Skip to content

GitLab

"example/12_reduce/reduce_example_common.hpp" did not exist on "6c3c06bf1f51d5a4b423634fc4cf48c0b7fe2599"
Unverified Commit 52c3fe05 authored by Chao Liu's avatar Chao Liu Committed by GitHub
Browse files

Refactor for MIOpen integration (#4) 

Refactor, so can bring multi-index transformation and padding support into MIOpen
parent 9aaeacc8
Show whitespace changes
Inline Side-by-side
Showing with 901 additions and 781 deletions
CMakeLists.txt
View file @ 52c3fe05
......@@ -47,14 +47,17 @@ include_directories(BEFORE
${PROJECT_SOURCE_DIR}/composable_kernel/include/tensor_description
${PROJECT_SOURCE_DIR}/composable_kernel/include/tensor_operation
${PROJECT_SOURCE_DIR}/composable_kernel/include/kernel_algorithm
${PROJECT_SOURCE_DIR}/external/include
${PROJECT_SOURCE_DIR}/driver/include
${PROJECT_BINARY_DIR}/composable_kernel/include/utility
)
if(DEVICE_BACKEND STREQUAL "AMD")
configure_file("${PROJECT_SOURCE_DIR}/composable_kernel/include/utility/config_amd.hpp.in" "${PROJECT_BINARY_DIR}/composable_kernel/include/utility/config.hpp")
configure_file("${PROJECT_SOURCE_DIR}/composable_kernel/include/utility/config.amd.hpp.in" "${PROJECT_BINARY_DIR}/composable_kernel/include/utility/config.hpp")
configure_file("${PROJECT_SOURCE_DIR}/composable_kernel/include/utility/float_type.amd.hpp.in" "${PROJECT_BINARY_DIR}/composable_kernel/include/utility/float_type.hpp")
elseif(DEVICE_BACKEND STREQUAL "NVIDIA")
configure_file("${PROJECT_SOURCE_DIR}/composable_kernel/include/utility/config_nvidia.hpp.in" "${PROJECT_BINARY_DIR}/composable_kernel/include/utility/config.hpp")
configure_file("${PROJECT_SOURCE_DIR}/composable_kernel/include/utility/config.nvidia.hpp.in" "${PROJECT_BINARY_DIR}/composable_kernel/include/utility/config.hpp")
configure_file("${PROJECT_SOURCE_DIR}/composable_kernel/include/utility/float_type.nvidia.hpp.in" "${PROJECT_BINARY_DIR}/composable_kernel/include/utility/float_type.hpp")
endif()
add_subdirectory(driver)
composable_kernel/include/kernel_algorithm/convolution_common.hpp 0 → 100644
View file @ 52c3fe05
#ifndef CK_CONVOLUTION_COMMON_HPP
#define CK_CONVOLUTION_COMMON_HPP
namespace ck {
enum ConvolutionDirection
{
Forward,
BackwardData,
BackwardWeight
};
} // namespace ck
#endif
composable_kernel/include/kernel_algorithm/gridwise_convolution_direct_v2_nchw_kcyx_nkhw.hpp
View file @ 52c3fe05
......@@ -2,7 +2,7 @@
#define CK_GRIDWISE_CONVOLUTION_DIRECT_V2_NCHW_KCYX_NKHW
#include "common_header.hpp"
#include "ConstantTensorDescriptor.hpp"
#include "ConstantTensorDescriptor_deprecated.hpp"
#include "blockwise_2d_tensor_op.hpp"
#include "blockwise_4d_tensor_op.hpp"
#include "threadwise_tensor_slice_copy.hpp"
......
composable_kernel/include/kernel_algorithm/gridwise_convolution_implicit_gemm_v1r1_chwn_cyxk_khwn.hpp
View file @ 52c3fe05
......@@ -2,7 +2,7 @@
#define CK_GRIDWISE_CONVOLUTION_IMPLICIT_GEMM_V1R1_CHWN_CYXK_KHWN
#include "common_header.hpp"
#include "ConstantTensorDescriptor.hpp"
#include "ConstantTensorDescriptor_deprecated.hpp"
#include "ConstantMatrixDescriptor.hpp"
#include "blockwise_4d_tensor_op.hpp"
#include "blockwise_2d_tensor_op.hpp"
......
composable_kernel/include/kernel_algorithm/gridwise_convolution_implicit_gemm_v1r2_chwn_cyxk_khwn.hpp
View file @ 52c3fe05
......@@ -2,7 +2,7 @@
#define CK_GRIDWISE_CONVOLUTION_IMPLICIT_GEMM_V1R2_CHWN_CYXK_KHWN
#include "common_header.hpp"
#include "ConstantTensorDescriptor.hpp"
#include "ConstantTensorDescriptor_deprecated.hpp"
#include "ConstantMatrixDescriptor.hpp"
#include "blockwise_2d_tensor_op.hpp"
#include "blockwise_3d_tensor_op.hpp"
......
composable_kernel/include/kernel_algorithm/gridwise_convolution_implicit_gemm_v1r3_chwn_cyxk_khwn.hpp
View file @ 52c3fe05
......@@ -2,7 +2,7 @@
#define CK_GRIDWISE_CONVOLUTION_IMPLICIT_GEMM_V1R3_CHWN_CYXK_KHWN_HPP
#include "common_header.hpp"
#include "ConstantTensorDescriptor.hpp"
#include "ConstantTensorDescriptor_deprecated.hpp"
#include "ConstantMatrixDescriptor.hpp"
#include "blockwise_generic_tensor_slice_copy.hpp"
#include "threadwise_generic_tensor_slice_copy.hpp"
......@@ -125,8 +125,8 @@ struct GridwiseConvolutionImplicitGemm_v1r3_chwn_cyxk_khwn
// blockwise copy
// input: format is [C, Hi, Wi, N]
auto blockwise_in_copy =
BlockwiseGenericTensorSliceCopy_v1<BlockSize,
auto blockwise_in_copy = BlockwiseGenericTensorSliceCopy_v1_deprecated<
BlockSize,
decltype(in_c_h_w_n_global_desc),
decltype(in_c_h_w_n_block_desc),
decltype(in_c_h_w_n_block_desc.GetLengths()),
......@@ -138,13 +138,12 @@ struct GridwiseConvolutionImplicitGemm_v1r3_chwn_cyxk_khwn
3,
3,
InBlockCopyDataPerAccess_N,
InBlockCopyDataPerAccess_N>({0, 0, 0, 0},
{0, 0, 0, 0});
InBlockCopyDataPerAccess_N>({0, 0, 0, 0}, {0, 0, 0, 0});
// blockwise wei copy
// format is [CPerBlock, X * KPerBlock]
const auto blockwise_wei_copy =
BlockwiseGenericTensorSliceCopy_v1<BlockSize,
BlockwiseGenericTensorSliceCopy_v1_deprecated<BlockSize,
decltype(wei_c_k_global_desc),
decltype(wei_c_k_block_desc),
decltype(wei_c_k_block_desc.GetLengths()),
......@@ -156,7 +155,8 @@ struct GridwiseConvolutionImplicitGemm_v1r3_chwn_cyxk_khwn
1,
1,
WeiBlockCopyDataPerAccess_K,
WeiBlockCopyDataPerAccess_K>({0, 0}, {0, 0});
WeiBlockCopyDataPerAccess_K>({0, 0},
{0, 0});
// a series of blockwise batched GEMM
// C_matrix += transpose(A_matrix) * B_matrix
......@@ -318,14 +318,15 @@ struct GridwiseConvolutionImplicitGemm_v1r3_chwn_cyxk_khwn
n_block_data_begin + n_thread_data_begin);
#if 1
ThreadwiseGenericTensorSliceCopy_v1r2<decltype(out_10d_thread_desc),
ThreadwiseGenericTensorSliceCopy_v1r2_deprecated<
decltype(out_10d_thread_desc),
decltype(out_10d_global_desc),
decltype(out_10d_thread_desc.GetLengths()),
arithmetic_sequence_gen<0, 10, 1>::type,
9,
OutThreadCopyDataPerAccess_N,
OutThreadCopyDataPerAccess_N>(
make_zero_array<index_t, 10>(), make_zero_array<index_t, 10>())
OutThreadCopyDataPerAccess_N>(make_zero_array<index_t, 10>(),
make_zero_array<index_t, 10>())
.Run(p_out_thread, p_out_thread_on_global);
#elif 0
ThreadwiseGenericTensorSliceCopy_v1r1<decltype(out_10d_thread_desc),
......@@ -388,14 +389,15 @@ struct GridwiseConvolutionImplicitGemm_v1r3_chwn_cyxk_khwn
n_block_data_begin + n_thread_data_begin);
#if 1
ThreadwiseGenericTensorSliceCopy_v1r2<decltype(out_10d_thread_desc),
ThreadwiseGenericTensorSliceCopy_v1r2_deprecated<
decltype(out_10d_thread_desc),
decltype(out_10d_global_desc),
decltype(out_10d_thread_desc.GetLengths()),
arithmetic_sequence_gen<0, 10, 1>::type,
9,
OutThreadCopyDataPerAccess_N,
OutThreadCopyDataPerAccess_N>(
make_zero_array<index_t, 10>(), make_zero_array<index_t, 10>())
OutThreadCopyDataPerAccess_N>(make_zero_array<index_t, 10>(),
make_zero_array<index_t, 10>())
.Run(p_out_thread, p_out_thread_on_global);
#elif 0
ThreadwiseGenericTensorSliceCopy_v1r1<decltype(out_10d_thread_desc),
......
composable_kernel/include/kernel_algorithm/gridwise_convolution_implicit_gemm_v1r3_chwn_cyxk_khwn_lds_double_buffer.hpp
View file @ 52c3fe05
......@@ -2,7 +2,7 @@
#define CK_GRIDWISE_CONVOLUTION_IMPLICIT_GEMM_V1R3_CHWN_CYXK_KHWN_LDS_DOUBLE_BUFFER_HPP
#include "common_header.hpp"
#include "ConstantTensorDescriptor.hpp"
#include "ConstantTensorDescriptor_deprecated.hpp"
#include "ConstantMatrixDescriptor.hpp"
#include "blockwise_generic_tensor_slice_copy.hpp"
#include "threadwise_generic_tensor_slice_copy.hpp"
......@@ -127,9 +127,9 @@ struct GridwiseConvolutionImplicitGemm_v1r3_chwn_cyxk_khwn_lds_double_buffer
// input: format is [C, Hi, Wi, N]
auto blockwise_in_copy =
#if 0
BlockwiseGenericTensorSliceCopy_v1
BlockwiseGenericTensorSliceCopy_v1_deprecated
#else
BlockwiseGenericTensorSliceCopy_v2
BlockwiseGenericTensorSliceCopy_v2_deprecated
#endif
<BlockSize,
decltype(in_c_h_w_n_global_desc),
......@@ -149,9 +149,9 @@ struct GridwiseConvolutionImplicitGemm_v1r3_chwn_cyxk_khwn_lds_double_buffer
// format is [CPerBlock, X * KPerBlock]
const auto blockwise_wei_copy =
#if 0
BlockwiseGenericTensorSliceCopy_v1
BlockwiseGenericTensorSliceCopy_v1_deprecated
#else
BlockwiseGenericTensorSliceCopy_v2
BlockwiseGenericTensorSliceCopy_v2_deprecated
#endif
<BlockSize,
decltype(wei_c_k_global_desc),
......@@ -406,14 +406,15 @@ struct GridwiseConvolutionImplicitGemm_v1r3_chwn_cyxk_khwn_lds_double_buffer
n_block_data_begin + n_thread_data_begin);
#if 1
ThreadwiseGenericTensorSliceCopy_v1r2<decltype(out_10d_thread_desc),
ThreadwiseGenericTensorSliceCopy_v1r2_deprecated<
decltype(out_10d_thread_desc),
decltype(out_10d_global_desc),
decltype(out_10d_thread_desc.GetLengths()),
arithmetic_sequence_gen<0, 10, 1>::type,
9,
OutThreadCopyDataPerAccess_N,
OutThreadCopyDataPerAccess_N>(
make_zero_array<index_t, 10>(), make_zero_array<index_t, 10>())
OutThreadCopyDataPerAccess_N>(make_zero_array<index_t, 10>(),
make_zero_array<index_t, 10>())
.Run(p_out_thread, p_out_thread_on_global);
#elif 0
ThreadwiseGenericTensorSliceCopy_v1r1<decltype(out_10d_thread_desc),
......@@ -476,14 +477,15 @@ struct GridwiseConvolutionImplicitGemm_v1r3_chwn_cyxk_khwn_lds_double_buffer
n_block_data_begin + n_thread_data_begin);
#if 1
ThreadwiseGenericTensorSliceCopy_v1r2<decltype(out_10d_thread_desc),
ThreadwiseGenericTensorSliceCopy_v1r2_deprecated<
decltype(out_10d_thread_desc),
decltype(out_10d_global_desc),
decltype(out_10d_thread_desc.GetLengths()),
arithmetic_sequence_gen<0, 10, 1>::type,
9,
OutThreadCopyDataPerAccess_N,
OutThreadCopyDataPerAccess_N>(
make_zero_array<index_t, 10>(), make_zero_array<index_t, 10>())
OutThreadCopyDataPerAccess_N>(make_zero_array<index_t, 10>(),
make_zero_array<index_t, 10>())
.Run(p_out_thread, p_out_thread_on_global);
#elif 0
ThreadwiseGenericTensorSliceCopy_v1r1<decltype(out_10d_thread_desc),
......
composable_kernel/include/kernel_algorithm/gridwise_convolution_implicit_gemm_v1r3_chwn_cyxk_khwn_padded.hpp
View file @ 52c3fe05
......@@ -2,7 +2,7 @@
#define CK_GRIDWISE_CONVOLUTION_IMPLICIT_GEMM_V1R3_CHWN_CYXK_KHWN_PADDED_HPP
#include "common_header.hpp"
#include "ConstantTensorDescriptor.hpp"
#include "ConstantTensorDescriptor_deprecated.hpp"
#include "ConstantMatrixDescriptor.hpp"
#include "tensor_descriptor.hpp"
#include "tensor_descriptor_helper.hpp"
......
composable_kernel/include/kernel_algorithm/gridwise_convolution_implicit_gemm_v1r3_nchw_cyxk_nkhw.hpp
View file @ 52c3fe05
......@@ -2,7 +2,7 @@
#define CK_GRIDWISE_CONVOLUTION_IMPLICIT_GEMM_V1R3_NCHW_CYXK_NKHW
#include "common_header.hpp"
#include "ConstantTensorDescriptor.hpp"
#include "ConstantTensorDescriptor_deprecated.hpp"
#include "ConstantMatrixDescriptor.hpp"
#include "blockwise_2d_tensor_op.hpp"
#include "blockwise_tensor_slice_copy.hpp"
......
composable_kernel/include/kernel_algorithm/gridwise_convolution_implicit_gemm_v1r3_nchw_cyxk_nkhw_lds_double_buffer.hpp
View file @ 52c3fe05
......@@ -2,7 +2,7 @@
#define CK_GRIDWISE_CONVOLUTION_IMPLICIT_GEMM_V1R3_NCHW_CYXK_NKHW_LDS_DOUBLE_BUFFER
#include "common_header.hpp"
#include "ConstantTensorDescriptor.hpp"
#include "ConstantTensorDescriptor_deprecated.hpp"
#include "ConstantMatrixDescriptor.hpp"
#include "blockwise_2d_tensor_op.hpp"
#include "blockwise_tensor_slice_copy.hpp"
......
composable_kernel/include/kernel_algorithm/gridwise_convolution_implicit_gemm_v2_chwn_cyxk_khwn.hpp
View file @ 52c3fe05
......@@ -2,7 +2,7 @@
#define CK_GRIDWISE_CONVOLUTION_IMPLICIT_GEMM_V2_CHWN_CYXK_KHWN
#include "common_header.hpp"
#include "ConstantTensorDescriptor.hpp"
#include "ConstantTensorDescriptor_deprecated.hpp"
#include "ConstantMatrixDescriptor.hpp"
#include "blockwise_4d_tensor_op.hpp"
#include "blockwise_2d_tensor_op.hpp"
......
composable_kernel/include/kernel_algorithm/gridwise_convolution_implicit_gemm_v2_chwn_cyxk_khwn_lds_double_buffer.hpp
View file @ 52c3fe05
......@@ -2,7 +2,7 @@
#define CK_GRIDWISE_CONVOLUTION_IMPLICIT_GEMM_V2_CHWN_CYXK_KHWN_LDS_DOUBLE_BUFFER
#include "common_header.hpp"
#include "ConstantTensorDescriptor.hpp"
#include "ConstantTensorDescriptor_deprecated.hpp"
#include "ConstantMatrixDescriptor.hpp"
#include "blockwise_4d_tensor_op.hpp"
#include "blockwise_2d_tensor_op.hpp"
......
composable_kernel/include/kernel_algorithm/gridwise_convolution_implicit_gemm_v3_nchw_cyxk_nkhw.hpp
View file @ 52c3fe05
......@@ -2,8 +2,8 @@
#define CK_GRIDWISE_CONVOLUTION_IMPLICIT_GEMM_V3_NCHW_CYXK_NKHW
#include "common_header.hpp"
#include "ConstantTensorDescriptor.hpp"
#include "ConstantMergedTensorDescriptor.hpp"
#include "ConstantTensorDescriptor_deprecated.hpp"
#include "ConstantMergedTensorDescriptor_deprecated.hpp"
#include "ConstantMatrixDescriptor.hpp"
#include "blockwise_generic_tensor_slice_copy.hpp"
#include "blockwise_gemm.hpp"
......@@ -128,7 +128,7 @@ struct GridwiseConvolutionImplicitGemm_v3_nchw_cyxk_nkhw
// input blockwise copy
// slice a merged tensor, reorder and copy to a normal tensor
// this copy operator already has blockwise offset built-in
auto blockwise_in_copy = BlockwiseGenericTensorSliceCopy_v1<
auto blockwise_in_copy = BlockwiseGenericTensorSliceCopy_v1_deprecated<
BlockSize,
Float,
decltype(in_c_n1_b_n2_global_merged_desc),
......@@ -155,8 +155,8 @@ struct GridwiseConvolutionImplicitGemm_v3_nchw_cyxk_nkhw
// operator for blockwise copy of weight into LDS
// slice a tensor, and copy it into another tensor
// this copy operator already have blockwise offset built-in
auto blockwise_wei_copy =
BlockwiseGenericTensorSliceCopy_v1<BlockSize,
auto blockwise_wei_copy = BlockwiseGenericTensorSliceCopy_v1_deprecated<
BlockSize,
Float,
decltype(wei_c_k_global_desc),
decltype(wei_c_k_block_desc),
......@@ -167,8 +167,7 @@ struct GridwiseConvolutionImplicitGemm_v3_nchw_cyxk_nkhw
Sequence<0, 1>, // src_access_order [C, K]
Sequence<0, 1>, // dst_access_order [C, K]
WeiBlockCopyDataPerAccess_K,
WeiBlockCopyDataPerAccess_K>(
{0, k_block_data_on_global}, {0, 0});
WeiBlockCopyDataPerAccess_K>({0, k_block_data_on_global}, {0, 0});
// GEMM definition
// c_mtx += transpose(a_mtx) * b_mtx
......
composable_kernel/include/kernel_algorithm/gridwise_convolution_implicit_gemm_v3_nchw_cyxk_nkhw_lds_double_buffer.hpp
View file @ 52c3fe05
......@@ -2,8 +2,8 @@
#define CK_GRIDWISE_CONVOLUTION_IMPLICIT_GEMM_V3_NCHW_CYXK_NKHW_LDS_DOUBLE_BUFFER
#include "common_header.hpp"
#include "ConstantTensorDescriptor.hpp"
#include "ConstantMergedTensorDescriptor.hpp"
#include "ConstantTensorDescriptor_deprecated.hpp"
#include "ConstantMergedTensorDescriptor_deprecated.hpp"
#include "ConstantMatrixDescriptor.hpp"
#include "blockwise_generic_tensor_slice_copy.hpp"
#include "blockwise_gemm.hpp"
......@@ -125,7 +125,7 @@ struct GridwiseConvolutionImplicitGemm_v3_nchw_cyxk_nkhw_lds_double_buffer
// input blockwise copy
// slice a merged tensor, reorder and copy to a normal tensor
// this copy operator already has blockwise offset built-in
const auto blockwise_in_copy = BlockwiseGenericTensorSliceCopy_v1<
const auto blockwise_in_copy = BlockwiseGenericTensorSliceCopy_v1_deprecated<
BlockSize,
Float,
decltype(in_c_n1_b_n2_global_merged_desc),
......@@ -152,8 +152,8 @@ struct GridwiseConvolutionImplicitGemm_v3_nchw_cyxk_nkhw_lds_double_buffer
// operator for blockwise copy of weight into LDS
// slice a tensor, and copy it into another tensor
// this copy operator already have blockwise offset built-in
const auto blockwise_wei_copy =
BlockwiseGenericTensorSliceCopy_v1<BlockSize,
const auto blockwise_wei_copy = BlockwiseGenericTensorSliceCopy_v1_deprecated<
BlockSize,
Float,
decltype(wei_c_k_global_desc),
decltype(wei_c_k_block_desc),
......@@ -164,8 +164,7 @@ struct GridwiseConvolutionImplicitGemm_v3_nchw_cyxk_nkhw_lds_double_buffer
Sequence<0, 1>, // src_access_order [C, K]
Sequence<0, 1>, // dst_access_order [C, K]
WeiBlockCopyDataPerAccess_K,
WeiBlockCopyDataPerAccess_K>(
{0, k_block_data_on_global}, {0, 0});
WeiBlockCopyDataPerAccess_K>({0, k_block_data_on_global}, {0, 0});
// GEMM definition
// c_mtx += transpose(a_mtx) * b_mtx
......
composable_kernel/include/kernel_algorithm/gridwise_convolution_implicit_gemm_v4r1_nchw_kcyx_nkhw_lds_double_buffer.hpp
View file @ 52c3fe05
......@@ -2,24 +2,71 @@
#define CK_GRIDWISE_CONVOLUTION_IMPLICIT_GEMM_V4R1_NCHW_KCYX_NKHW_LDS_DOUBLE_BUFFER_HPP
#include "common_header.hpp"
#include "ConstantTensorDescriptor.hpp"
#include "ConstantMergedTensorDescriptor.hpp"
#include "tensor_descriptor.hpp"
#include "tensor_descriptor_helper.hpp"
#include "ConstantMatrixDescriptor.hpp"
#include "blockwise_generic_tensor_slice_copy_deprecated.hpp"
#include "blockwise_generic_tensor_slice_copy.hpp"
#include "threadwise_generic_tensor_slice_copy.hpp"
#include "blockwise_gemm.hpp"
#include "threadwise_generic_tensor_slice_copy_deprecated.hpp"
#include "convolution_common.hpp"
namespace ck {
// define B = merge(N0, Ho, Wo)
template <ConvolutionDirection>
struct make_wei_e_k_global_desc_v4r1;
template <>
struct make_wei_e_k_global_desc_v4r1<ConvolutionDirection::Forward>
{
template <typename WeiDesc>
__device__ constexpr auto operator()(WeiDesc) const
{
constexpr auto I1 = Number<1>{};
constexpr auto I3 = Number<3>{};
return reorder_tensor_descriptor_given_upper2lower(
unfold_tensor_descriptor(WeiDesc{}, I1, I3), Sequence<1, 0>{});
}
};
template <>
struct make_wei_e_k_global_desc_v4r1<ConvolutionDirection::BackwardWeight>
{
template <typename WeiDesc>
__device__ constexpr auto operator()(WeiDesc) const
{
constexpr auto I0 = Number<0>{};
constexpr auto I1 = Number<1>{};
constexpr auto I2 = Number<2>{};
constexpr auto I3 = Number<3>{};
constexpr auto wei_k_c_y_x_global_desc = WeiDesc{};
constexpr index_t K = wei_k_c_y_x_global_desc.GetLength(I0);
constexpr index_t C = wei_k_c_y_x_global_desc.GetLength(I1);
constexpr index_t Y = wei_k_c_y_x_global_desc.GetLength(I2);
constexpr index_t X = wei_k_c_y_x_global_desc.GetLength(I3);
return transform_tensor_descriptor(
unfold_tensor_descriptor(wei_k_c_y_x_global_desc, I2, I3),
make_tuple(Merge<Sequence<C, Y * X>>{}, PassThrough<K>{}),
make_tuple(Sequence<1, 2>{}, Sequence<0>{}),
make_tuple(Sequence<0>{}, Sequence<1>{}));
}
};
template <index_t GridSize,
index_t BlockSize,
class Float,
class InGlobalDesc,
class WeiGlobalDesc,
class OutGlobalDesc,
class ConvStrides,
class ConvDilations,
typename Float,
typename AccDataType,
typename InGlobalDesc,
typename WeiGlobalDesc,
typename OutGlobalDesc,
typename ConvStrides,
typename ConvDilations,
typename LeftPads,
typename RightPads,
ConvolutionDirection ConvDirection,
index_t BPerBlock,
index_t KPerBlock,
index_t EPerBlock,
......@@ -33,18 +80,18 @@ template <index_t GridSize,
index_t GemmKPerThreadLoop,
index_t GemmDataPerReadA,
index_t GemmDataPerReadB,
class InBlockCopySubLengths_E_N1_B_N2,
class InBlockCopyClusterLengths_E_N1_B_N2,
class InBlockCopyThreadClusterArrangeOrder,
class InBlockCopySrcAccessOrder,
class InBlockCopyDstAccessOrder,
typename InBlockCopySubLengths_E_N1_B_N2,
typename InBlockCopyClusterLengths_E_N1_B_N2,
typename InBlockCopyThreadClusterArrangeOrder,
typename InBlockCopySrcAccessOrder,
typename InBlockCopyDstAccessOrder,
index_t InBlockCopySrcDataPerRead_B,
index_t InBlockCopyDstDataPerWrite_N2,
class WeiBlockCopySubLengths_E_K,
class WeiBlockCopyClusterLengths_E_K,
class WeiBlockCopyThreadClusterArrangeOrder,
class WeiBlockCopySrcAccessOrder,
class WeiBlockCopyDstAccessOrder,
typename WeiBlockCopySubLengths_E_K,
typename WeiBlockCopyClusterLengths_E_K,
typename WeiBlockCopyThreadClusterArrangeOrder,
typename WeiBlockCopySrcAccessOrder,
typename WeiBlockCopyDstAccessOrder,
index_t WeiBlockCopySrcDataPerRead_E,
index_t WeiBlockCopyDstDataPerWrite_K>
struct GridwiseConvolutionImplicitGemm_v4r1_nchw_kcyx_nkhw_lds_double_buffer
......@@ -53,6 +100,22 @@ struct GridwiseConvolutionImplicitGemm_v4r1_nchw_kcyx_nkhw_lds_double_buffer
const Float* const __restrict__ p_wei_global,
Float* const __restrict__ p_out_global) const
{
constexpr auto I0 = Number<0>{};
constexpr auto I1 = Number<1>{};
constexpr auto I2 = Number<2>{};
constexpr auto I3 = Number<3>{};
constexpr auto True = integral_constant<bool, true>{};
constexpr auto generic_address_space =
integral_constant<AddressSpace, AddressSpace::generic>{};
constexpr auto global_address_space =
integral_constant<AddressSpace, AddressSpace::global>{};
static_assert(ConvDirection == ConvolutionDirection::Forward ||
ConvDirection == ConvolutionDirection::BackwardWeight,
"wrong! this kernel only support convolution forward and backward-weight");
// this is a mess
// TODO: find more elegent way of specifying (or calculating) performance parameters
constexpr index_t N1 = GemmNRepeat;
......@@ -63,24 +126,18 @@ struct GridwiseConvolutionImplicitGemm_v4r1_nchw_kcyx_nkhw_lds_double_buffer
0,
"wrong!");
constexpr auto I0 = Number<0>{};
constexpr auto I1 = Number<1>{};
constexpr auto I2 = Number<2>{};
constexpr auto I3 = Number<3>{};
constexpr auto I5 = Number<5>{};
constexpr auto True = integral_constant<bool, true>{};
constexpr auto in_n_c_h_w_global_desc = InGlobalDesc{};
constexpr auto in_n_c_hi_wi_global_desc = InGlobalDesc{};
constexpr auto wei_k_c_y_x_global_desc = WeiGlobalDesc{};
constexpr auto out_n_k_h_w_global_desc = OutGlobalDesc{};
constexpr auto out_n_k_ho_wo_global_desc = OutGlobalDesc{};
constexpr index_t N = in_n_c_h_w_global_desc.GetLength(I0);
constexpr index_t C = in_n_c_h_w_global_desc.GetLength(I1);
constexpr index_t N = in_n_c_hi_wi_global_desc.GetLength(I0);
constexpr index_t C = in_n_c_hi_wi_global_desc.GetLength(I1);
constexpr index_t Hi = in_n_c_hi_wi_global_desc.GetLength(I2);
constexpr index_t Wi = in_n_c_hi_wi_global_desc.GetLength(I3);
constexpr index_t K = out_n_k_h_w_global_desc.GetLength(I1);
constexpr index_t Ho = out_n_k_h_w_global_desc.GetLength(I2);
constexpr index_t Wo = out_n_k_h_w_global_desc.GetLength(I3);
constexpr index_t K = out_n_k_ho_wo_global_desc.GetLength(I1);
constexpr index_t Ho = out_n_k_ho_wo_global_desc.GetLength(I2);
constexpr index_t Wo = out_n_k_ho_wo_global_desc.GetLength(I3);
constexpr index_t Y = wei_k_c_y_x_global_desc.GetLength(I2);
constexpr index_t X = wei_k_c_y_x_global_desc.GetLength(I3);
......@@ -106,46 +163,51 @@ struct GridwiseConvolutionImplicitGemm_v4r1_nchw_kcyx_nkhw_lds_double_buffer
"be violated");
// divide block work by [K, B]
static_assert(K % KPerBlock == 0 && B % BPerBlock == 0 && E % (2 * EPerBlock) == 0,
static_assert(K % KPerBlock == 0 && B % BPerBlock == 0 && E % EPerBlock == 0,
"wrong! cannot divide work evenly among block");
constexpr index_t KBlockWork = K / KPerBlock;
constexpr index_t BBlockWork = B / BPerBlock;
constexpr auto block_work_desc =
make_ConstantTensorDescriptor_packed(Sequence<KBlockWork, BBlockWork>{});
make_cluster_descriptor(Sequence<KBlockWork, BBlockWork>{});
const auto block_work_multi_id =
block_work_desc.GetMultiIndexFrom1dIndex(get_block_1d_id());
const auto block_work_id = block_work_desc.CalculateClusterIndex(get_block_1d_id());
const index_t k_block_data_on_global = block_work_multi_id[0] * KPerBlock;
const index_t b_block_data_on_global = block_work_multi_id[1] * BPerBlock;
const index_t k_block_data_on_global = block_work_id[0] * KPerBlock;
const index_t b_block_data_on_global = block_work_id[1] * BPerBlock;
// input tensor
// tensor descriptor in device memory [N0, N1, N2, Ho, Wo]
constexpr auto in_n0_n1_n2_h_w_global_desc =
in_n_c_h_w_global_desc.StridedSlice(I2, Number<Ho>{}, Number<ConvStrideH>{})
.StridedSlice(I3, Number<Wo>{}, Number<ConvStrideW>{})
.Fold(I0, Number<N1>{}, Number<N2>{})
.Extract(Sequence<0, 1, 2, 4, 5>{});
// batch descritpor for device memory
constexpr auto in_c_y_x_global_desc =
in_n_c_h_w_global_desc.StridedSlice(I2, Number<Y>{}, Number<ConvDilationH>{})
.StridedSlice(I3, Number<X>{}, Number<ConvDilationW>{})
.Extract(Sequence<1, 2, 3>{});
// merged tensor descriptor in device memory [E, N1, B, N2], src of blockwise copy
constexpr auto in_e_n1_b_n2_global_merged_desc = make_ConstantMergedTensorDescriptor(
in_c_y_x_global_desc.Embed(in_n0_n1_n2_h_w_global_desc),
Sequence<0, 1, 2>{},
Sequence<4>{},
Sequence<3, 6, 7>{},
Sequence<5>{});
// memory layout descriptor in LDS [E, N1, B, N2], dst of blockwise copy
// global tensor in global memory
constexpr auto in_n_c_hip_wip_global_desc = transform_tensor_descriptor(
in_n_c_hi_wi_global_desc,
make_tuple(
PassThrough<N>{}, PassThrough<C>{}, Pad<Sequence<Hi, Wi>, LeftPads, RightPads>{}),
make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2, 3>{}),
make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2, 3>{}));
constexpr auto in_n0_n1_n2_c_y_ho_x_wo_global_desc = transform_tensor_descriptor(
in_n_c_hip_wip_global_desc,
make_tuple(UnMerge<Sequence<N0, N1, N2>>{},
PassThrough<C>{},
Embed<Sequence<Y, Ho>, Sequence<ConvDilationH, ConvStrideH, 0>>{},
Embed<Sequence<X, Wo>, Sequence<ConvDilationW, ConvStrideW, 0>>{}),
make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}, Sequence<3>{}),
make_tuple(Sequence<0, 1, 2>{}, Sequence<3>{}, Sequence<4, 5>{}, Sequence<6, 7>{}));
// global tensor in global memory, src of blockwise copy
constexpr auto in_e_n1_b_n2_global_desc = transform_tensor_descriptor(
in_n0_n1_n2_c_y_ho_x_wo_global_desc,
make_tuple(Merge<Sequence<C, Y, X>>{},
PassThrough<N1>{},
Merge<Sequence<N0, Ho, Wo>>{},
PassThrough<N2>{}),
make_tuple(Sequence<3, 4, 6>{}, Sequence<1>{}, Sequence<0, 5, 7>{}, Sequence<2>{}),
make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}, Sequence<3>{}));
// block tensor in LDS memory, dst of blockwise copy
// be careful of LDS alignment
constexpr auto in_e_n1_b_n2_block_desc = make_ConstantTensorDescriptor_aligned(
constexpr auto in_e_n1_b_n2_block_desc = make_native_tensor_descriptor_aligned(
Sequence<EPerBlock, N1, BPerBlock, N2>{}, Number<InBlockCopyDstDataPerWrite_N2>{});
// this check is ad-hoc
......@@ -154,12 +216,10 @@ struct GridwiseConvolutionImplicitGemm_v4r1_nchw_kcyx_nkhw_lds_double_buffer
static_assert(in_e_n1_b_n2_block_desc.GetStride(I1) % GemmDataPerReadB == 0,
"GemmDataPerReadB alignment requirement is not satisfied");
// input blockwise copy
// slice a merged tensor, reorder and copy to a normal tensor
// this copy operator already has blockwise offset built-in
// input tensor blockwise copy
auto blockwise_in_copy =
BlockwiseGenericTensorSliceCopy_v2<BlockSize,
decltype(in_e_n1_b_n2_global_merged_desc),
BlockwiseGenericTensorSliceCopy_v4<BlockSize,
decltype(in_e_n1_b_n2_global_desc),
decltype(in_e_n1_b_n2_block_desc),
decltype(in_e_n1_b_n2_block_desc.GetLengths()),
InBlockCopySubLengths_E_N1_B_N2,
......@@ -174,21 +234,27 @@ struct GridwiseConvolutionImplicitGemm_v4r1_nchw_kcyx_nkhw_lds_double_buffer
{0, 0, b_block_data_on_global, 0}, {0, 0, 0, 0});
// weight tensor
// tensor descriptor in device memory, src of blockwise copy
// global tensor in global memory, src of blockwise copy
// It is constructed differently, depending on whether forward or backward weight
// convolution
constexpr auto wei_e_k_global_desc =
wei_k_c_y_x_global_desc.Unfold(I1, I3).ReorderGivenNew2Old(Sequence<1, 0>{});
make_wei_e_k_global_desc_v4r1<ConvDirection>{}(wei_k_c_y_x_global_desc);
// tensor descriptor in LDS, dst of blockwise copy
// block tensor in LDS memory, dst of blockwise copy
// be careful of LDS alignment
constexpr auto wei_e_k_block_desc = make_ConstantTensorDescriptor_aligned(
constexpr auto wei_e_k_block_desc = make_native_tensor_descriptor_aligned(
Sequence<EPerBlock, KPerBlock>{},
Number<math::lcm(WeiBlockCopyDstDataPerWrite_K, GemmDataPerReadA)>{});
// operator for blockwise copy of weight into LDS
// slice a tensor, and copy it into another tensor
// this copy operator already have blockwise offset built-in
// this check is ad-hoc
// TODO: need to properly implement tensor descriptor with multiple alignment
// requirements
static_assert(wei_e_k_block_desc.GetStride(I0) % GemmDataPerReadA == 0,
"GemmDataPerReadA alignment requirement is not satisfied");
// weight tensor blockwise copy
auto blockwise_wei_copy =
BlockwiseGenericTensorSliceCopy_v2<BlockSize,
BlockwiseGenericTensorSliceCopy_v4<BlockSize,
decltype(wei_e_k_global_desc),
decltype(wei_e_k_block_desc),
decltype(wei_e_k_block_desc.GetLengths()),
......@@ -211,8 +277,11 @@ struct GridwiseConvolutionImplicitGemm_v4r1_nchw_kcyx_nkhw_lds_double_buffer
// register
constexpr auto a_e_k_block_mtx_desc = make_ConstantMatrixDescriptor(wei_e_k_block_desc);
constexpr auto b_e_n1bn2_block_mtx_desc =
make_ConstantMatrixDescriptor(in_e_n1_b_n2_block_desc.Unfold(I1, I3));
constexpr auto b_e_n1bn2_block_mtx_desc = make_ConstantMatrixDescriptor(
in_e_n1_b_n2_block_desc.GetLength(I0),
in_e_n1_b_n2_block_desc.GetLength(I1) * in_e_n1_b_n2_block_desc.GetLength(I2) *
in_e_n1_b_n2_block_desc.GetLength(I3),
in_e_n1_b_n2_block_desc.GetStride(I0));
// sanity check
static_assert(KPerBlock % (GemmMPerThreadSubC * GemmMLevel0Cluster * GemmMLevel1Cluster) ==
......@@ -258,17 +327,17 @@ struct GridwiseConvolutionImplicitGemm_v4r1_nchw_kcyx_nkhw_lds_double_buffer
__shared__ Float p_wei_block_double[2 * wei_block_space];
// register allocation for output
Float p_out_thread[c_k0k1_n1n2_thread_mtx_desc.GetElementSpace()];
AccDataType p_out_thread[c_k0k1_n1n2_thread_mtx_desc.GetElementSpace()];
// zero out threadwise output
threadwise_matrix_set_zero(c_k0k1_n1n2_thread_mtx_desc, p_out_thread);
// LDS double buffer: preload data into LDS
{
blockwise_in_copy.template Run<Float, Float, address_space_t::global>(
p_in_global, p_in_block_double);
blockwise_wei_copy.template Run<Float, Float, address_space_t::global>(
p_wei_global, p_wei_block_double);
blockwise_in_copy.Run(
p_in_global, p_in_block_double, global_address_space, generic_address_space);
blockwise_wei_copy.Run(
p_wei_global, p_wei_block_double, global_address_space, generic_address_space);
}
// LDS double buffer: main body
......@@ -299,12 +368,10 @@ struct GridwiseConvolutionImplicitGemm_v4r1_nchw_kcyx_nkhw_lds_double_buffer
__syncthreads();
// LDS doubel buffer: load next data from device mem
blockwise_in_copy
.template RunLoadThreadBuffer<Float, Float, address_space_t::global>(
p_in_global, p_in_thread_buffer);
blockwise_wei_copy
.template RunLoadThreadBuffer<Float, Float, address_space_t::global>(
p_wei_global, p_wei_thread_buffer);
blockwise_in_copy.RunLoadThreadBuffer(
p_in_global, p_in_thread_buffer, global_address_space, generic_address_space);
blockwise_wei_copy.RunLoadThreadBuffer(
p_wei_global, p_wei_thread_buffer, global_address_space, generic_address_space);
// LDS double buffer: GEMM on current data
blockwise_gemm.Run(p_wei_block_now, p_in_block_now, p_out_thread);
......@@ -317,7 +384,10 @@ struct GridwiseConvolutionImplicitGemm_v4r1_nchw_kcyx_nkhw_lds_double_buffer
// LDS double buffer: tail
{
// even iteration
constexpr bool has_two_iteration_left = (E % (2 * EPerBlock) == 0);
if(has_two_iteration_left) // if has 2 iteration left
{
Float p_in_thread_buffer[blockwise_in_copy.GetThreadBufferSize()];
Float p_wei_thread_buffer[blockwise_wei_copy.GetThreadBufferSize()];
......@@ -326,51 +396,72 @@ struct GridwiseConvolutionImplicitGemm_v4r1_nchw_kcyx_nkhw_lds_double_buffer
__syncthreads();
// LDS doubel buffer: load next data from device mem
blockwise_in_copy.template RunLoadThreadBuffer<Float, Float, address_space_t::global>(
p_in_global, p_in_thread_buffer);
blockwise_wei_copy.template RunLoadThreadBuffer<Float, Float, address_space_t::global>(
p_wei_global, p_wei_thread_buffer);
// LDS double buffer: load last data from device mem
blockwise_in_copy.RunLoadThreadBuffer(
p_in_global, p_in_thread_buffer, global_address_space, generic_address_space);
blockwise_wei_copy.RunLoadThreadBuffer(
p_wei_global, p_wei_thread_buffer, global_address_space, generic_address_space);
// LDS double buffer: GEMM on current data
// LDS double buffer: GEMM on 2nd-last data
blockwise_gemm.Run(p_wei_block_double, p_in_block_double, p_out_thread);
// LDS double buffer: store next data to LDS
// LDS double buffer: store last data to LDS
blockwise_in_copy.RunStoreThreadBuffer(p_in_thread_buffer,
p_in_block_double + in_block_space);
blockwise_wei_copy.RunStoreThreadBuffer(p_wei_thread_buffer,
p_wei_block_double + wei_block_space);
// odd iteration
__syncthreads();
// LDS double buffer: GEMM on current data
// LDS double buffer: GEMM on last data
blockwise_gemm.Run(p_wei_block_double + wei_block_space,
p_in_block_double + in_block_space,
p_out_thread);
}
else // if has 1 iteration left
{
__syncthreads();
// LDS double buffer: GEMM on last data
blockwise_gemm.Run(p_wei_block_double, p_in_block_double, p_out_thread);
}
}
// copy output: register to global memory
{
constexpr index_t K1 = GemmMPerThreadSubC * GemmMLevel0Cluster * GemmMLevel1Cluster;
constexpr index_t K0 = K / K1;
// define tensor descriptor for threadwise copy
// output memory layout descriptor in register, src of threadwise copy
constexpr auto out_k0_k1_n1_b_n2_thread_mem_desc = make_ConstantTensorDescriptor_packed(
// define output tensor descriptor for threadwise copy
// thread output tensor, src of threadwise copy
constexpr auto out_k0_k1_n1_b_n2_thread_desc = make_native_tensor_descriptor_packed(
Sequence<GemmMRepeat, GemmMPerThreadSubC, N1, 1, N2>{});
// output memory layout descriptor in device memory
constexpr auto out_n0_n1_n2_k0_k1_h_w_global_mem_desc =
out_n_k_h_w_global_desc.Fold(I1, Number<K1>{}).Fold(I0, Number<N1>{}, Number<N2>{});
// output merged global tensor descriptor, dst of threadwise copy
constexpr auto out_k0_k1_n1_b_n2_global_merged_desc =
make_ConstantMergedTensorDescriptor(out_n0_n1_n2_k0_k1_h_w_global_mem_desc,
Sequence<3>{},
// global output tensor
constexpr auto out_n0_n1_n2_k0_k1_ho_wo_global_desc = transform_tensor_descriptor(
out_n_k_ho_wo_global_desc,
make_tuple(UnMerge<Sequence<N0, N1, N2>>{},
UnMerge<Sequence<K0, K1>>{},
PassThrough<Ho>{},
PassThrough<Wo>{}),
make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}, Sequence<3>{}),
make_tuple(Sequence<0, 1, 2>{}, Sequence<3, 4>{}, Sequence<5>{}, Sequence<6>{}));
// global output tensor, dst of threadwise copy
constexpr auto out_k0_k1_n1_b_n2_global_desc = transform_tensor_descriptor(
out_n0_n1_n2_k0_k1_ho_wo_global_desc,
make_tuple(PassThrough<K0>{},
PassThrough<K1>{},
PassThrough<N1>{},
Merge<Sequence<N0, Ho, Wo>>{},
PassThrough<N2>{}),
make_tuple(Sequence<3>{},
Sequence<4>{},
Sequence<1>{},
Sequence<0, 5, 6>{},
Sequence<2>{});
Sequence<2>{}),
make_tuple(
Sequence<0>{}, Sequence<1>{}, Sequence<2>{}, Sequence<3>{}, Sequence<4>{}));
// calculate origin of thread output tensor on global memory
// blockwise GEMM c matrix starting index
......@@ -383,14 +474,12 @@ struct GridwiseConvolutionImplicitGemm_v4r1_nchw_kcyx_nkhw_lds_double_buffer
const index_t b_thread_data_on_global =
b_block_data_on_global + c_thread_mtx_on_block.col / N2;
ThreadwiseGenericTensorSliceCopy_v2r1<
decltype(out_k0_k1_n1_b_n2_thread_mem_desc),
decltype(out_k0_k1_n1_b_n2_global_merged_desc),
decltype(out_k0_k1_n1_b_n2_thread_mem_desc.GetLengths()),
arithmetic_sequence_gen<0, 5, 1>::type,
ThreadwiseGenericTensorSliceCopy_v4r2<decltype(out_k0_k1_n1_b_n2_thread_desc),
decltype(out_k0_k1_n1_b_n2_global_desc),
decltype(
out_k0_k1_n1_b_n2_thread_desc.GetLengths()),
arithmetic_sequence_gen<0, 5, 1>::type,
3,
3,
1,
1>({0, 0, 0, 0, 0},
{k_thread_data_on_global / K1,
......@@ -398,11 +487,10 @@ struct GridwiseConvolutionImplicitGemm_v4r1_nchw_kcyx_nkhw_lds_double_buffer
0,
b_thread_data_on_global,
0})
.template Run<Float, Float, address_space_t::generic, address_space_t::global>(
p_out_thread, p_out_global);
.Run(p_out_thread, p_out_global, generic_address_space, global_address_space);
}
}
};
} // namespace ck
#endif // CK_GRIDWISE_CONVOLUTION_IMPLICIT_GEMM_V4R1_NCHW_KCYX_NKHW_LDS_DOUBLE_BUFFER_HPP
#endif
composable_kernel/include/kernel_algorithm/gridwise_convolution_implicit_gemm_v4r1_nchw_kcyx_nkhw_padded_lds_double_buffer.hpp → composable_kernel/include/kernel_algorithm/gridwise_convolution_implicit_gemm_v4r1_nchw_kcyx_nkhw_lds_double_buffer_deprecated.hpp
View file @ 52c3fe05
#ifndef CK_GRIDWISE_CONVOLUTION_IMPLICIT_GEMM_V4R1_NCHW_KCYX_NKHW_PADDED_LDS_DOUBLE_BUFFER_HPP
#define CK_GRIDWISE_CONVOLUTION_IMPLICIT_GEMM_V4R1_NCHW_KCYX_NKHW_PADDED_LDS_DOUBLE_BUFFER_HPP
#ifndef CK_GRIDWISE_CONVOLUTION_IMPLICIT_GEMM_V4R1_NCHW_KCYX_NKHW_LDS_DOUBLE_BUFFER_DEPRECATED_HPP
#define CK_GRIDWISE_CONVOLUTION_IMPLICIT_GEMM_V4R1_NCHW_KCYX_NKHW_LDS_DOUBLE_BUFFER_DEPRECATED_HPP
#include "common_header.hpp"
#include "tensor_descriptor.hpp"
#include "tensor_descriptor_helper.hpp"
#include "ConstantTensorDescriptor_deprecated.hpp"
#include "ConstantMergedTensorDescriptor_deprecated.hpp"
#include "ConstantMatrixDescriptor.hpp"
#include "blockwise_generic_tensor_slice_copy.hpp"
#include "threadwise_generic_tensor_slice_copy.hpp"
#include "blockwise_generic_tensor_slice_copy_deprecated.hpp"
#include "blockwise_gemm.hpp"
#include "threadwise_generic_tensor_slice_copy_deprecated.hpp"
#include "convolution_common.hpp"
namespace ck {
template <ConvolutionDirection>
struct make_wei_e_k_global_desc_v4r1_deprecated;
template <>
struct make_wei_e_k_global_desc_v4r1_deprecated<ConvolutionDirection::Forward>
{
template <typename WeiDesc>
__device__ constexpr auto operator()(WeiDesc) const
{
constexpr auto I1 = Number<1>{};
constexpr auto I3 = Number<3>{};
return WeiDesc::Unfold(I1, I3).ReorderGivenNew2Old(Sequence<1, 0>{});
}
};
template <>
struct make_wei_e_k_global_desc_v4r1_deprecated<ConvolutionDirection::BackwardWeight>
{
template <typename WeiDesc>
__device__ constexpr auto operator()(WeiDesc) const
{
constexpr auto I2 = Number<2>{};
constexpr auto I3 = Number<3>{};
return make_ConstantMergedTensorDescriptor(
WeiDesc::Unfold(I2, I3), Sequence<1, 2>{}, Sequence<0>{});
}
};
// define B = merge(N0, Ho, Wo)
template <index_t GridSize,
index_t BlockSize,
typename Float,
typename InGlobalDesc,
typename WeiGlobalDesc,
typename OutGlobalDesc,
typename ConvStrides,
typename ConvDilations,
typename LeftPads,
typename RightPads,
class Float,
class AccDataType,
class InGlobalDesc,
class WeiGlobalDesc,
class OutGlobalDesc,
class ConvStrides,
class ConvDilations,
ConvolutionDirection ConvDirection,
index_t BPerBlock,
index_t KPerBlock,
index_t EPerBlock,
......@@ -35,26 +66,42 @@ template <index_t GridSize,
index_t GemmKPerThreadLoop,
index_t GemmDataPerReadA,
index_t GemmDataPerReadB,
typename InBlockCopySubLengths_E_N1_B_N2,
typename InBlockCopyClusterLengths_E_N1_B_N2,
typename InBlockCopyThreadClusterArrangeOrder,
typename InBlockCopySrcAccessOrder,
typename InBlockCopyDstAccessOrder,
class InBlockCopySubLengths_E_N1_B_N2,
class InBlockCopyClusterLengths_E_N1_B_N2,
class InBlockCopyThreadClusterArrangeOrder,
class InBlockCopySrcAccessOrder,
class InBlockCopyDstAccessOrder,
index_t InBlockCopySrcDataPerRead_B,
index_t InBlockCopyDstDataPerWrite_N2,
typename WeiBlockCopySubLengths_E_K,
typename WeiBlockCopyClusterLengths_E_K,
typename WeiBlockCopyThreadClusterArrangeOrder,
typename WeiBlockCopySrcAccessOrder,
typename WeiBlockCopyDstAccessOrder,
class WeiBlockCopySubLengths_E_K,
class WeiBlockCopyClusterLengths_E_K,
class WeiBlockCopyThreadClusterArrangeOrder,
class WeiBlockCopySrcAccessOrder,
class WeiBlockCopyDstAccessOrder,
index_t WeiBlockCopySrcDataPerRead_E,
index_t WeiBlockCopyDstDataPerWrite_K>
struct GridwiseConvolutionImplicitGemm_v4r1_nchw_kcyx_nkhw_padded_lds_double_buffer
struct GridwiseConvolutionImplicitGemm_v4r1_nchw_kcyx_nkhw_lds_double_buffer_deprecated
{
__device__ void Run(const Float* const __restrict__ p_in_global,
const Float* const __restrict__ p_wei_global,
Float* const __restrict__ p_out_global) const
{
constexpr auto I0 = Number<0>{};
constexpr auto I1 = Number<1>{};
constexpr auto I2 = Number<2>{};
constexpr auto I3 = Number<3>{};
constexpr auto True = integral_constant<bool, true>{};
constexpr auto generic_address_space =
integral_constant<AddressSpace, AddressSpace::generic>{};
constexpr auto global_address_space =
integral_constant<AddressSpace, AddressSpace::global>{};
static_assert(ConvDirection == ConvolutionDirection::Forward ||
ConvDirection == ConvolutionDirection::BackwardWeight,
"wrong! this kernel only support convolution forward and backward-weight");
// this is a mess
// TODO: find more elegent way of specifying (or calculating) performance parameters
constexpr index_t N1 = GemmNRepeat;
......@@ -65,25 +112,16 @@ struct GridwiseConvolutionImplicitGemm_v4r1_nchw_kcyx_nkhw_padded_lds_double_buf
0,
"wrong!");
constexpr auto I0 = Number<0>{};
constexpr auto I1 = Number<1>{};
constexpr auto I2 = Number<2>{};
constexpr auto I3 = Number<3>{};
constexpr auto True = integral_constant<bool, true>{};
constexpr auto in_n_c_hi_wi_global_desc = InGlobalDesc{};
constexpr auto in_n_c_h_w_global_desc = InGlobalDesc{};
constexpr auto wei_k_c_y_x_global_desc = WeiGlobalDesc{};
constexpr auto out_n_k_ho_wo_global_desc = OutGlobalDesc{};
constexpr auto out_n_k_h_w_global_desc = OutGlobalDesc{};
constexpr index_t N = in_n_c_hi_wi_global_desc.GetLength(I0);
constexpr index_t C = in_n_c_hi_wi_global_desc.GetLength(I1);
constexpr index_t Hi = in_n_c_hi_wi_global_desc.GetLength(I2);
constexpr index_t Wi = in_n_c_hi_wi_global_desc.GetLength(I3);
constexpr index_t N = in_n_c_h_w_global_desc.GetLength(I0);
constexpr index_t C = in_n_c_h_w_global_desc.GetLength(I1);
constexpr index_t K = out_n_k_ho_wo_global_desc.GetLength(I1);
constexpr index_t Ho = out_n_k_ho_wo_global_desc.GetLength(I2);
constexpr index_t Wo = out_n_k_ho_wo_global_desc.GetLength(I3);
constexpr index_t K = out_n_k_h_w_global_desc.GetLength(I1);
constexpr index_t Ho = out_n_k_h_w_global_desc.GetLength(I2);
constexpr index_t Wo = out_n_k_h_w_global_desc.GetLength(I3);
constexpr index_t Y = wei_k_c_y_x_global_desc.GetLength(I2);
constexpr index_t X = wei_k_c_y_x_global_desc.GetLength(I3);
......@@ -116,43 +154,39 @@ struct GridwiseConvolutionImplicitGemm_v4r1_nchw_kcyx_nkhw_padded_lds_double_buf
constexpr index_t BBlockWork = B / BPerBlock;
constexpr auto block_work_desc =
make_cluster_descriptor(Sequence<KBlockWork, BBlockWork>{});
make_ConstantTensorDescriptor_packed(Sequence<KBlockWork, BBlockWork>{});
const auto block_work_id = block_work_desc.CalculateClusterIndex(get_block_1d_id());
const auto block_work_multi_id =
block_work_desc.GetMultiIndexFrom1dIndex(get_block_1d_id());
const index_t k_block_data_on_global = block_work_id[0] * KPerBlock;
const index_t b_block_data_on_global = block_work_id[1] * BPerBlock;
const index_t k_block_data_on_global = block_work_multi_id[0] * KPerBlock;
const index_t b_block_data_on_global = block_work_multi_id[1] * BPerBlock;
// input tensor
// global memory
constexpr auto in_n_c_hip_wip_global_desc = transform_tensor_descriptor(
in_n_c_hi_wi_global_desc,
make_tuple(
PassThrough<N>{}, PassThrough<C>{}, Pad<Sequence<Hi, Wi>, LeftPads, RightPads>{}),
make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2, 3>{}),
make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2, 3>{}));
constexpr auto in_n0_n1_n2_c_y_ho_x_wo_global_desc = transform_tensor_descriptor(
in_n_c_hip_wip_global_desc,
make_tuple(UnMerge<Sequence<N0, N1, N2>>{},
PassThrough<C>{},
Embed<Sequence<Y, Ho>, Sequence<ConvDilationH, ConvStrideH, 0>>{},
Embed<Sequence<X, Wo>, Sequence<ConvDilationW, ConvStrideW, 0>>{}),
make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}, Sequence<3>{}),
make_tuple(Sequence<0, 1, 2>{}, Sequence<3>{}, Sequence<4, 5>{}, Sequence<6, 7>{}));
constexpr auto in_e_n1_b_n2_global_desc = transform_tensor_descriptor(
in_n0_n1_n2_c_y_ho_x_wo_global_desc,
make_tuple(Merge<Sequence<C, Y, X>>{},
PassThrough<N1>{},
Merge<Sequence<N0, Ho, Wo>>{},
PassThrough<N2>{}),
make_tuple(Sequence<3, 4, 6>{}, Sequence<1>{}, Sequence<0, 5, 7>{}, Sequence<2>{}),
make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}, Sequence<3>{}));
// tensor descriptor in device memory [N0, N1, N2, Ho, Wo]
constexpr auto in_n0_n1_n2_h_w_global_desc =
in_n_c_h_w_global_desc.StridedSlice(I2, Number<Ho>{}, Number<ConvStrideH>{})
.StridedSlice(I3, Number<Wo>{}, Number<ConvStrideW>{})
.Fold(I0, Number<N1>{}, Number<N2>{})
.Extract(Sequence<0, 1, 2, 4, 5>{});
// batch descritpor for device memory
constexpr auto in_c_y_x_global_desc =
in_n_c_h_w_global_desc.StridedSlice(I2, Number<Y>{}, Number<ConvDilationH>{})
.StridedSlice(I3, Number<X>{}, Number<ConvDilationW>{})
.Extract(Sequence<1, 2, 3>{});
// merged tensor descriptor in device memory [E, N1, B, N2], src of blockwise copy
constexpr auto in_e_n1_b_n2_global_merged_desc = make_ConstantMergedTensorDescriptor(
in_c_y_x_global_desc.Embed(in_n0_n1_n2_h_w_global_desc),
Sequence<0, 1, 2>{},
Sequence<4>{},
Sequence<3, 6, 7>{},
Sequence<5>{});
// memory layout descriptor in LDS [E, N1, B, N2], dst of blockwise copy
// be careful of LDS alignment
constexpr auto in_e_n1_b_n2_block_desc = make_native_tensor_descriptor_aligned(
constexpr auto in_e_n1_b_n2_block_desc = make_ConstantTensorDescriptor_aligned(
Sequence<EPerBlock, N1, BPerBlock, N2>{}, Number<InBlockCopyDstDataPerWrite_N2>{});
// this check is ad-hoc
......@@ -164,9 +198,9 @@ struct GridwiseConvolutionImplicitGemm_v4r1_nchw_kcyx_nkhw_padded_lds_double_buf
// input blockwise copy
// slice a merged tensor, reorder and copy to a normal tensor
// this copy operator already has blockwise offset built-in
auto blockwise_in_copy =
BlockwiseGenericTensorSliceCopy_v4<BlockSize,
decltype(in_e_n1_b_n2_global_desc),
auto blockwise_in_copy = BlockwiseGenericTensorSliceCopy_v2_deprecated<
BlockSize,
decltype(in_e_n1_b_n2_global_merged_desc),
decltype(in_e_n1_b_n2_block_desc),
decltype(in_e_n1_b_n2_block_desc.GetLengths()),
InBlockCopySubLengths_E_N1_B_N2,
......@@ -177,31 +211,26 @@ struct GridwiseConvolutionImplicitGemm_v4r1_nchw_kcyx_nkhw_padded_lds_double_buf
2,
3,
InBlockCopySrcDataPerRead_B,
InBlockCopyDstDataPerWrite_N2>(
{0, 0, b_block_data_on_global, 0}, {0, 0, 0, 0});
InBlockCopyDstDataPerWrite_N2>({0, 0, b_block_data_on_global, 0}, {0, 0, 0, 0});
// weight tensor
// tensor descriptor in device memory, src of blockwise copy
constexpr auto wei_e_k_global_desc = reorder_tensor_descriptor_given_upper2lower(
unfold_tensor_descriptor(wei_k_c_y_x_global_desc, I1, I3), Sequence<1, 0>{});
// Iensor descriptor in device memory, src of blockwise copy
// It is constructed differently, depending on whether forward or backward weight
// convolution
constexpr auto wei_e_k_global_desc =
make_wei_e_k_global_desc_v4r1_deprecated<ConvDirection>{}(wei_k_c_y_x_global_desc);
// tensor descriptor in LDS, dst of blockwise copy
// be careful of LDS alignment
constexpr auto wei_e_k_block_desc = make_native_tensor_descriptor_aligned(
constexpr auto wei_e_k_block_desc = make_ConstantTensorDescriptor_aligned(
Sequence<EPerBlock, KPerBlock>{},
Number<math::lcm(WeiBlockCopyDstDataPerWrite_K, GemmDataPerReadA)>{});
// this check is ad-hoc
// TODO: need to properly implement tensor descriptor with multiple alignment
// requirements
static_assert(wei_e_k_block_desc.GetStride(I0) % GemmDataPerReadA == 0,
"GemmDataPerReadA alignment requirement is not satisfied");
// operator for blockwise copy of weight into LDS
// slice a tensor, and copy it into another tensor
// this copy operator already have blockwise offset built-in
auto blockwise_wei_copy =
BlockwiseGenericTensorSliceCopy_v4<BlockSize,
BlockwiseGenericTensorSliceCopy_v2_deprecated<BlockSize,
decltype(wei_e_k_global_desc),
decltype(wei_e_k_block_desc),
decltype(wei_e_k_block_desc.GetLengths()),
......@@ -224,11 +253,8 @@ struct GridwiseConvolutionImplicitGemm_v4r1_nchw_kcyx_nkhw_padded_lds_double_buf
// register
constexpr auto a_e_k_block_mtx_desc = make_ConstantMatrixDescriptor(wei_e_k_block_desc);
constexpr auto b_e_n1bn2_block_mtx_desc = make_ConstantMatrixDescriptor(
in_e_n1_b_n2_block_desc.GetLength(I0),
in_e_n1_b_n2_block_desc.GetLength(I1) * in_e_n1_b_n2_block_desc.GetLength(I2) *
in_e_n1_b_n2_block_desc.GetLength(I3),
in_e_n1_b_n2_block_desc.GetStride(I0));
constexpr auto b_e_n1bn2_block_mtx_desc =
make_ConstantMatrixDescriptor(in_e_n1_b_n2_block_desc.Unfold(I1, I3));
// sanity check
static_assert(KPerBlock % (GemmMPerThreadSubC * GemmMLevel0Cluster * GemmMLevel1Cluster) ==
......@@ -240,14 +266,14 @@ struct GridwiseConvolutionImplicitGemm_v4r1_nchw_kcyx_nkhw_padded_lds_double_buf
// c_thread_mtx definition: this is a mess
// TODO:: more elegent way of defining c_thread_mtx
constexpr auto c_k0k2_n1n2_thread_mtx_desc = make_ConstantMatrixDescriptor_packed(
Number<GemmMRepeat * GemmMPerThreadSubC>{}, Number<N1 * N2>{});
constexpr auto c_k0k1_n1n2_thread_mtx_desc = make_ConstantMatrixDescriptor_packed(
Number<GemmMRepeat * GemmMPerThreadSubC>{}, Number<GemmNRepeat * GemmNPerThreadSubC>{});
const auto blockwise_gemm = BlockwiseGemmBlockABlockBThreadCTransANormalBNormalC_v2<
BlockSize,
decltype(a_e_k_block_mtx_desc),
decltype(b_e_n1bn2_block_mtx_desc),
decltype(c_k0k2_n1n2_thread_mtx_desc),
decltype(c_k0k1_n1n2_thread_mtx_desc),
GemmMPerThreadSubC,
GemmNPerThreadSubC,
GemmMLevel0Cluster,
......@@ -274,17 +300,17 @@ struct GridwiseConvolutionImplicitGemm_v4r1_nchw_kcyx_nkhw_padded_lds_double_buf
__shared__ Float p_wei_block_double[2 * wei_block_space];
// register allocation for output
Float p_out_thread[c_k0k2_n1n2_thread_mtx_desc.GetElementSpace()];
AccDataType p_out_thread[c_k0k1_n1n2_thread_mtx_desc.GetElementSpace()];
// zero out threadwise output
threadwise_matrix_set_zero(c_k0k2_n1n2_thread_mtx_desc, p_out_thread);
threadwise_matrix_set_zero(c_k0k1_n1n2_thread_mtx_desc, p_out_thread);
// LDS double buffer: preload data into LDS
{
blockwise_in_copy.template Run<Float, Float, address_space_t::global>(
p_in_global, p_in_block_double);
blockwise_wei_copy.template Run<Float, Float, address_space_t::global>(
p_wei_global, p_wei_block_double);
blockwise_in_copy.Run(
p_in_global, p_in_block_double, global_address_space, generic_address_space);
blockwise_wei_copy.Run(
p_wei_global, p_wei_block_double, global_address_space, generic_address_space);
}
// LDS double buffer: main body
......@@ -315,12 +341,10 @@ struct GridwiseConvolutionImplicitGemm_v4r1_nchw_kcyx_nkhw_padded_lds_double_buf
__syncthreads();
// LDS doubel buffer: load next data from device mem
blockwise_in_copy
.template RunLoadThreadBuffer<Float, Float, address_space_t::global>(
p_in_global, p_in_thread_buffer);
blockwise_wei_copy
.template RunLoadThreadBuffer<Float, Float, address_space_t::global>(
p_wei_global, p_wei_thread_buffer);
blockwise_in_copy.RunLoadThreadBuffer(
p_in_global, p_in_thread_buffer, global_address_space, generic_address_space);
blockwise_wei_copy.RunLoadThreadBuffer(
p_wei_global, p_wei_thread_buffer, global_address_space, generic_address_space);
// LDS double buffer: GEMM on current data
blockwise_gemm.Run(p_wei_block_now, p_in_block_now, p_out_thread);
......@@ -343,10 +367,10 @@ struct GridwiseConvolutionImplicitGemm_v4r1_nchw_kcyx_nkhw_padded_lds_double_buf
__syncthreads();
// LDS doubel buffer: load next data from device mem
blockwise_in_copy.template RunLoadThreadBuffer<Float, Float, address_space_t::global>(
p_in_global, p_in_thread_buffer);
blockwise_wei_copy.template RunLoadThreadBuffer<Float, Float, address_space_t::global>(
p_wei_global, p_wei_thread_buffer);
blockwise_in_copy.RunLoadThreadBuffer(
p_in_global, p_in_thread_buffer, global_address_space, generic_address_space);
blockwise_wei_copy.RunLoadThreadBuffer(
p_wei_global, p_wei_thread_buffer, global_address_space, generic_address_space);
// LDS double buffer: GEMM on current data
blockwise_gemm.Run(p_wei_block_double, p_in_block_double, p_out_thread);
......@@ -369,38 +393,24 @@ struct GridwiseConvolutionImplicitGemm_v4r1_nchw_kcyx_nkhw_padded_lds_double_buf
// copy output: register to global memory
{
constexpr index_t K1 = GemmMPerThreadSubC * GemmMLevel0Cluster * GemmMLevel1Cluster;
constexpr index_t K0 = K / K1;
// define tensor descriptor for threadwise copy
// output memory layout descriptor in register, src of threadwise copy
constexpr auto out_k0_k1_n1_b_n2_thread_desc = make_native_tensor_descriptor_packed(
constexpr auto out_k0_k1_n1_b_n2_thread_mem_desc = make_ConstantTensorDescriptor_packed(
Sequence<GemmMRepeat, GemmMPerThreadSubC, N1, 1, N2>{});
// output memory layout descriptor in device memory
constexpr auto out_n0_n1_n2_k0_k1_ho_wo_global_desc = transform_tensor_descriptor(
out_n_k_ho_wo_global_desc,
make_tuple(UnMerge<Sequence<N0, N1, N2>>{},
UnMerge<Sequence<K0, K1>>{},
PassThrough<Ho>{},
PassThrough<Wo>{}),
make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}, Sequence<3>{}),
make_tuple(Sequence<0, 1, 2>{}, Sequence<3, 4>{}, Sequence<5>{}, Sequence<6>{}));
constexpr auto out_n0_n1_n2_k0_k1_h_w_global_mem_desc =
out_n_k_h_w_global_desc.Fold(I1, Number<K1>{}).Fold(I0, Number<N1>{}, Number<N2>{});
// output merged global tensor descriptor, dst of threadwise copy
constexpr auto out_k0_k1_n1_b_n2_global_desc = transform_tensor_descriptor(
out_n0_n1_n2_k0_k1_ho_wo_global_desc,
make_tuple(PassThrough<K0>{},
PassThrough<K1>{},
PassThrough<N1>{},
Merge<Sequence<N0, Ho, Wo>>{},
PassThrough<N2>{}),
make_tuple(Sequence<3>{},
constexpr auto out_k0_k1_n1_b_n2_global_merged_desc =
make_ConstantMergedTensorDescriptor(out_n0_n1_n2_k0_k1_h_w_global_mem_desc,
Sequence<3>{},
Sequence<4>{},
Sequence<1>{},
Sequence<0, 5, 6>{},
Sequence<2>{}),
make_tuple(
Sequence<0>{}, Sequence<1>{}, Sequence<2>{}, Sequence<3>{}, Sequence<4>{}));
Sequence<2>{});
// calculate origin of thread output tensor on global memory
// blockwise GEMM c matrix starting index
......@@ -413,11 +423,13 @@ struct GridwiseConvolutionImplicitGemm_v4r1_nchw_kcyx_nkhw_padded_lds_double_buf
const index_t b_thread_data_on_global =
b_block_data_on_global + c_thread_mtx_on_block.col / N2;
ThreadwiseGenericTensorSliceCopy_v4r2<decltype(out_k0_k1_n1_b_n2_thread_desc),
decltype(out_k0_k1_n1_b_n2_global_desc),
decltype(
out_k0_k1_n1_b_n2_thread_desc.GetLengths()),
ThreadwiseGenericTensorSliceCopy_v2r1_deprecated<
decltype(out_k0_k1_n1_b_n2_thread_mem_desc),
decltype(out_k0_k1_n1_b_n2_global_merged_desc),
decltype(out_k0_k1_n1_b_n2_thread_mem_desc.GetLengths()),
arithmetic_sequence_gen<0, 5, 1>::type,
arithmetic_sequence_gen<0, 5, 1>::type,
3,
3,
1,
1>({0, 0, 0, 0, 0},
......@@ -426,18 +438,10 @@ struct GridwiseConvolutionImplicitGemm_v4r1_nchw_kcyx_nkhw_padded_lds_double_buf
0,
b_thread_data_on_global,
0})
#if 1
.template Run<Float, Float, address_space_t::generic, address_space_t::global>
#else // tweaking
.template Run_optimized_dst_address_calculation<Float,
Float,
address_space_t::generic,
address_space_t::global>
#endif
(p_out_thread, p_out_global);
.Run(p_out_thread, p_out_global, generic_address_space, global_address_space);
}
}
};
} // namespace ck
#endif
#endif // CK_GRIDWISE_CONVOLUTION_IMPLICIT_GEMM_V4_NCHW_KCYX_NKHW_LDS_DOUBLE_BUFFER_DEPRECATED_HPP
composable_kernel/include/kernel_algorithm/gridwise_convolution_implicit_gemm_v4r2_nchw_kcyx_nkhw_lds_double_buffer.hpp
View file @ 52c3fe05
......@@ -2,8 +2,8 @@
#define CK_GRIDWISE_CONVOLUTION_IMPLICIT_GEMM_V4R2_NCHW_KCYX_NKHW_LDS_DOUBLE_BUFFER
#include "common_header.hpp"
#include "ConstantTensorDescriptor.hpp"
#include "ConstantMergedTensorDescriptor.hpp"
#include "ConstantTensorDescriptor_deprecated.hpp"
#include "ConstantMergedTensorDescriptor_deprecated.hpp"
#include "ConstantMatrixDescriptor.hpp"
#include "blockwise_generic_tensor_slice_copy.hpp"
#include "blockwise_gemm.hpp"
......@@ -166,7 +166,7 @@ struct GridwiseConvolutionImplicitGemm_v4r2_nchw_kcyx_nkhw_lds_double_buffer
// input blockwise copy
// slice a merged tensor, reorder and copy to a normal tensor
// this copy operator already has blockwise offset built-in
auto blockwise_in_copy = BlockwiseGenericTensorSliceCopy_v1<
auto blockwise_in_copy = BlockwiseGenericTensorSliceCopy_v1_deprecated<
BlockSize,
Float,
decltype(in_e_n0_ho0_wo0_b_n2_ho2_wo2_global_merged_desc),
......@@ -196,7 +196,7 @@ struct GridwiseConvolutionImplicitGemm_v4r2_nchw_kcyx_nkhw_lds_double_buffer
// slice a tensor, and copy it into another tensor
// this copy operator already have blockwise offset built-in
auto blockwise_wei_copy =
BlockwiseGenericTensorSliceCopy_v1<BlockSize,
BlockwiseGenericTensorSliceCopy_v1_deprecated<BlockSize,
Float,
decltype(wei_e_k_global_desc),
decltype(wei_e_k_block_desc),
......
composable_kernel/include/kernel_algorithm/gridwise_convolution_implicit_gemm_v4r3_nchw_kcyx_nkhw_lds_double_buffer.hpp
View file @ 52c3fe05
......@@ -2,8 +2,8 @@
#define CK_GRIDWISE_CONVOLUTION_IMPLICIT_GEMM_V4R3_NCHW_KCYX_NKHW_LDS_DOUBLE_BUFFER
#include "common_header.hpp"
#include "ConstantTensorDescriptor.hpp"
#include "ConstantMergedTensorDescriptor.hpp"
#include "ConstantTensorDescriptor_deprecated.hpp"
#include "ConstantMergedTensorDescriptor_deprecated.hpp"
#include "ConstantMatrixDescriptor.hpp"
#include "blockwise_generic_tensor_slice_copy.hpp"
#include "blockwise_gemm.hpp"
......@@ -165,7 +165,7 @@ struct GridwiseConvolutionImplicitGemm_v4r3_nchw_kcyx_nkhw_lds_double_buffer
// input blockwise copy
// slice a merged tensor, reorder and copy to a normal tensor
// this copy operator already has blockwise offset built-in
auto blockwise_in_copy = BlockwiseGenericTensorSliceCopy_v1<
auto blockwise_in_copy = BlockwiseGenericTensorSliceCopy_v1_deprecated<
BlockSize,
Float,
decltype(in_e_n1_ho1_wo1_b_n2_ho2_wo2_global_merged_desc),
......@@ -195,7 +195,7 @@ struct GridwiseConvolutionImplicitGemm_v4r3_nchw_kcyx_nkhw_lds_double_buffer
// slice a tensor, and copy it into another tensor
// this copy operator already have blockwise offset built-in
auto blockwise_wei_copy =
BlockwiseGenericTensorSliceCopy_v1<BlockSize,
BlockwiseGenericTensorSliceCopy_v1_deprecated<BlockSize,
Float,
decltype(wei_e_k_global_desc),
decltype(wei_e_k_block_desc),
......
composable_kernel/include/kernel_algorithm/gridwise_convolution_implicit_gemm_v4r4_nchw_kcyx_nkhw_lds_double_buffer.hpp
View file @ 52c3fe05
#ifndef CK_GRIDWISE_CONVOLUTION_IMPLICIT_GEMM_V4R4_NCHW_KCYX_NKHW_HPP_LDS_DOUBLE_BUFFER_HPP
#define CK_GRIDWISE_CONVOLUTION_IMPLICIT_GEMM_V4R4_NCHW_KCYX_NKHW_HPP_LDS_DOUBLE_BUFFER_HPP
#ifndef CK_GRIDWISE_CONVOLUTION_IMPLICIT_GEMM_V4R4_NCHW_KCYX_NKHW_LDS_DOUBLE_BUFFER_HPP
#define CK_GRIDWISE_CONVOLUTION_IMPLICIT_GEMM_V4R4_NCHW_KCYX_NKHW_LDS_DOUBLE_BUFFER_HPP
#include "common_header.hpp"
#include "ConstantTensorDescriptor.hpp"
#include "ConstantMergedTensorDescriptor.hpp"
#include "tensor_descriptor.hpp"
#include "tensor_descriptor_helper.hpp"
#include "ConstantMatrixDescriptor.hpp"
#include "blockwise_generic_tensor_slice_copy_deprecated.hpp"
#include "blockwise_generic_tensor_slice_copy.hpp"
#include "threadwise_generic_tensor_slice_copy.hpp"
#include "blockwise_gemm.hpp"
#include "threadwise_generic_tensor_slice_copy_deprecated.hpp"
namespace ck {
// B = merge(N, Ho, Wo)
template <index_t GridSize,
index_t BlockSize,
class Float,
class InGlobalDesc,
class WeiGlobalDesc,
class OutGlobalDesc,
class ConvStrides,
class ConvDilations,
typename Float,
typename InGlobalDesc,
typename WeiGlobalDesc,
typename OutGlobalDesc,
typename ConvStrides,
typename ConvDilations,
typename LeftPads,
typename RightPads,
index_t BPerBlock,
index_t KPerBlock,
index_t EPerBlock,
......@@ -32,17 +34,17 @@ template <index_t GridSize,
index_t GemmKPerThreadLoop,
index_t GemmDataPerReadA,
index_t GemmDataPerReadB,
class InBlockCopySubLengths_E_B,
class InBlockCopyClusterLengths_E_B,
class InBlockCopyThreadClusterArrangeOrder,
class InBlockCopySrcAccessOrder,
class InBlockCopyDstAccessOrder,
typename InBlockCopySubLengths_E_B,
typename InBlockCopyClusterLengths_E_B,
typename InBlockCopyThreadClusterArrangeOrder,
typename InBlockCopySrcAccessOrder,
typename InBlockCopyDstAccessOrder,
index_t InBlockCopyDataPerAccess_B,
class WeiBlockCopySubLengths_E_K,
class WeiBlockCopyClusterLengths_E_K,
class WeiBlockCopyThreadClusterArrangeOrder,
class WeiBlockCopySrcAccessOrder,
class WeiBlockCopyDstAccessOrder,
typename WeiBlockCopySubLengths_E_K,
typename WeiBlockCopyClusterLengths_E_K,
typename WeiBlockCopyThreadClusterArrangeOrder,
typename WeiBlockCopySrcAccessOrder,
typename WeiBlockCopyDstAccessOrder,
index_t WeiBlockCopySrcDataPerRead_E,
index_t WeiBlockCopyDstDataPerWrite_K,
index_t OutThreadCopyDataPerAccess_B>
......@@ -56,23 +58,32 @@ struct GridwiseConvolutionImplicitGemm_v4r4_nchw_kcyx_nkhw_lds_double_buffer
constexpr auto I1 = Number<1>{};
constexpr auto I2 = Number<2>{};
constexpr auto I3 = Number<3>{};
constexpr auto I5 = Number<5>{};
constexpr auto True = integral_constant<bool, true>{};
constexpr auto in_n_c_h_w_global_desc = InGlobalDesc{};
constexpr auto wei_k_c_y_x_global_desc = WeiGlobalDesc{};
constexpr auto out_n_k_h_w_global_desc = OutGlobalDesc{};
constexpr auto generic_address_space =
integral_constant<AddressSpace, AddressSpace::generic>{};
constexpr auto global_address_space =
integral_constant<AddressSpace, AddressSpace::global>{};
constexpr index_t N = in_n_c_h_w_global_desc.GetLengths()[0];
constexpr index_t C = in_n_c_h_w_global_desc.GetLengths()[1];
constexpr auto in_n_c_hi_wi_global_desc =
make_native_tensor_descriptor(InGlobalDesc::GetLengths(), InGlobalDesc::GetStrides());
constexpr auto wei_k_c_y_x_global_desc =
make_native_tensor_descriptor(WeiGlobalDesc::GetLengths(), WeiGlobalDesc::GetStrides());
constexpr auto out_n_k_ho_wo_global_desc =
make_native_tensor_descriptor(OutGlobalDesc::GetLengths(), OutGlobalDesc::GetStrides());
constexpr index_t K = out_n_k_h_w_global_desc.GetLengths()[1];
constexpr index_t Ho = out_n_k_h_w_global_desc.GetLengths()[2];
constexpr index_t Wo = out_n_k_h_w_global_desc.GetLengths()[3];
constexpr index_t N = in_n_c_hi_wi_global_desc.GetLength(I0);
constexpr index_t C = in_n_c_hi_wi_global_desc.GetLength(I1);
constexpr index_t Hi = in_n_c_hi_wi_global_desc.GetLength(I2);
constexpr index_t Wi = in_n_c_hi_wi_global_desc.GetLength(I3);
constexpr index_t Y = wei_k_c_y_x_global_desc.GetLengths()[2];
constexpr index_t X = wei_k_c_y_x_global_desc.GetLengths()[3];
constexpr index_t K = out_n_k_ho_wo_global_desc.GetLength(I1);
constexpr index_t Ho = out_n_k_ho_wo_global_desc.GetLength(I2);
constexpr index_t Wo = out_n_k_ho_wo_global_desc.GetLength(I3);
constexpr index_t Y = wei_k_c_y_x_global_desc.GetLength(I2);
constexpr index_t X = wei_k_c_y_x_global_desc.GetLength(I3);
constexpr index_t ConvStrideH = ConvStrides{}[0];
constexpr index_t ConvStrideW = ConvStrides{}[1];
......@@ -90,50 +101,52 @@ struct GridwiseConvolutionImplicitGemm_v4r4_nchw_kcyx_nkhw_lds_double_buffer
"be violated");
// divide block work by [K, B]
static_assert(K % KPerBlock == 0 && B % BPerBlock == 0 && E % (2 * EPerBlock) == 0,
static_assert(K % KPerBlock == 0 && B % BPerBlock == 0 && E % EPerBlock == 0,
"wrong! cannot divide work evenly among block");
constexpr index_t KBlockWork = K / KPerBlock;
constexpr index_t BBlockWork = B / BPerBlock;
constexpr auto block_work_desc =
make_ConstantTensorDescriptor_packed(Sequence<KBlockWork, BBlockWork>{});
make_cluster_descriptor(Sequence<KBlockWork, BBlockWork>{});
const auto block_work_multi_id =
block_work_desc.GetMultiIndexFrom1dIndex(get_block_1d_id());
const auto block_work_id = block_work_desc.CalculateClusterIndex(get_block_1d_id());
const index_t k_block_data_on_global = block_work_multi_id[0] * KPerBlock;
const index_t b_block_data_on_global = block_work_multi_id[1] * BPerBlock;
const index_t k_block_data_on_global = block_work_id[0] * KPerBlock;
const index_t b_block_data_on_global = block_work_id[1] * BPerBlock;
// input tensor
// tensor descriptor in device memory [N, Ho, Wo]
constexpr auto in_n_ho_wo_global_desc =
in_n_c_h_w_global_desc.Extract(I0, I2, I3)
.StridedSlice(I1, Number<Ho>{}, Number<ConvStrideH>{})
.StridedSlice(I2, Number<Wo>{}, Number<ConvStrideW>{});
// batch descritpor for device memory
constexpr auto in_c_y_x_global_desc =
in_n_c_h_w_global_desc.StridedSlice(I2, Number<Y>{}, Number<ConvDilationH>{})
.StridedSlice(I3, Number<X>{}, Number<ConvDilationW>{})
.Extract(Sequence<1, 2, 3>{});
// merged tensor descriptor in device memory [E, B], src of blockwise copy
constexpr auto in_e_b_global_desc =
make_ConstantMergedTensorDescriptor(in_c_y_x_global_desc.Embed(in_n_ho_wo_global_desc),
Sequence<0, 1, 2>{},
Sequence<3, 4, 5>{});
// memory layout descriptor in LDS [E, B], dst of blockwise copy
// global mem
constexpr auto in_n_c_hip_wip_global_desc = transform_tensor_descriptor(
in_n_c_hi_wi_global_desc,
make_tuple(
PassThrough<N>{}, PassThrough<C>{}, Pad<Sequence<Hi, Wi>, LeftPads, RightPads>{}),
make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2, 3>{}),
make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2, 3>{}));
constexpr auto in_n_c_y_ho_x_wo_global_desc = transform_tensor_descriptor(
in_n_c_hip_wip_global_desc,
make_tuple(PassThrough<N>{},
PassThrough<C>{},
Embed<Sequence<Y, Ho>, Sequence<ConvDilationH, ConvStrideH, 0>>{},
Embed<Sequence<X, Wo>, Sequence<ConvDilationW, ConvStrideW, 0>>{}),
make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}, Sequence<3>{}),
make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2, 3>{}, Sequence<4, 5>{}));
constexpr auto in_e_b_global_desc = transform_tensor_descriptor(
in_n_c_y_ho_x_wo_global_desc,
make_tuple(Merge<Sequence<C, Y, X>>{}, Merge<Sequence<N, Ho, Wo>>{}),
make_tuple(Sequence<1, 2, 4>{}, Sequence<0, 3, 5>{}),
make_tuple(Sequence<0>{}, Sequence<1>{}));
// LDS mem
// be careful of LDS alignment
constexpr auto in_e_b_block_desc =
make_ConstantTensorDescriptor_packed(Sequence<EPerBlock, BPerBlock>{});
make_native_tensor_descriptor_packed(Sequence<EPerBlock, BPerBlock>{});
// input blockwise copy
// slice a merged tensor, reorder and copy to a normal tensor
// this copy operator already has blockwise offset built-in
auto blockwise_in_copy =
BlockwiseGenericTensorSliceCopy_v2<BlockSize,
BlockwiseGenericTensorSliceCopy_v4<BlockSize,
decltype(in_e_b_global_desc),
decltype(in_e_b_block_desc),
decltype(in_e_b_block_desc.GetLengths()),
......@@ -149,13 +162,13 @@ struct GridwiseConvolutionImplicitGemm_v4r4_nchw_kcyx_nkhw_lds_double_buffer
{0, b_block_data_on_global}, {0, 0});
// weight tensor
// tensor descriptor in device memory, src of blockwise copy
constexpr auto wei_e_k_global_desc =
wei_k_c_y_x_global_desc.Unfold(I1, I3).ReorderGivenNew2Old(Sequence<1, 0>{});
// global mem
constexpr auto wei_e_k_global_desc = reorder_tensor_descriptor_given_upper2lower(
unfold_tensor_descriptor(wei_k_c_y_x_global_desc, I1, I3), Sequence<1, 0>{});
// tensor descriptor in LDS, dst of blockwise copy
// LDS
// be careful of LDS alignment
constexpr auto wei_e_k_block_desc = make_ConstantTensorDescriptor_aligned(
constexpr auto wei_e_k_block_desc = make_native_tensor_descriptor_aligned(
Sequence<EPerBlock, KPerBlock>{},
Number<math::lcm(WeiBlockCopyDstDataPerWrite_K, GemmDataPerReadA)>{});
......@@ -165,11 +178,9 @@ struct GridwiseConvolutionImplicitGemm_v4r4_nchw_kcyx_nkhw_lds_double_buffer
static_assert(wei_e_k_block_desc.GetStride(I0) % GemmDataPerReadA == 0,
"GemmDataPerReadA alignment requirement is not satisfied");
// operator for blockwise copy of weight into LDS
// slice a tensor, and copy it into another tensor
// this copy operator already have blockwise offset built-in
// weight blockwise copy
auto blockwise_wei_copy =
BlockwiseGenericTensorSliceCopy_v2<BlockSize,
BlockwiseGenericTensorSliceCopy_v4<BlockSize,
decltype(wei_e_k_global_desc),
decltype(wei_e_k_block_desc),
decltype(wei_e_k_block_desc.GetLengths()),
......@@ -247,14 +258,12 @@ struct GridwiseConvolutionImplicitGemm_v4r4_nchw_kcyx_nkhw_lds_double_buffer
// zero out threadwise output
threadwise_matrix_set_zero(c_k0k1_b0b1_thread_mtx_desc, p_out_thread);
const Float* p_wei_block_on_global = p_wei_global;
// LDS double buffer: preload data into LDS
{
blockwise_in_copy.template Run<Float, address_space_t::global>(p_in_global,
p_in_block_double);
blockwise_wei_copy.template Run<Float, address_space_t::global>(p_wei_global,
p_wei_block_double);
blockwise_in_copy.Run(
p_in_global, p_in_block_double, global_address_space, generic_address_space);
blockwise_wei_copy.Run(
p_wei_global, p_wei_block_double, global_address_space, generic_address_space);
}
// LDS double buffer: main body
......@@ -285,10 +294,10 @@ struct GridwiseConvolutionImplicitGemm_v4r4_nchw_kcyx_nkhw_lds_double_buffer
__syncthreads();
// LDS doubel buffer: load next data from device mem
blockwise_in_copy.template RunLoadThreadBuffer<Float, address_space_t::global>(
p_in_global, p_in_thread_buffer);
blockwise_wei_copy.template RunLoadThreadBuffer<Float, address_space_t::global>(
p_wei_global, p_wei_thread_buffer);
blockwise_in_copy.RunLoadThreadBuffer(
p_in_global, p_in_thread_buffer, global_address_space, generic_address_space);
blockwise_wei_copy.RunLoadThreadBuffer(
p_wei_global, p_wei_thread_buffer, global_address_space, generic_address_space);
// LDS double buffer: GEMM on current data
blockwise_gemm.Run(p_wei_block_now, p_in_block_now, p_out_thread);
......@@ -300,32 +309,34 @@ struct GridwiseConvolutionImplicitGemm_v4r4_nchw_kcyx_nkhw_lds_double_buffer
}
// LDS double buffer: tail
{
constexpr bool has_two_iteration_left = (E % (2 * EPerBlock) == 0);
if(has_two_iteration_left) // if has 2 iteration left
{
Float p_in_thread_buffer[blockwise_in_copy.GetThreadBufferSize()];
Float p_wei_thread_buffer[blockwise_wei_copy.GetThreadBufferSize()];
// even iteration
blockwise_in_copy.MoveSrcSliceWindow(Sequence<EPerBlock, 0>{}, True);
blockwise_wei_copy.MoveSrcSliceWindow(Sequence<EPerBlock, 0>{}, True);
__syncthreads();
// LDS doubel buffer: load next data from device mem
blockwise_in_copy.template RunLoadThreadBuffer<Float, address_space_t::global>(
p_in_global, p_in_thread_buffer);
blockwise_wei_copy.template RunLoadThreadBuffer<Float, address_space_t::global>(
p_wei_global, p_wei_thread_buffer);
// LDS double buffer: load last data from device mem
blockwise_in_copy.RunLoadThreadBuffer(
p_in_global, p_in_thread_buffer, global_address_space, generic_address_space);
blockwise_wei_copy.RunLoadThreadBuffer(
p_wei_global, p_wei_thread_buffer, global_address_space, generic_address_space);
// LDS double buffer: GEMM on current data
// LDS double buffer: GEMM on 2nd-last data
blockwise_gemm.Run(p_wei_block_double, p_in_block_double, p_out_thread);
// LDS double buffer: store next data to LDS
// LDS double buffer: store last data to LDS
blockwise_in_copy.RunStoreThreadBuffer(p_in_thread_buffer,
p_in_block_double + in_block_space);
blockwise_wei_copy.RunStoreThreadBuffer(p_wei_thread_buffer,
p_wei_block_double + wei_block_space);
// odd iteration
__syncthreads();
// LDS double buffer: GEMM on current data
......@@ -333,18 +344,17 @@ struct GridwiseConvolutionImplicitGemm_v4r4_nchw_kcyx_nkhw_lds_double_buffer
p_in_block_double + in_block_space,
p_out_thread);
}
// copy output: register to global memory
else // if has 1 iteration left
{
constexpr index_t K1 = GemmMPerThreadSubC * GemmMLevel0Cluster * GemmMLevel1Cluster;
constexpr index_t B1 = GemmNPerThreadSubC * GemmNLevel0Cluster * GemmNLevel1Cluster;
__syncthreads();
// define tensor descriptor for threadwise copy
// output global descriptor, for calculating origin of thread tensor
// in global memory
constexpr auto out_k_b_global_desc = make_ConstantMergedTensorDescriptor(
out_n_k_h_w_global_desc, Sequence<1>{}, Sequence<0, 2, 3>{});
// LDS double buffer: GEMM on last data
blockwise_gemm.Run(p_wei_block_double, p_in_block_double, p_out_thread);
}
}
// copy output: register to global memory
{
// calculate origin of thread output tensor on global memory
// blockwise GEMM c matrix starting index
const auto c_thread_mtx_on_block =
......@@ -356,47 +366,48 @@ struct GridwiseConvolutionImplicitGemm_v4r4_nchw_kcyx_nkhw_lds_double_buffer
const index_t b_thread_data_on_global =
b_block_data_on_global + c_thread_mtx_on_block.col;
// This is a hack, because slicing a merged dimension is not supported yet.
// This should be replaced with logic above, once slicing a merged dimension support
// become available
// src descriptor
constexpr auto out_k0_k1_b0_b1_thread_desc = make_native_tensor_descriptor_packed(
Sequence<GemmMRepeat, GemmMPerThreadSubC, GemmNRepeat, GemmNPerThreadSubC>{});
// dst descriptor
constexpr auto out_k0_k1_b_global_desc =
make_ConstantMergedTensorDescriptor(out_n_k_h_w_global_desc.Fold(I1, Number<K1>{}),
Sequence<1>{},
Sequence<2>{},
Sequence<0, 3, 4>{});
constexpr index_t K1 = GemmMPerThreadSubC * GemmMLevel0Cluster * GemmMLevel1Cluster;
constexpr index_t B1 = GemmNPerThreadSubC * GemmNLevel0Cluster * GemmNLevel1Cluster;
// src descriptor
constexpr auto out_k0_k1_b_thread_desc = make_ConstantTensorDescriptor_packed(
Sequence<GemmMRepeat, GemmMPerThreadSubC, GemmNRepeat * GemmNPerThreadSubC>{});
using OutThreadCopySliceLengths =
Sequence<GemmMRepeat, GemmMPerThreadSubC, GemmNPerThreadSubC>;
auto threadwise_out_copy =
ThreadwiseGenericTensorSliceCopy_v2r1<decltype(out_k0_k1_b_thread_desc),
decltype(out_k0_k1_b_global_desc),
OutThreadCopySliceLengths,
arithmetic_sequence_gen<0, 3, 1>::type,
arithmetic_sequence_gen<0, 3, 1>::type,
2,
2,
constexpr index_t K0 = K / K1;
constexpr index_t B0 = B / B1;
constexpr auto out_k_b_global_desc = transform_tensor_descriptor(
out_n_k_ho_wo_global_desc,
make_tuple(PassThrough<K>{}, Merge<Sequence<N, Ho, Wo>>{}),
make_tuple(Sequence<1>{}, Sequence<0, 2, 3>{}),
make_tuple(Sequence<0>{}, Sequence<1>{}));
constexpr auto out_k0_k1_b0_b1_global_desc = transform_tensor_descriptor(
out_k_b_global_desc,
make_tuple(UnMerge<Sequence<K0, K1>>{}, UnMerge<Sequence<B0, B1>>{}),
make_tuple(Sequence<0>{}, Sequence<1>{}),
make_tuple(Sequence<0, 1>{}, Sequence<2, 3>{}));
// output threadwise copy
ThreadwiseGenericTensorSliceCopy_v4r2<
decltype(out_k0_k1_b0_b1_thread_desc),
decltype(out_k0_k1_b0_b1_global_desc),
decltype(out_k0_k1_b0_b1_thread_desc.GetLengths()),
arithmetic_sequence_gen<0, 4, 1>::type,
3,
OutThreadCopyDataPerAccess_B,
OutThreadCopyDataPerAccess_B>(
{0, 0, 0},
OutThreadCopyDataPerAccess_B>({0, 0, 0, 0},
{k_thread_data_on_global / K1,
k_thread_data_on_global % K1,
b_thread_data_on_global});
for(index_t nrepeat = 0; nrepeat < GemmNRepeat; ++nrepeat)
{
threadwise_out_copy
.template Run<Float, address_space_t::generic, address_space_t::global>(
p_out_thread, p_out_global);
threadwise_out_copy.MoveSrcSliceWindow(Sequence<0, 0, GemmNPerThreadSubC>{}, True);
threadwise_out_copy.MoveDstSliceWindow(Sequence<0, 0, B1>{}, True);
}
b_thread_data_on_global / B1,
b_thread_data_on_global % B1})
#if 1
.Run(p_out_thread, p_out_global, generic_address_space, global_address_space);
#else // tweaking
.Run_optimized_dst_address_calculation(
p_out_thread, p_out_global, generic_address_space, global_address_space);
#endif
}
}
};
......
composable_kernel/include/kernel_algorithm/gridwise_convolution_implicit_gemm_v4r4_nchw_kcyx_nkhw_padded_lds_double_buffer.hpp → composable_kernel/include/kernel_algorithm/gridwise_convolution_implicit_gemm_v4r4_nchw_kcyx_nkhw_lds_double_buffer_deprecated.hpp
View file @ 52c3fe05
#ifndef CK_GRIDWISE_CONVOLUTION_IMPLICIT_GEMM_V4R4_NCHW_KCYX_NKHW_PADDED_LDS_DOUBLE_BUFFER_HPP
#define CK_GRIDWISE_CONVOLUTION_IMPLICIT_GEMM_V4R4_NCHW_KCYX_NKHW_PADDED_LDS_DOUBLE_BUFFER_HPP
#ifndef CK_GRIDWISE_CONVOLUTION_IMPLICIT_GEMM_V4R4_NCHW_KCYX_NKHW_HPP_LDS_DOUBLE_BUFFER_DEPRECATRD_HPP
#define CK_GRIDWISE_CONVOLUTION_IMPLICIT_GEMM_V4R4_NCHW_KCYX_NKHW_HPP_LDS_DOUBLE_BUFFER_DEPRECATRD_HPP
#include "common_header.hpp"
#include "tensor_descriptor.hpp"
#include "tensor_descriptor_helper.hpp"
#include "ConstantTensorDescriptor_deprecated.hpp"
#include "ConstantMergedTensorDescriptor_deprecated.hpp"
#include "ConstantMatrixDescriptor.hpp"
#include "blockwise_generic_tensor_slice_copy.hpp"
#include "threadwise_generic_tensor_slice_copy.hpp"
#include "blockwise_generic_tensor_slice_copy_deprecated.hpp"
#include "blockwise_gemm.hpp"
#include "threadwise_generic_tensor_slice_copy_deprecated.hpp"
namespace ck {
// B = merge(N, Ho, Wo)
template <index_t GridSize,
index_t BlockSize,
typename Float,
typename InGlobalDesc,
typename WeiGlobalDesc,
typename OutGlobalDesc,
typename ConvStrides,
typename ConvDilations,
typename LeftPads,
typename RightPads,
class Float,
class InGlobalDesc,
class WeiGlobalDesc,
class OutGlobalDesc,
class ConvStrides,
class ConvDilations,
index_t BPerBlock,
index_t KPerBlock,
index_t EPerBlock,
......@@ -34,21 +32,21 @@ template <index_t GridSize,
index_t GemmKPerThreadLoop,
index_t GemmDataPerReadA,
index_t GemmDataPerReadB,
typename InBlockCopySubLengths_E_B,
typename InBlockCopyClusterLengths_E_B,
typename InBlockCopyThreadClusterArrangeOrder,
typename InBlockCopySrcAccessOrder,
typename InBlockCopyDstAccessOrder,
class InBlockCopySubLengths_E_B,
class InBlockCopyClusterLengths_E_B,
class InBlockCopyThreadClusterArrangeOrder,
class InBlockCopySrcAccessOrder,
class InBlockCopyDstAccessOrder,
index_t InBlockCopyDataPerAccess_B,
typename WeiBlockCopySubLengths_E_K,
typename WeiBlockCopyClusterLengths_E_K,
typename WeiBlockCopyThreadClusterArrangeOrder,
typename WeiBlockCopySrcAccessOrder,
typename WeiBlockCopyDstAccessOrder,
class WeiBlockCopySubLengths_E_K,
class WeiBlockCopyClusterLengths_E_K,
class WeiBlockCopyThreadClusterArrangeOrder,
class WeiBlockCopySrcAccessOrder,
class WeiBlockCopyDstAccessOrder,
index_t WeiBlockCopySrcDataPerRead_E,
index_t WeiBlockCopyDstDataPerWrite_K,
index_t OutThreadCopyDataPerAccess_B>
struct GridwiseConvolutionImplicitGemm_v4r4_nchw_kcyx_nkhw_padded_lds_double_buffer
struct GridwiseConvolutionImplicitGemm_v4r4_nchw_kcyx_nkhw_lds_double_buffer_deprecated
{
__device__ void Run(const Float* const __restrict__ p_in_global,
const Float* const __restrict__ p_wei_global,
......@@ -58,27 +56,23 @@ struct GridwiseConvolutionImplicitGemm_v4r4_nchw_kcyx_nkhw_padded_lds_double_buf
constexpr auto I1 = Number<1>{};
constexpr auto I2 = Number<2>{};
constexpr auto I3 = Number<3>{};
constexpr auto I5 = Number<5>{};
constexpr auto True = integral_constant<bool, true>{};
constexpr auto in_n_c_hi_wi_global_desc =
make_native_tensor_descriptor(InGlobalDesc::GetLengths(), InGlobalDesc::GetStrides());
constexpr auto wei_k_c_y_x_global_desc =
make_native_tensor_descriptor(WeiGlobalDesc::GetLengths(), WeiGlobalDesc::GetStrides());
constexpr auto out_n_k_ho_wo_global_desc =
make_native_tensor_descriptor(OutGlobalDesc::GetLengths(), OutGlobalDesc::GetStrides());
constexpr auto in_n_c_h_w_global_desc = InGlobalDesc{};
constexpr auto wei_k_c_y_x_global_desc = WeiGlobalDesc{};
constexpr auto out_n_k_h_w_global_desc = OutGlobalDesc{};
constexpr index_t N = in_n_c_hi_wi_global_desc.GetLength(I0);
constexpr index_t C = in_n_c_hi_wi_global_desc.GetLength(I1);
constexpr index_t Hi = in_n_c_hi_wi_global_desc.GetLength(I2);
constexpr index_t Wi = in_n_c_hi_wi_global_desc.GetLength(I3);
constexpr index_t N = in_n_c_h_w_global_desc.GetLengths()[0];
constexpr index_t C = in_n_c_h_w_global_desc.GetLengths()[1];
constexpr index_t K = out_n_k_ho_wo_global_desc.GetLength(I1);
constexpr index_t Ho = out_n_k_ho_wo_global_desc.GetLength(I2);
constexpr index_t Wo = out_n_k_ho_wo_global_desc.GetLength(I3);
constexpr index_t K = out_n_k_h_w_global_desc.GetLengths()[1];
constexpr index_t Ho = out_n_k_h_w_global_desc.GetLengths()[2];
constexpr index_t Wo = out_n_k_h_w_global_desc.GetLengths()[3];
constexpr index_t Y = wei_k_c_y_x_global_desc.GetLength(I2);
constexpr index_t X = wei_k_c_y_x_global_desc.GetLength(I3);
constexpr index_t Y = wei_k_c_y_x_global_desc.GetLengths()[2];
constexpr index_t X = wei_k_c_y_x_global_desc.GetLengths()[3];
constexpr index_t ConvStrideH = ConvStrides{}[0];
constexpr index_t ConvStrideW = ConvStrides{}[1];
......@@ -103,45 +97,43 @@ struct GridwiseConvolutionImplicitGemm_v4r4_nchw_kcyx_nkhw_padded_lds_double_buf
constexpr index_t BBlockWork = B / BPerBlock;
constexpr auto block_work_desc =
make_cluster_descriptor(Sequence<KBlockWork, BBlockWork>{});
make_ConstantTensorDescriptor_packed(Sequence<KBlockWork, BBlockWork>{});
const auto block_work_id = block_work_desc.CalculateClusterIndex(get_block_1d_id());
const auto block_work_multi_id =
block_work_desc.GetMultiIndexFrom1dIndex(get_block_1d_id());
const index_t k_block_data_on_global = block_work_id[0] * KPerBlock;
const index_t b_block_data_on_global = block_work_id[1] * BPerBlock;
const index_t k_block_data_on_global = block_work_multi_id[0] * KPerBlock;
const index_t b_block_data_on_global = block_work_multi_id[1] * BPerBlock;
// input tensor
// global mem
constexpr auto in_n_c_hip_wip_global_desc = transform_tensor_descriptor(
in_n_c_hi_wi_global_desc,
make_tuple(
PassThrough<N>{}, PassThrough<C>{}, Pad<Sequence<Hi, Wi>, LeftPads, RightPads>{}),
make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2, 3>{}),
make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2, 3>{}));
constexpr auto in_n_c_y_ho_x_wo_global_desc = transform_tensor_descriptor(
in_n_c_hip_wip_global_desc,
make_tuple(PassThrough<N>{},
PassThrough<C>{},
Embed<Sequence<Y, Ho>, Sequence<ConvDilationH, ConvStrideH, 0>>{},
Embed<Sequence<X, Wo>, Sequence<ConvDilationW, ConvStrideW, 0>>{}),
make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}, Sequence<3>{}),
make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2, 3>{}, Sequence<4, 5>{}));
constexpr auto in_e_b_global_desc = transform_tensor_descriptor(
in_n_c_y_ho_x_wo_global_desc,
make_tuple(Merge<Sequence<C, Y, X>>{}, Merge<Sequence<N, Ho, Wo>>{}),
make_tuple(Sequence<1, 2, 4>{}, Sequence<0, 3, 5>{}),
make_tuple(Sequence<0>{}, Sequence<1>{}));
// LDS mem
// tensor descriptor in device memory [N, Ho, Wo]
constexpr auto in_n_ho_wo_global_desc =
in_n_c_h_w_global_desc.Extract(I0, I2, I3)
.StridedSlice(I1, Number<Ho>{}, Number<ConvStrideH>{})
.StridedSlice(I2, Number<Wo>{}, Number<ConvStrideW>{});
// batch descritpor for device memory
constexpr auto in_c_y_x_global_desc =
in_n_c_h_w_global_desc.StridedSlice(I2, Number<Y>{}, Number<ConvDilationH>{})
.StridedSlice(I3, Number<X>{}, Number<ConvDilationW>{})
.Extract(Sequence<1, 2, 3>{});
// merged tensor descriptor in device memory [E, B], src of blockwise copy
constexpr auto in_e_b_global_desc =
make_ConstantMergedTensorDescriptor(in_c_y_x_global_desc.Embed(in_n_ho_wo_global_desc),
Sequence<0, 1, 2>{},
Sequence<3, 4, 5>{});
// memory layout descriptor in LDS [E, B], dst of blockwise copy
// be careful of LDS alignment
constexpr auto in_e_b_block_desc =
make_native_tensor_descriptor_packed(Sequence<EPerBlock, BPerBlock>{});
make_ConstantTensorDescriptor_packed(Sequence<EPerBlock, BPerBlock>{});
// input blockwise copy
// slice a merged tensor, reorder and copy to a normal tensor
// this copy operator already has blockwise offset built-in
auto blockwise_in_copy =
BlockwiseGenericTensorSliceCopy_v4<BlockSize,
BlockwiseGenericTensorSliceCopy_v2_deprecated<BlockSize,
decltype(in_e_b_global_desc),
decltype(in_e_b_block_desc),
decltype(in_e_b_block_desc.GetLengths()),
......@@ -157,13 +149,13 @@ struct GridwiseConvolutionImplicitGemm_v4r4_nchw_kcyx_nkhw_padded_lds_double_buf
{0, b_block_data_on_global}, {0, 0});
// weight tensor
// global mem
constexpr auto wei_e_k_global_desc = reorder_tensor_descriptor_given_upper2lower(
unfold_tensor_descriptor(wei_k_c_y_x_global_desc, I1, I3), Sequence<1, 0>{});
// tensor descriptor in device memory, src of blockwise copy
constexpr auto wei_e_k_global_desc =
wei_k_c_y_x_global_desc.Unfold(I1, I3).ReorderGivenNew2Old(Sequence<1, 0>{});
// LDS
// tensor descriptor in LDS, dst of blockwise copy
// be careful of LDS alignment
constexpr auto wei_e_k_block_desc = make_native_tensor_descriptor_aligned(
constexpr auto wei_e_k_block_desc = make_ConstantTensorDescriptor_aligned(
Sequence<EPerBlock, KPerBlock>{},
Number<math::lcm(WeiBlockCopyDstDataPerWrite_K, GemmDataPerReadA)>{});
......@@ -173,9 +165,11 @@ struct GridwiseConvolutionImplicitGemm_v4r4_nchw_kcyx_nkhw_padded_lds_double_buf
static_assert(wei_e_k_block_desc.GetStride(I0) % GemmDataPerReadA == 0,
"GemmDataPerReadA alignment requirement is not satisfied");
// weight blockwise copy
// operator for blockwise copy of weight into LDS
// slice a tensor, and copy it into another tensor
// this copy operator already have blockwise offset built-in
auto blockwise_wei_copy =
BlockwiseGenericTensorSliceCopy_v4<BlockSize,
BlockwiseGenericTensorSliceCopy_v2_deprecated<BlockSize,
decltype(wei_e_k_global_desc),
decltype(wei_e_k_block_desc),
decltype(wei_e_k_block_desc.GetLengths()),
......@@ -253,12 +247,14 @@ struct GridwiseConvolutionImplicitGemm_v4r4_nchw_kcyx_nkhw_padded_lds_double_buf
// zero out threadwise output
threadwise_matrix_set_zero(c_k0k1_b0b1_thread_mtx_desc, p_out_thread);
const Float* p_wei_block_on_global = p_wei_global;
// LDS double buffer: preload data into LDS
{
blockwise_in_copy.template Run<Float, Float, address_space_t::global>(
p_in_global, p_in_block_double);
blockwise_wei_copy.template Run<Float, Float, address_space_t::global>(
p_wei_global, p_wei_block_double);
blockwise_in_copy.template Run<Float, AddressSpace::global>(p_in_global,
p_in_block_double);
blockwise_wei_copy.template Run<Float, AddressSpace::global>(p_wei_global,
p_wei_block_double);
}
// LDS double buffer: main body
......@@ -289,11 +285,9 @@ struct GridwiseConvolutionImplicitGemm_v4r4_nchw_kcyx_nkhw_padded_lds_double_buf
__syncthreads();
// LDS doubel buffer: load next data from device mem
blockwise_in_copy
.template RunLoadThreadBuffer<Float, Float, address_space_t::global>(
blockwise_in_copy.template RunLoadThreadBuffer<Float, AddressSpace::global>(
p_in_global, p_in_thread_buffer);
blockwise_wei_copy
.template RunLoadThreadBuffer<Float, Float, address_space_t::global>(
blockwise_wei_copy.template RunLoadThreadBuffer<Float, AddressSpace::global>(
p_wei_global, p_wei_thread_buffer);
// LDS double buffer: GEMM on current data
......@@ -317,9 +311,9 @@ struct GridwiseConvolutionImplicitGemm_v4r4_nchw_kcyx_nkhw_padded_lds_double_buf
__syncthreads();
// LDS doubel buffer: load next data from device mem
blockwise_in_copy.template RunLoadThreadBuffer<Float, Float, address_space_t::global>(
blockwise_in_copy.template RunLoadThreadBuffer<Float, AddressSpace::global>(
p_in_global, p_in_thread_buffer);
blockwise_wei_copy.template RunLoadThreadBuffer<Float, Float, address_space_t::global>(
blockwise_wei_copy.template RunLoadThreadBuffer<Float, AddressSpace::global>(
p_wei_global, p_wei_thread_buffer);
// LDS double buffer: GEMM on current data
......@@ -342,6 +336,15 @@ struct GridwiseConvolutionImplicitGemm_v4r4_nchw_kcyx_nkhw_padded_lds_double_buf
// copy output: register to global memory
{
constexpr index_t K1 = GemmMPerThreadSubC * GemmMLevel0Cluster * GemmMLevel1Cluster;
constexpr index_t B1 = GemmNPerThreadSubC * GemmNLevel0Cluster * GemmNLevel1Cluster;
// define tensor descriptor for threadwise copy
// output global descriptor, for calculating origin of thread tensor
// in global memory
constexpr auto out_k_b_global_desc = make_ConstantMergedTensorDescriptor(
out_n_k_h_w_global_desc, Sequence<1>{}, Sequence<0, 2, 3>{});
// calculate origin of thread output tensor on global memory
// blockwise GEMM c matrix starting index
const auto c_thread_mtx_on_block =
......@@ -353,51 +356,46 @@ struct GridwiseConvolutionImplicitGemm_v4r4_nchw_kcyx_nkhw_padded_lds_double_buf
const index_t b_thread_data_on_global =
b_block_data_on_global + c_thread_mtx_on_block.col;
// src descriptor
constexpr auto out_k0_k1_b0_b1_thread_desc = make_native_tensor_descriptor_packed(
Sequence<GemmMRepeat, GemmMPerThreadSubC, GemmNRepeat, GemmNPerThreadSubC>{});
// This is a hack, because slicing a merged dimension is not supported yet.
// This should be replaced with logic above, once slicing a merged dimension support
// become available
// dst descriptor
constexpr index_t K1 = GemmMPerThreadSubC * GemmMLevel0Cluster * GemmMLevel1Cluster;
constexpr index_t B1 = GemmNPerThreadSubC * GemmNLevel0Cluster * GemmNLevel1Cluster;
constexpr auto out_k0_k1_b_global_desc =
make_ConstantMergedTensorDescriptor(out_n_k_h_w_global_desc.Fold(I1, Number<K1>{}),
Sequence<1>{},
Sequence<2>{},
Sequence<0, 3, 4>{});
constexpr index_t K0 = K / K1;
constexpr index_t B0 = B / B1;
constexpr auto out_k_b_global_desc = transform_tensor_descriptor(
out_n_k_ho_wo_global_desc,
make_tuple(PassThrough<K>{}, Merge<Sequence<N, Ho, Wo>>{}),
make_tuple(Sequence<1>{}, Sequence<0, 2, 3>{}),
make_tuple(Sequence<0>{}, Sequence<1>{}));
constexpr auto out_k0_k1_b0_b1_global_desc = transform_tensor_descriptor(
out_k_b_global_desc,
make_tuple(UnMerge<Sequence<K0, K1>>{}, UnMerge<Sequence<B0, B1>>{}),
make_tuple(Sequence<0>{}, Sequence<1>{}),
make_tuple(Sequence<0, 1>{}, Sequence<2, 3>{}));
// output threadwise copy
ThreadwiseGenericTensorSliceCopy_v4r2<
decltype(out_k0_k1_b0_b1_thread_desc),
decltype(out_k0_k1_b0_b1_global_desc),
decltype(out_k0_k1_b0_b1_thread_desc.GetLengths()),
arithmetic_sequence_gen<0, 4, 1>::type,
3,
// src descriptor
constexpr auto out_k0_k1_b_thread_desc = make_ConstantTensorDescriptor_packed(
Sequence<GemmMRepeat, GemmMPerThreadSubC, GemmNRepeat * GemmNPerThreadSubC>{});
using OutThreadCopySliceLengths =
Sequence<GemmMRepeat, GemmMPerThreadSubC, GemmNPerThreadSubC>;
auto threadwise_out_copy = ThreadwiseGenericTensorSliceCopy_v2r1_deprecated<
decltype(out_k0_k1_b_thread_desc),
decltype(out_k0_k1_b_global_desc),
OutThreadCopySliceLengths,
arithmetic_sequence_gen<0, 3, 1>::type,
arithmetic_sequence_gen<0, 3, 1>::type,
2,
2,
OutThreadCopyDataPerAccess_B,
OutThreadCopyDataPerAccess_B>({0, 0, 0, 0},
OutThreadCopyDataPerAccess_B>({0, 0, 0},
{k_thread_data_on_global / K1,
k_thread_data_on_global % K1,
b_thread_data_on_global / B1,
b_thread_data_on_global % B1})
#if 1
.template Run<Float, Float, address_space_t::generic, address_space_t::global>
#else // tweaking
.template Run_optimized_dst_address_calculation<Float,
Float,
address_space_t::generic,
address_space_t::global>
#endif
(p_out_thread, p_out_global);
b_thread_data_on_global});
for(index_t nrepeat = 0; nrepeat < GemmNRepeat; ++nrepeat)
{
threadwise_out_copy
.template Run<Float, AddressSpace::generic, AddressSpace::global>(p_out_thread,
p_out_global);
threadwise_out_copy.MoveSrcSliceWindow(Sequence<0, 0, GemmNPerThreadSubC>{}, True);
threadwise_out_copy.MoveDstSliceWindow(Sequence<0, 0, B1>{}, True);
}
}
}
};
......
Markdown is supported
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment