mirror of
https://github.com/ROCm/composable_kernel.git
synced 2026-05-11 08:50:17 +00:00
added lds doubl buffer for implicit gemm v4 (nchw, kcyx)
This commit is contained in:
Chao Liu
@@ -3,6 +3,7 @@
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#include "device.hpp"
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#include "gridwise_convolution_wrapper.hip.hpp"
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#include "gridwise_convolution_implicit_gemm_v4_nchw_kcyx_nkhw.hip.hpp"
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#include "gridwise_convolution_implicit_gemm_v4_lds_double_buffer_nchw_kcyx_nkhw.hip.hpp"
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template <class T, class InDesc, class WeiDesc, class OutDesc>
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void device_convolution_implicit_gemm_v4_nchw_kcyx_nkhw(InDesc,
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@@ -86,8 +87,10 @@ void device_convolution_implicit_gemm_v4_nchw_kcyx_nkhw(InDesc,
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for(index_t i = 0; i < nrepeat; ++i)
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{
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constexpr auto gridwise_conv =
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#if 1
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#if 0
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GridwiseConvolutionImplicitGemm_v4_nchw_kcyx_nkhw
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#else
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GridwiseConvolutionImplicitGemm_v4_lds_double_buffer_nchw_kcyx_nkhw
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#endif
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<GridSize,
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BlockSize,
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@@ -455,10 +455,10 @@ int main(int argc, char* argv[])
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constexpr index_t HPad = 0;
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constexpr index_t WPad = 0;
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#elif 0
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#elif 1
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// 1x1 filter, 28x28 image
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constexpr index_t N = 16;
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constexpr index_t C = 256;
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constexpr index_t N = 128;
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constexpr index_t C = 512;
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constexpr index_t HI = 28;
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constexpr index_t WI = 28;
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constexpr index_t K = 512;
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@@ -0,0 +1,421 @@
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#pragma once
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#include "common.hip.hpp"
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#include "ConstantTensorDescriptor.hip.hpp"
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#include "ConstantMergedTensorDescriptor.hip.hpp"
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#include "ConstantMatrixDescriptor.hip.hpp"
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#include "blockwise_generic_tensor_slice_op.hip.hpp"
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#include "blockwise_gemm.hip.hpp"
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#include "threadwise_tensor_slice_op.hip.hpp"
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// define B = merge(N, Ho, Wo)
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template <index_t GridSize,
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index_t BlockSize,
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class Float,
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class InGlobalDesc,
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class WeiGlobalDesc,
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class OutGlobalDesc,
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index_t BPerBlock,
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index_t KPerBlock,
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index_t EPerBlock,
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index_t N1,
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index_t N2,
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index_t GemmMPerThreadSubC,
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index_t GemmNPerThreadSubC,
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index_t GemmMLevel0Cluster,
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index_t GemmNLevel0Cluster,
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index_t GemmMLevel1Cluster,
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index_t GemmNLevel1Cluster,
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index_t GemmKPerThreadLoop,
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index_t GemmDataPerReadA,
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index_t GemmDataPerReadB,
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class InBlockCopySubLengths_E_N1_B_N2,
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class InBlockCopyClusterLengths_E_N1_B_N2,
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index_t InBlockCopySrcDataPerRead_B,
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index_t InBlockCopyDstDataPerWrite_N2,
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class WeiBlockCopySubLengths_E_K,
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class WeiBlockCopyClusterLengths_E_K,
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index_t WeiBlockCopySrcDataPerRead_E,
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index_t WeiBlockCopyDstDataPerWrite_K>
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struct GridwiseConvolutionImplicitGemm_v4_lds_double_buffer_nchw_kcyx_nkhw
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{
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__device__ void Run(const Float* const __restrict__ p_in_global,
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const Float* const __restrict__ p_wei_global,
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Float* const __restrict__ p_out_global) const
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{
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// this is a mess
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// TODO: find more elegent way of specifying (or calculating) performance parameters
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static_assert(N2 == GemmNPerThreadSubC, "wrong!");
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static_assert((N1 * N2 * BPerBlock) %
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(GemmNPerThreadSubC * GemmNLevel0Cluster * GemmNLevel1Cluster) ==
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0,
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"wrong!");
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constexpr auto I0 = Number<0>{};
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constexpr auto I1 = Number<1>{};
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constexpr auto I2 = Number<2>{};
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constexpr auto I3 = Number<3>{};
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constexpr auto I4 = Number<4>{};
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constexpr auto I5 = Number<5>{};
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constexpr auto I6 = Number<6>{};
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constexpr auto I7 = Number<7>{};
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constexpr auto True = integral_constant<bool, true>{};
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constexpr auto in_n_c_h_w_global_desc = InGlobalDesc{};
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constexpr auto wei_k_c_y_x_global_desc = WeiGlobalDesc{};
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constexpr auto out_n_k_h_w_global_desc = OutGlobalDesc{};
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constexpr index_t N = in_n_c_h_w_global_desc.GetLength(I0);
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constexpr index_t C = in_n_c_h_w_global_desc.GetLength(I1);
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constexpr index_t Hi = in_n_c_h_w_global_desc.GetLength(I2);
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constexpr index_t Wi = in_n_c_h_w_global_desc.GetLength(I3);
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constexpr index_t K = out_n_k_h_w_global_desc.GetLength(I1);
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constexpr index_t Ho = out_n_k_h_w_global_desc.GetLength(I2);
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constexpr index_t Wo = out_n_k_h_w_global_desc.GetLength(I3);
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constexpr index_t Y = wei_k_c_y_x_global_desc.GetLength(I2);
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constexpr index_t X = wei_k_c_y_x_global_desc.GetLength(I3);
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static_assert(N % (N1 * N2) == 0, "wrong! cannot divice N evenly among thread");
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constexpr index_t N0 = N / (N1 * N2);
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constexpr index_t B = N0 * Ho * Wo;
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constexpr index_t E = C * Y * X;
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// divide block work by [K, B]
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static_assert(K % KPerBlock == 0 && B % BPerBlock == 0 && E % (2 * EPerBlock) == 0,
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"wrong! cannot divide work evenly among block");
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constexpr index_t KBlockWork = K / KPerBlock;
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constexpr index_t BBlockWork = B / BPerBlock;
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constexpr auto block_work_desc =
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make_ConstantTensorDescriptor_default_rank_packed(Sequence<KBlockWork, BBlockWork>{});
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const auto block_work_multi_id =
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block_work_desc.GetMultiIndexFrom1dIndex(get_block_1d_id());
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const index_t k_block_data_on_global = block_work_multi_id[0] * KPerBlock;
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const index_t b_block_data_on_global = block_work_multi_id[1] * BPerBlock;
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// input tensor
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// tensor descriptor in device memory [N0, N1, N2, Ho, Wo]
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constexpr auto in_n0_n1_n2_h_w_global_desc = in_n_c_h_w_global_desc.Slice(I2, Number<Ho>{})
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.Slice(I3, Number<Wo>{})
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.Fold(I0, Number<N1>{}, Number<N2>{})
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.Extract(Sequence<0, 1, 2, 4, 5>{});
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// batch descritpor for device memory
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constexpr auto in_c_y_x_global_desc = in_n_c_h_w_global_desc.Slice(I2, Number<Y>{})
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.Slice(I3, Number<X>{})
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.Extract(Sequence<1, 2, 3>{});
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// merged tensor descriptor in device memory [E, N1, B, N2], src of blockwise copy
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constexpr auto in_e_n1_b_n2_global_merged_desc = make_ConstantMergedTensorDescriptor(
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in_c_y_x_global_desc.Embed(in_n0_n1_n2_h_w_global_desc),
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Sequence<0, 1, 2>{},
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Sequence<4>{},
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Sequence<3, 6, 7>{},
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Sequence<5>{});
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#if 0
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if(get_block_1d_id() == 0 && get_thread_local_1d_id() == 0)
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{
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print_ConstantTensorDescriptor(in_n0_n1_n2_h_w_global_desc,
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"in_n0_n1_n2_h_w_global_desc: ");
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print_ConstantTensorDescriptor(in_c_y_x_global_desc, "in_c_y_x_global_desc: ");
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print_ConstantMergedTensorDescriptor(in_e_n1_b_n2_global_merged_desc,
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"in_e_n1_b_n2_global_merged_desc: ");
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}
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#endif
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// memory layout descriptor in LDS [E, N1, B, N2], dst of blockwise copy
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// be careful of LDS alignment
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constexpr auto in_e_n1_b_n2_block_desc = make_ConstantTensorDescriptor_default_rank_aligned(
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Sequence<EPerBlock, N1, BPerBlock, N2>{}, Number<InBlockCopyDstDataPerWrite_N2>{});
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// this check is ad-hoc
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// TODO: need to properly implement tensor descriptor with multiple alignment
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// requirements
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static_assert(in_e_n1_b_n2_block_desc.GetStride(I1) % GemmDataPerReadB == 0,
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"GemmDataPerReadB alignment requirement is not satisfied");
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// input blockwise copy
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// slice a merged tensor, reorder and copy to a normal tensor
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// this copy operator already has blockwise offset built-in
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auto blockwise_in_copy = BlockwiseGenericTensorSliceCopy_v1<
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BlockSize,
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Float,
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decltype(in_e_n1_b_n2_global_merged_desc),
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decltype(in_e_n1_b_n2_block_desc),
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decltype(in_e_n1_b_n2_block_desc.GetLengths()),
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InBlockCopySubLengths_E_N1_B_N2,
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InBlockCopyClusterLengths_E_N1_B_N2,
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Sequence<0, 1, 3, 2>, // thread_arrange_order [E, N1, N2, B]
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Sequence<0, 1, 3, 2>, // src_access_order [E, N1, N2, B]
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Sequence<0, 1, 2, 3>, // dst_access_order [E, N1, B, N2]
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InBlockCopySrcDataPerRead_B,
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InBlockCopyDstDataPerWrite_N2>({0, 0, b_block_data_on_global, 0}, {0, 0, 0, 0});
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// weight tensor
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// tensor descriptor in device memory, src of blockwise copy
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constexpr auto wei_e_k_global_desc =
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wei_k_c_y_x_global_desc.Unfold(I1, I3).ReorderGivenNew2Old(Sequence<1, 0>{});
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// tensor descriptor in LDS, dst of blockwise copy
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// be careful of LDS alignment
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constexpr auto wei_e_k_block_desc = make_ConstantTensorDescriptor_default_rank_aligned(
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Sequence<EPerBlock, KPerBlock>{},
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Number<mod_conv::max(WeiBlockCopyDstDataPerWrite_K, GemmDataPerReadA)>{});
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// operator for blockwise copy of weight into LDS
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// slice a tensor, and copy it into another tensor
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// this copy operator already have blockwise offset built-in
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auto blockwise_wei_copy =
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BlockwiseGenericTensorSliceCopy_v1<BlockSize,
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Float,
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decltype(wei_e_k_global_desc),
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decltype(wei_e_k_block_desc),
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decltype(wei_e_k_block_desc.GetLengths()),
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WeiBlockCopySubLengths_E_K,
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WeiBlockCopyClusterLengths_E_K,
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Sequence<1, 0>, // thread_arrange_order [K, E]
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Sequence<1, 0>, // src_access_order [K, E]
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Sequence<0, 1>, // dst_access_order [E, K]
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WeiBlockCopySrcDataPerRead_E,
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WeiBlockCopyDstDataPerWrite_K>(
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{0, k_block_data_on_global}, {0, 0});
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// GEMM definition
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// c_mtx += transpose(a_mtx) * b_mtx
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// a_mtx[EPerBlock, KPerBlock] is in LDS
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// b_mtx[EPerBlocl, N1 * BPerBlock * N2] is in LDS
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// c_mtx[KPerBlock, N1 * BPerBlock * N2] is distributed among threads, and saved in
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// register
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constexpr auto a_e_k_block_mtx_desc = make_ConstantMatrixDescriptor(
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Number<EPerBlock>{}, Number<KPerBlock>{}, Number<wei_e_k_block_desc.GetStride(I0)>{});
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constexpr auto b_e_n1bn2_block_mtx_desc =
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make_ConstantMatrixDescriptor(Number<EPerBlock>{},
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Number<N1 * BPerBlock * N2>{},
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Number<in_e_n1_b_n2_block_desc.GetStride(I0)>{});
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// sanity check
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static_assert(KPerBlock % (GemmMPerThreadSubC * GemmMLevel0Cluster * GemmMLevel1Cluster) ==
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0,
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"wrong!");
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constexpr index_t GemmMRepeat =
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KPerBlock / (GemmMPerThreadSubC * GemmMLevel0Cluster * GemmMLevel1Cluster);
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// c_thread_mtx definition: this is a mess
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// TODO:: more elegent way of defining c_thread_mtx
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constexpr auto c_k0k2_n1n2_thread_mtx_desc = make_ConstantMatrixDescriptor(
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Number<GemmMRepeat * GemmMPerThreadSubC>{}, Number<N1 * N2>{});
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const auto blockwise_gemm = BlockwiseGemmBlockABlockBThreadCTransANormalBNormalC_v2<
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BlockSize,
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decltype(a_e_k_block_mtx_desc),
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decltype(b_e_n1bn2_block_mtx_desc),
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decltype(c_k0k2_n1n2_thread_mtx_desc),
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GemmMPerThreadSubC,
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GemmNPerThreadSubC,
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GemmMLevel0Cluster,
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GemmNLevel0Cluster,
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GemmMLevel1Cluster,
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GemmNLevel1Cluster,
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GemmKPerThreadLoop,
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GemmDataPerReadA,
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GemmDataPerReadB>{};
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// choose GEMM implementation here
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const auto run_blockwise_gemm = [&](auto... Xs) {
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#if 1
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return blockwise_gemm.Run(Xs...);
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#elif 0
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return blockwise_gemm.Run_asm(Xs...);
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#endif
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};
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// LDS allocation for input and weight: be careful of alignment
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constexpr index_t max_align = mod_conv::max(InBlockCopyDstDataPerWrite_N2,
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WeiBlockCopyDstDataPerWrite_K,
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GemmDataPerReadA,
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GemmDataPerReadB);
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constexpr index_t in_block_space =
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in_e_n1_b_n2_block_desc.GetElementSpace(Number<max_align>{});
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constexpr index_t wei_block_space = wei_e_k_block_desc.GetElementSpace(Number<max_align>{});
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__shared__ Float p_in_block_double[2 * in_block_space];
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__shared__ Float p_wei_block_double[2 * wei_block_space];
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// register allocation for output
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Float p_out_thread[c_k0k2_n1n2_thread_mtx_desc.GetElementSpace()];
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// zero out threadwise output
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threadwise_matrix_set_zero(c_k0k2_n1n2_thread_mtx_desc, p_out_thread);
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#if 0
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if(e == 0 * EPerBlock && get_block_1d_id() == 0)
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{
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printf("id %5u %5u: "
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"mThreadSrcOffset %u, mThreadDstOffset %u \n",
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get_block_1d_id(),
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get_thread_local_1d_id(),
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blockwise_wei_copy.mThreadSrcOffset,
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blockwise_wei_copy.mThreadDstOffset);
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}
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#endif
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// LDS double buffer: preload data into LDS
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{
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Float p_in_register_clipboard[blockwise_in_copy.GetRegisterClipboardSize()];
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Float p_wei_register_clipboard[blockwise_wei_copy.GetRegisterClipboardSize()];
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blockwise_in_copy.RunLoadRegisterClipboard(p_in_global, p_in_register_clipboard);
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blockwise_wei_copy.RunLoadRegisterClipboard(p_wei_global, p_wei_register_clipboard);
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blockwise_in_copy.RunStoreRegisterClipboard(p_in_register_clipboard, p_in_block_double);
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blockwise_wei_copy.RunStoreRegisterClipboard(p_wei_register_clipboard,
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p_wei_block_double);
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}
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// LDS double buffer: main body
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for(index_t e_block_data_begin = 0; e_block_data_begin + 2 * EPerBlock < E;
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e_block_data_begin += 2 * EPerBlock)
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{
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#pragma unroll
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for(index_t iloop = 0; iloop < 2; ++iloop)
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{
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const bool even_loop = (iloop % 2 == 0);
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Float* p_in_block_now =
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even_loop ? p_in_block_double : p_in_block_double + in_block_space;
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Float* p_wei_block_now =
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even_loop ? p_wei_block_double : p_wei_block_double + wei_block_space;
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Float* p_in_block_next =
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even_loop ? p_in_block_double + in_block_space : p_in_block_double;
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Float* p_wei_block_next =
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even_loop ? p_wei_block_double + wei_block_space : p_wei_block_double;
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Float p_in_register_clipboard[blockwise_in_copy.GetRegisterClipboardSize()];
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Float p_wei_register_clipboard[blockwise_wei_copy.GetRegisterClipboardSize()];
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blockwise_in_copy.MoveSlicingWindowOnSourceTensor(I0, Number<EPerBlock>{}, True);
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blockwise_wei_copy.MoveSlicingWindowOnSourceTensor(I0, Number<EPerBlock>{}, True);
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__syncthreads();
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// LDS doubel buffer: load next data from device mem
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blockwise_in_copy.RunLoadRegisterClipboard(p_in_global, p_in_register_clipboard);
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blockwise_wei_copy.RunLoadRegisterClipboard(p_wei_global, p_wei_register_clipboard);
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// LDS double buffer: GEMM on current data
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run_blockwise_gemm(p_wei_block_now, p_in_block_now, p_out_thread);
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// LDS double buffer: store next data to LDS
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blockwise_in_copy.RunStoreRegisterClipboard(p_in_register_clipboard,
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p_in_block_next);
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blockwise_wei_copy.RunStoreRegisterClipboard(p_wei_register_clipboard,
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p_wei_block_next);
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}
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}
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// LDS double buffer: tail
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{
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Float p_in_register_clipboard[blockwise_in_copy.GetRegisterClipboardSize()];
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Float p_wei_register_clipboard[blockwise_wei_copy.GetRegisterClipboardSize()];
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// even iteration
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blockwise_in_copy.MoveSlicingWindowOnSourceTensor(I0, Number<EPerBlock>{}, True);
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blockwise_wei_copy.MoveSlicingWindowOnSourceTensor(I0, Number<EPerBlock>{}, True);
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__syncthreads();
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// LDS doubel buffer: load next data from device mem
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blockwise_in_copy.RunLoadRegisterClipboard(p_in_global, p_in_register_clipboard);
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blockwise_wei_copy.RunLoadRegisterClipboard(p_wei_global, p_wei_register_clipboard);
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// LDS double buffer: GEMM on current data
|
||||
run_blockwise_gemm(p_wei_block_double, p_in_block_double, p_out_thread);
|
||||
|
||||
// LDS double buffer: store next data to LDS
|
||||
blockwise_in_copy.RunStoreRegisterClipboard(p_in_register_clipboard,
|
||||
p_in_block_double + in_block_space);
|
||||
blockwise_wei_copy.RunStoreRegisterClipboard(p_wei_register_clipboard,
|
||||
p_wei_block_double + wei_block_space);
|
||||
|
||||
// odd iteration
|
||||
__syncthreads();
|
||||
|
||||
// LDS double buffer: GEMM on current data
|
||||
run_blockwise_gemm(p_wei_block_double + wei_block_space,
|
||||
p_in_block_double + in_block_space,
|
||||
p_out_thread);
|
||||
}
|
||||
|
||||
// copy output: register to global memory
|
||||
{
|
||||
constexpr index_t K2 = GemmMPerThreadSubC;
|
||||
constexpr index_t K1 = GemmMLevel0Cluster * GemmMLevel1Cluster;
|
||||
constexpr index_t K0 = K / (K1 * K2);
|
||||
|
||||
// define tensor descriptor for threadwise copy
|
||||
// output memory layout descriptor in register
|
||||
constexpr auto out_k0_k1_k2_n1_n0_h_w_n2_thread_mem_desc =
|
||||
make_ConstantTensorDescriptor_default_rank_packed(
|
||||
Sequence<KPerBlock / (K1 * K2), 1, K2, N1, 1, 1, 1, N2>{});
|
||||
|
||||
// output tensor descriptor in register, src of threadwise copy
|
||||
constexpr auto out_n0_n1_n2_k0_k1_k2_h_w_thread_desc =
|
||||
out_k0_k1_k2_n1_n0_h_w_n2_thread_mem_desc.ReorderGivenNew2Old(
|
||||
Sequence<4, 3, 7, 0, 1, 2, 5, 6>{});
|
||||
|
||||
// output memory layout descriptor in device memory, dst of threadwise copy
|
||||
constexpr auto out_n0_n1_n2_k0_k1_k2_h_w_global_mem_desc =
|
||||
out_n_k_h_w_global_desc.Fold(I1, Number<K1>{}, Number<K2>{})
|
||||
.Fold(I0, Number<N1>{}, Number<N2>{});
|
||||
|
||||
// calculate origin of thread output tensor on global memory
|
||||
// blockwise GEMM c matrix starting index
|
||||
const auto c_thread_mtx_on_block =
|
||||
blockwise_gemm.GetBeginOfThreadMatrixC(get_thread_local_1d_id());
|
||||
|
||||
const index_t k_thread_data_on_global =
|
||||
k_block_data_on_global + c_thread_mtx_on_block.row;
|
||||
|
||||
const index_t b_thread_data_on_global =
|
||||
b_block_data_on_global + c_thread_mtx_on_block.col / N2;
|
||||
|
||||
// output merged global tensor descriptor, for calculating origin of thread tensor
|
||||
// in global memory
|
||||
constexpr auto out_k_n1_b_n2_global_merged_desc = make_ConstantMergedTensorDescriptor(
|
||||
out_n0_n1_n2_k0_k1_k2_h_w_global_mem_desc.Unfold(I3, I5),
|
||||
Sequence<3>{},
|
||||
Sequence<1>{},
|
||||
Sequence<0, 4, 5>{},
|
||||
Sequence<2>{});
|
||||
|
||||
// origin of dst in device memory
|
||||
Float* p_out_thread_on_global =
|
||||
p_out_global +
|
||||
out_k_n1_b_n2_global_merged_desc.GetOffsetFromMultiIndex(
|
||||
k_thread_data_on_global, 0, b_thread_data_on_global, 0);
|
||||
|
||||
threadwise_generic_tensor_slice_copy(out_n0_n1_n2_k0_k1_k2_h_w_thread_desc,
|
||||
p_out_thread,
|
||||
{0, 0, 0, 0, 0, 0, 0, 0},
|
||||
out_n0_n1_n2_k0_k1_k2_h_w_global_mem_desc,
|
||||
p_out_thread_on_global,
|
||||
{0, 0, 0, 0, 0, 0, 0, 0},
|
||||
out_n0_n1_n2_k0_k1_k2_h_w_thread_desc.GetLengths(),
|
||||
arithmetic_sequence_gen<0, 8, 1>::SeqType{});
|
||||
}
|
||||
}
|
||||
};
|
||||
Reference in New Issue
Block a user