
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decltype(in_chwn_global_desc),
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decltype(in_chwn_block_desc),
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decltype(in_chwn_block_desc.GetLengths())>{};
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#elif 1
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const auto blockwise_in_copy = Blockwise4dTensorCopy3<BlockSize,
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const auto blockwise_in_copy = Blockwise4dTensorCopy3<BlockSize,
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Float,
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decltype(in_chwn_global_desc),
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decltype(in_chwn_block_desc),
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decltype(in_chwn_block_desc.GetLengths()),
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InBlockCopyThreadPerDims,
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InBlockCopyDataPerRead>{};
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#endif
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// blockwise wei copy
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// format is [CPerBlock*S*R,KPerBlock]
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#if 0
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const auto blockwise_wei_copy =
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Blockwise2dTensorCopy1<BlockSize,
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Float,
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decltype(wei_ek_global_desc),
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decltype(wei_ek_block_desc),
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decltype(wei_ek_block_desc.GetLengths())>{};
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#elif 0
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const auto blockwise_wei_copy = Blockwise2dTensorCopy2<BlockSize,
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Float,
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decltype(wei_ek_global_desc),
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decltype(wei_ek_block_desc),
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decltype(wei_ek_block_desc.GetLengths()),
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WeiBlockCopyThreadPerDim0,
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WeiBlockCopyThreadPerDim1>{};
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#elif 1
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// blockwise wei copy
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// format is [CPerBlock*S*R,KPerBlock]
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const auto blockwise_wei_copy = Blockwise2dTensorCopy3<BlockSize,
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Float,
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decltype(wei_ek_global_desc),
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decltype(wei_ek_block_desc),
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decltype(wei_ek_block_desc.GetLengths()),
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WeiBlockCopyDataPerRead>{};
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#endif
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// a series of blockwise batched GEMM
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// C_matrix += transpose(A_matrix) * B_matrix
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// A_matrix and B_matrix saved in LDS, C_matrix saved in register
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// A_matrix[C,K] is a sub-matrix of wei_block[S,R,C,K]
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// A_matrix[C,K] is a sub-matrix of wei_block[C,S,R,K]
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// B_matrix[C,Wo*N] is a sub-matrix of in_block[C,Hi,Wi,N]
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// C_matrix[K,Wo*N] is a sub-matrix of out_block[Ho,K,Wo,N]
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// C_matrix[K,Wo*N] is a sub-matrix of out_block[K,Ho,Wo,N]
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constexpr auto a_cxk_block_mtx_desc = make_ConstantMatrixDescriptor(
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Number<CPerBlock>{}, Number<KPerBlock>{}, Number<wei_csrk_block_desc.GetStride(I0)>{});
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@@ -185,23 +145,6 @@ gridwise_implicit_gemm_convolution_1_chwn_csrk_khwn(const Float* const __restric
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Number<WoPerThread * NPerThread>{},
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Number<out_khwn_thread_desc.GetStride(I1)>{});
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#if 0
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const auto blockwise_batch_gemm =
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Blockwise1dStridedBatchedGemmBlockABlockBThreadC<BlockSize,
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decltype(a_cxk_block_mtx_desc),
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decltype(b_cxwn_block_mtx_desc),
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decltype(c_kxwn_thread_mtx_desc),
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true,
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false,
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false,
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0,
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in_chwn_block_desc.GetStride(I1),
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out_khwn_thread_desc.GetStride(I1),
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HoPerBlock,
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HoPerThread,
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GemmKPerThreadLoop,
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true>{};
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#else
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const auto blockwise_batch_gemm = BlockwiseBatchGemmBlockABlockBThreadCTransANormalBNormalC_V2<
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BlockSize,
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decltype(a_cxk_block_mtx_desc),
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@@ -219,7 +162,6 @@ gridwise_implicit_gemm_convolution_1_chwn_csrk_khwn(const Float* const __restric
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GemmNLevel1Cluster,
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GemmKPerThreadLoop,
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HoPerThread>{};
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#endif
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// LDS: be careful of alignment
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constexpr unsigned in_block_size = in_chwn_block_desc.GetElementSpace();
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@@ -277,26 +219,6 @@ gridwise_implicit_gemm_convolution_1_chwn_csrk_khwn(const Float* const __restric
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const auto c_thread_mtx_begin =
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blockwise_batch_gemm.GetBeginOfThreadMatrixC(get_thread_local_1d_id());
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// for v1 batch-gemm
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const unsigned k_thread_data_begin = c_thread_mtx_begin.row;
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const unsigned ho_thread_data_begin = c_thread_mtx_begin.batch;
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const unsigned wo_thread_data_begin = c_thread_mtx_begin.col / NPerBlock;
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const unsigned n_thread_data_begin = c_thread_mtx_begin.col % NPerBlock;
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threadwise_4d_tensor_copy_v2(
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out_khwn_thread_desc,
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p_out_thread,
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out_khwn_global_desc,
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p_out_global + out_khwn_global_desc.Get1dIndex(k_block_data_begin + k_thread_data_begin,
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ho_block_data_begin + ho_thread_data_begin,
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wo_block_data_begin + wo_thread_data_begin,
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n_block_data_begin + n_thread_data_begin),
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out_khwn_thread_desc.GetLengths(),
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Number<OutThreadCopyDataPerWrite>{});
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#elif 0
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const auto c_thread_mtx_begin =
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blockwise_batch_gemm.GetBeginOfThreadMatrixC(get_thread_local_1d_id());
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for(unsigned k = 0; k < out_khwn_thread_desc.GetLength(I0); ++k)
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{
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for(unsigned ho = 0; ho < out_khwn_thread_desc.GetLength(I1); ++ho)
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@@ -334,7 +256,7 @@ gridwise_implicit_gemm_convolution_1_chwn_csrk_khwn(const Float* const __restric
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const unsigned k_thread_data_begin = c_thread_mtx_begin.row;
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const unsigned ho_thread_data_begin = c_thread_mtx_begin.batch;
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const unsigned wo_thread_data_begin = c_thread_mtx_begin.col / NPerBlock;
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const unsigned n_thread_data_begin = c_thread_mtx_begin.col % NPerBlock;
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const unsigned n_thread_data_begin = c_thread_mtx_begin.col - NPerBlock * wo_thread_data_begin;
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// this is for v2 GEMM
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// output is a 8d tensor
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@@ -375,6 +297,8 @@ gridwise_implicit_gemm_convolution_1_chwn_csrk_khwn(const Float* const __restric
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}
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else if(NPerThread == NPerBlock)
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{
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// not implemented yet
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assert(false);
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}
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else
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{
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