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Commit 569ad66e authored by Chao Liu's avatar Chao Liu
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added implicit gemm v1r3 lds_double_buffer NCHW * CYXK = KNHW, reworked static functionals

parent 87d8740b
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driver/device_convolution_implicit_gemm_v1_chwn_cyxk_khwn.hpp
View file @ 569ad66e
......@@ -3,7 +3,6 @@
#include "device.hpp"
#include "gridwise_convolution_wrapper.hip.hpp"
#include "gridwise_convolution_implicit_gemm_v1r1_chwn_cyxk_khwn.hip.hpp"
#include "gridwise_convolution_implicit_gemm_v1r1_lds_double_buffer_chwn_cyxk_khwn.hip.hpp"
#include "gridwise_convolution_implicit_gemm_v1r2_chwn_cyxk_khwn.hip.hpp"
#include "gridwise_convolution_implicit_gemm_v1r3_chwn_cyxk_khwn.hip.hpp"
#include "gridwise_convolution_implicit_gemm_v1r3_lds_double_buffer_chwn_cyxk_khwn.hip.hpp"
......@@ -81,6 +80,8 @@ void device_convolution_implicit_gemm_v1_chwn_cyxk_khwn(InDesc,
#if 0
// for 3x3, 34x34, v1r1, Pascal
constexpr index_t BlockSize = 128;
constexpr index_t NPerBlock = 16;
constexpr index_t KPerBlock = 64;
constexpr index_t CPerBlock = 4;
......@@ -92,14 +93,6 @@ void device_convolution_implicit_gemm_v1_chwn_cyxk_khwn(InDesc,
constexpr index_t HoPerThread = 1;
constexpr index_t WoPerThread = 2;
constexpr index_t InBlockCopy_ThreadPerDimC = 4;
constexpr index_t InBlockCopy_ThreadPerDimH = 4;
constexpr index_t InBlockCopy_ThreadPerDimW = 2;
constexpr index_t InBlockCopy_ThreadPerDimN = 4;
constexpr index_t InBlockCopyDataPerRead_N = 4;
constexpr index_t WeiBlockCopyDataPerRead_K = 4;
constexpr index_t GemmMPerThreadSubC = 4;
constexpr index_t GemmNPerThreadSubC = 4;
constexpr index_t GemmMLevel0Cluster = 4;
......@@ -110,11 +103,16 @@ void device_convolution_implicit_gemm_v1_chwn_cyxk_khwn(InDesc,
constexpr index_t GemmDataPerReadA = 4;
constexpr index_t GemmDataPerReadB = 4;
constexpr index_t OutThreadCopyDataPerWrite_N = 2;
using InBlockCopyClusterLengths_CHWN = Sequence<4, 4, 2, 4>;
constexpr index_t InBlockCopyDataPerRead_N = 4;
constexpr index_t BlockSize = 128;
constexpr index_t WeiBlockCopyDataPerRead_K = 4;
constexpr index_t OutThreadCopyDataPerWrite_N = 2;
#elif 0
// for 3x3, 34x34, v1r2, Pascal, in-block-copy1
constexpr index_t BlockSize = 128;
constexpr index_t NPerBlock = 4;
constexpr index_t KPerBlock = 64;
constexpr index_t CPerBlock = 8;
......@@ -126,27 +124,86 @@ void device_convolution_implicit_gemm_v1_chwn_cyxk_khwn(InDesc,
constexpr index_t HoPerThread = 1;
constexpr index_t WoPerThread = 2;
constexpr index_t InBlockCopy_ThreadPerDimC = 4;
constexpr index_t InBlockCopy_ThreadPerDimH = 4;
constexpr index_t InBlockCopy_ThreadPerDimW = 2;
constexpr index_t InBlockCopy_ThreadPerDimN = 1;
constexpr index_t GemmMPerThreadSubC = 4;
constexpr index_t GemmNPerThreadSubC = 4;
constexpr index_t GemmMLevel0Cluster = 4;
constexpr index_t GemmNLevel0Cluster = 2;
constexpr index_t GemmMLevel1Cluster = 2;
constexpr index_t GemmNLevel1Cluster = 2;
constexpr index_t GemmKPerThreadLoop = 1;
constexpr index_t GemmDataPerReadA = 4;
constexpr index_t GemmDataPerReadB = 4;
using InBlockCopyClusterLengths_CHWN = Sequence<0, 0, 0, 0>; // not used
constexpr index_t InBlockCopyDataPerRead_N = 4;
constexpr index_t WeiBlockCopyDataPerRead_K = 4;
constexpr index_t OutThreadCopyDataPerWrite_N = 2;
#elif 1
// for 3x3, 34x34, v1r3, Pascal
// for 3x3, 28x28, v1r3, Pascal
// for 3x3, 14x14, v1r3, Pascal
constexpr index_t BlockSize = 128;
constexpr index_t NPerBlock = 16;
constexpr index_t KPerBlock = 128;
constexpr index_t CPerBlock = 8;
constexpr index_t HoPerBlock = 2;
constexpr index_t WoPerBlock = 2;
constexpr index_t NPerThread = 4;
constexpr index_t KPerThread = 8;
constexpr index_t HoPerThread = 1;
constexpr index_t WoPerThread = 2;
constexpr index_t GemmMPerThreadSubC = 4;
constexpr index_t GemmNPerThreadSubC = 4;
constexpr index_t GemmMLevel0Cluster = 4;
constexpr index_t GemmNLevel0Cluster = 2;
constexpr index_t GemmMLevel1Cluster = 2;
constexpr index_t GemmMLevel1Cluster = 4;
constexpr index_t GemmNLevel1Cluster = 2;
constexpr index_t GemmKPerThreadLoop = 1;
constexpr index_t GemmDataPerReadA = 4;
constexpr index_t GemmDataPerReadB = 4;
constexpr index_t OutThreadCopyDataPerWrite_N = 2;
using InBlockCopyClusterLengths_CHWN = Sequence<8, 2, 2, 4>;
constexpr index_t InBlockCopyDataPerRead_N = 4;
constexpr index_t WeiBlockCopyDataPerRead_K = 4;
constexpr index_t OutThreadCopyDataPerWrite_N = 2;
#elif 0
// for 3x3, 34x34, v1r3, Pascal, bad
constexpr index_t BlockSize = 128;
constexpr index_t NPerBlock = 1;
constexpr index_t KPerBlock = 128;
constexpr index_t CPerBlock = 8;
constexpr index_t HoPerBlock = 2;
constexpr index_t WoPerBlock = 32;
constexpr index_t NPerThread = 1;
constexpr index_t KPerThread = 8;
constexpr index_t HoPerThread = 1;
constexpr index_t WoPerThread = 8;
constexpr index_t GemmMPerThreadSubC = 4;
constexpr index_t GemmNPerThreadSubC = 4;
constexpr index_t GemmMLevel0Cluster = 4;
constexpr index_t GemmNLevel0Cluster = 2;
constexpr index_t GemmMLevel1Cluster = 4;
constexpr index_t GemmNLevel1Cluster = 2;
constexpr index_t GemmKPerThreadLoop = 1;
constexpr index_t GemmDataPerReadA = 4;
constexpr index_t GemmDataPerReadB = 4;
using InBlockCopyClusterLengths_CHWN = Sequence<2, 2, 32, 1>;
constexpr index_t InBlockCopyDataPerRead_N = 1;
constexpr index_t WeiBlockCopyDataPerRead_K = 2;
constexpr index_t OutThreadCopyDataPerWrite_N = 1;
#elif 0
// for 3x3, 34x34, v1r1, Vega 20
constexpr index_t NPerBlock = 16;
......@@ -309,38 +366,6 @@ void device_convolution_implicit_gemm_v1_chwn_cyxk_khwn(InDesc,
constexpr index_t WeiBlockCopyDataPerRead_K = 4;
constexpr index_t OutThreadCopyDataPerWrite_N = 2;
#elif 1
// for 3x3, 28x28, v1r3, Pascal
// for 3x3, 14x14, v1r3, Pascal
constexpr index_t BlockSize = 128;
constexpr index_t NPerBlock = 16;
constexpr index_t KPerBlock = 128;
constexpr index_t CPerBlock = 8;
constexpr index_t HoPerBlock = 2;
constexpr index_t WoPerBlock = 2;
constexpr index_t NPerThread = 4;
constexpr index_t KPerThread = 8;
constexpr index_t HoPerThread = 1;
constexpr index_t WoPerThread = 2;
constexpr index_t GemmMPerThreadSubC = 4;
constexpr index_t GemmNPerThreadSubC = 4;
constexpr index_t GemmMLevel0Cluster = 4;
constexpr index_t GemmNLevel0Cluster = 2;
constexpr index_t GemmMLevel1Cluster = 4;
constexpr index_t GemmNLevel1Cluster = 2;
constexpr index_t GemmKPerThreadLoop = 1;
constexpr index_t GemmDataPerReadA = 4;
constexpr index_t GemmDataPerReadB = 4;
using InBlockCopyClusterLengths_CHWN = Sequence<8, 2, 2, 4>;
constexpr index_t InBlockCopyDataPerRead_N = 4;
constexpr index_t WeiBlockCopyDataPerRead_K = 4;
constexpr index_t OutThreadCopyDataPerWrite_N = 2;
#elif 0
// for 1x1, 28x28, v1r1, Pascal
......@@ -419,13 +444,11 @@ void device_convolution_implicit_gemm_v1_chwn_cyxk_khwn(InDesc,
constexpr auto gridwise_conv =
#if 0
GridwiseConvolutionImplicitGemm_v1r1_chwn_cyxk_khwn
#elif 0
GridwiseConvolutionImplicitGemm_v1r1_lds_double_buffer_chwn_cyxk_khwn
#elif 0
GridwiseConvolutionImplicitGemm_v1r2_chwn_cyxk_khwn
#elif 0
GridwiseConvolutionImplicitGemm_v1r3_chwn_cyxk_khwn
#elif 1
GridwiseConvolutionImplicitGemm_v1r3_chwn_cyxk_khwn
#elif 0
GridwiseConvolutionImplicitGemm_v1r3_lds_double_buffer_chwn_cyxk_khwn
#endif
<GridSize,
......
driver/device_convolution_implicit_gemm_v1_nchw_cyxk_khwn.hpp
View file @ 569ad66e
......@@ -3,6 +3,8 @@
#include "device.hpp"
#include "gridwise_convolution_wrapper.hip.hpp"
#include "gridwise_convolution_implicit_gemm_v1r2_nchw_cyxk_khwn.hip.hpp"
#include "gridwise_convolution_implicit_gemm_v1r3_nchw_cyxk_khwn.hip.hpp"
#include "gridwise_convolution_implicit_gemm_v1r3_lds_double_buffer_nchw_cyxk_khwn.hip.hpp"
template <class T, class InDesc, class WeiDesc, class OutDesc>
void device_convolution_implicit_gemm_v1_nchw_cyxk_khwn(InDesc,
......@@ -62,7 +64,7 @@ void device_convolution_implicit_gemm_v1_nchw_cyxk_khwn(InDesc,
wei_cyxk_device_buf.ToDevice(wei_cyxk.mData.data());
out_khwn_device_buf.ToDevice(out_khwn.mData.data());
#if 1
#if 0
// for 3x3, 28x28, v1r2, Pascal
constexpr index_t BlockSize = 128;
......@@ -93,8 +95,78 @@ void device_convolution_implicit_gemm_v1_nchw_cyxk_khwn(InDesc,
constexpr index_t InBlockReorderDataPerRead_W = 2;
constexpr index_t InBlockReorderDataPerWrite_N = 4;
using WeiBlockCopyClusterLengths_CXK = Sequence<4, 1, 32>;
constexpr index_t WeiBlockCopyDataPerRead_C = 4;
using WeiBlockCopyClusterLengths = Sequence<4, 1, 32>;
constexpr index_t WeiBlockCopyDataPerRead_K = 4;
constexpr index_t OutThreadCopyDataPerWrite_N = 2;
#elif 0
// for 3x3, 28x28, v1r3, Pascal, bad
constexpr index_t BlockSize = 128;
constexpr index_t NPerBlock = 16;
constexpr index_t KPerBlock = 128;
constexpr index_t CPerBlock = 8;
constexpr index_t HoPerBlock = 2;
constexpr index_t WoPerBlock = 2;
constexpr index_t NPerThread = 4;
constexpr index_t KPerThread = 8;
constexpr index_t HoPerThread = 1;
constexpr index_t WoPerThread = 2;
constexpr index_t GemmMPerThreadSubC = 4;
constexpr index_t GemmNPerThreadSubC = 4;
constexpr index_t GemmMLevel0Cluster = 4;
constexpr index_t GemmNLevel0Cluster = 2;
constexpr index_t GemmMLevel1Cluster = 4;
constexpr index_t GemmNLevel1Cluster = 2;
constexpr index_t GemmKPerThreadLoop = 1;
constexpr index_t GemmDataPerReadA = 4;
constexpr index_t GemmDataPerReadB = 4;
using InBlockReorderSrcSubLengths_NCHW = Sequence<4, 1, 1, 1>;
using InBlockReorderSrcClusterLengths_NCHW = Sequence<4, 8, 2, 2>;
using InBlockReorderMapThreadCluster2SrcCluster_CHNW2NCHW = Sequence<1, 2, 0, 3>;
constexpr index_t InBlockReorderDataPerRead_W = 1; // v1r3 cannot do vector load input for NCHW
constexpr index_t InBlockReorderDataPerWrite_N = 1; // not used yet
using WeiBlockCopyClusterLengths = Sequence<0, 0>; // not used
constexpr index_t WeiBlockCopyDataPerRead_K = 4;
constexpr index_t OutThreadCopyDataPerWrite_N = 2;
#elif 1
// for 3x3, 34x34, v1r3, Pascal
constexpr index_t BlockSize = 128;
constexpr index_t NPerBlock = 2;
constexpr index_t KPerBlock = 128;
constexpr index_t CPerBlock = 8;
constexpr index_t HoPerBlock = 2;
constexpr index_t WoPerBlock = 16;
constexpr index_t NPerThread = 2;
constexpr index_t KPerThread = 8;
constexpr index_t HoPerThread = 1;
constexpr index_t WoPerThread = 4;
constexpr index_t GemmMPerThreadSubC = 4;
constexpr index_t GemmNPerThreadSubC = 4;
constexpr index_t GemmMLevel0Cluster = 4;
constexpr index_t GemmNLevel0Cluster = 2;
constexpr index_t GemmMLevel1Cluster = 4;
constexpr index_t GemmNLevel1Cluster = 2;
constexpr index_t GemmKPerThreadLoop = 1;
constexpr index_t GemmDataPerReadA = 4;
constexpr index_t GemmDataPerReadB = 4;
using InBlockReorderSrcSubLengths_NCHW = Sequence<2, 1, 2, 1>;
using InBlockReorderSrcClusterLengths_NCHW = Sequence<1, 8, 1, 16>;
using InBlockReorderMapThreadCluster2SrcCluster_CHNW2NCHW = Sequence<1, 2, 0, 3>;
constexpr index_t InBlockReorderDataPerRead_W = 1; // v1r3 cannot do vector load input for NCHW
constexpr index_t InBlockReorderDataPerWrite_N = 1; // not used yet
using WeiBlockCopyClusterLengths = Sequence<0, 0>; // not used
constexpr index_t WeiBlockCopyDataPerRead_K = 4;
constexpr index_t OutThreadCopyDataPerWrite_N = 2;
#endif
......@@ -108,8 +180,12 @@ void device_convolution_implicit_gemm_v1_nchw_cyxk_khwn(InDesc,
for(index_t i = 0; i < nrepeat; ++i)
{
constexpr auto gridwise_conv =
#if 1
#if 0
GridwiseConvolutionImplicitGemm_v1r2_nchw_cyxk_khwn
#elif 1
GridwiseConvolutionImplicitGemm_v1r3_nchw_cyxk_khwn
#elif 1
GridwiseConvolutionImplicitGemm_v1r3_lds_double_buffer_nchw_cyxk_khwn
#endif
<GridSize,
BlockSize,
......@@ -140,8 +216,8 @@ void device_convolution_implicit_gemm_v1_nchw_cyxk_khwn(InDesc,
InBlockReorderMapThreadCluster2SrcCluster_CHNW2NCHW,
InBlockReorderDataPerRead_W,
InBlockReorderDataPerWrite_N,
WeiBlockCopyClusterLengths_CXK,
WeiBlockCopyDataPerRead_C,
WeiBlockCopyClusterLengths,
WeiBlockCopyDataPerRead_K,
OutThreadCopyDataPerWrite_N>{};
float time = launch_kernel(run_gridwise_convolution<decltype(gridwise_conv), T>,
......
driver/driver.hip.cpp
View file @ 569ad66e
......@@ -46,7 +46,7 @@ struct GeneratorTensor_3
#if 0
auto f_acc = std::plus<index_t>{};
#else
auto f_acc = [](auto a, auto b) { return 10 * a + b; };
auto f_acc = [](auto a, auto b) { return 100 * a + b; };
#endif
return std::accumulate(dims.begin(), dims.end(), index_t(0), f_acc);
......@@ -390,8 +390,6 @@ void host_winograd_3x3_convolution(const Tensor<TIn>& in_nchw,
template <class T>
void check_error(const Tensor<T>& ref, const Tensor<T>& result)
{
// printf("\n");
float error = 0;
float max_diff = -1;
float ref_value = 0, result_value = 0;
......@@ -405,10 +403,7 @@ void check_error(const Tensor<T>& ref, const Tensor<T>& result)
ref_value = ref.mData[i];
result_value = result.mData[i];
}
// printf("{%f, %f}", double(ref.mData[i]), double(result.mData[i]));
}
// printf("\n");
std::cout << "error: " << error << std::endl;
std::cout << "max_diff: " << max_diff << ", " << ref_value << ", " << result_value << std::endl;
......@@ -416,18 +411,7 @@ void check_error(const Tensor<T>& ref, const Tensor<T>& result)
int main(int argc, char* argv[])
{
#if 0
constexpr index_t N = 128;
constexpr index_t C = 8;
constexpr index_t HI = 28;
constexpr index_t WI = 28;
constexpr index_t K = 128;
constexpr index_t Y = 3;
constexpr index_t X = 3;
constexpr index_t HPad = 0;
constexpr index_t WPad = 0;
#elif 0
#if 1
// 3x3, 34x34
constexpr index_t N = 64;
constexpr index_t C = 256;
......@@ -499,7 +483,7 @@ int main(int argc, char* argv[])
constexpr index_t HPad = 1;
constexpr index_t WPad = 1;
#elif 1
#elif 0
// 5x5 filter, 20x86 image
constexpr index_t N = 16;
constexpr index_t C = 256;
......@@ -547,7 +531,7 @@ int main(int argc, char* argv[])
constexpr index_t HPad = 0;
constexpr index_t WPad = 0;
#elif 10
#elif 0
// 1x1 filter, 14x14 image
constexpr index_t N = 128;
constexpr index_t C = 512;
......@@ -619,9 +603,9 @@ int main(int argc, char* argv[])
device_direct_convolution_2_nchw_kcyx_nkhw
#elif 0
device_direct_convolution_2_vectorized_nchw_kcyx_nkhw
#elif 1
device_convolution_implicit_gemm_v1_chwn_cyxk_khwn
#elif 0
device_convolution_implicit_gemm_v1_chwn_cyxk_khwn
#elif 1
device_convolution_implicit_gemm_v1_nchw_cyxk_khwn
#elif 0
device_convolution_implicit_gemm_v2_chwn_cyxk_khwn
......
src/include/Array.hip.hpp
View file @ 569ad66e
......@@ -19,6 +19,20 @@ struct Array
__host__ __device__ const TData& operator[](index_t i) const { return mData[i]; }
__host__ __device__ TData& operator[](index_t i) { return mData[i]; }
__host__ __device__ auto PushBack(TData x) const
{
Array<TData, NSize + 1> new_array;
static_for<0, NSize, 1>{}([=](auto I) {
constexpr index_t i = I.Get();
new_array[i] = mData[i];
});
new_array[NSize] = x;
return new_array;
}
};
template <class TData, index_t NSize, index_t... IRs>
......
src/include/ConstantTensorDescriptor.hip.hpp
View file @ 569ad66e
#pragma once
#include "common.hip.hpp"
// this is ugly, only for 2d
template <index_t L0, index_t L1>
__host__ __device__ constexpr auto calculate_default_strides(Sequence<L0, L1>)
template <class PreviousStrides, class RemainLengths>
__host__ __device__ constexpr auto calculate_default_strides_impl(PreviousStrides, RemainLengths)
{
return Sequence<L1, 1>{};
}
constexpr index_t previous_stride = PreviousStrides{}.Front();
constexpr index_t current_length = RemainLengths{}.Back();
constexpr index_t current_stride = current_length * previous_stride;
// this is ugly, only for 3d
template <index_t L0, index_t L1, index_t L2>
__host__ __device__ constexpr auto calculate_default_strides(Sequence<L0, L1, L2>)
{
return Sequence<L1 * L2, L2, 1>{};
return calculate_default_strides_impl(PreviousStrides{}.PushFront(Number<current_stride>{}),
RemainLengths{}.PopBack());
}
// this is ugly, only for 4d
template <index_t L0, index_t L1, index_t L2, index_t L3>
__host__ __device__ constexpr auto calculate_default_strides(Sequence<L0, L1, L2, L3>)
template <class PreviousStrides, index_t L0, index_t L1>
__host__ __device__ constexpr auto calculate_default_strides_impl(PreviousStrides, Sequence<L0, L1>)
{
return Sequence<L1 * L2 * L3, L2 * L3, L3, 1>{};
}
constexpr index_t previous_stride = PreviousStrides{}.Front();
constexpr index_t current_stride = L1 * previous_stride;
// this is ugly, only for 6d
template <index_t L0, index_t L1, index_t L2, index_t L3, index_t L4, index_t L5>
__host__ __device__ constexpr auto calculate_default_strides(Sequence<L0, L1, L2, L3, L4, L5>)
{
return Sequence<L1 * L2 * L3 * L4 * L5, L2 * L3 * L4 * L5, L3 * L4 * L5, L4 * L5, L5, 1>{};
return PreviousStrides{}.PushFront(Number<current_stride>{});
}
// this is ugly, only for 8d
template <index_t L0,
index_t L1,
index_t L2,
index_t L3,
index_t L4,
index_t L5,
index_t L6,
index_t L7>
__host__ __device__ constexpr auto
calculate_default_strides(Sequence<L0, L1, L2, L3, L4, L5, L6, L7>)
{
return Sequence<L1 * L2 * L3 * L4 * L5 * L6 * L7,
L2 * L3 * L4 * L5 * L6 * L7,
L3 * L4 * L5 * L6 * L7,
L4 * L5 * L6 * L7,
L5 * L6 * L7,
L6 * L7,
L7,
1>{};
}
// this is ugly, only for 8d
template <index_t L0,
index_t L1,
index_t L2,
index_t L3,
index_t L4,
index_t L5,
index_t L6,
index_t L7,
index_t L8,
index_t L9>
__host__ __device__ constexpr auto
calculate_default_strides(Sequence<L0, L1, L2, L3, L4, L5, L6, L7, L8, L9>)
template <class Lengths>
__host__ __device__ constexpr auto calculate_default_strides(Lengths)
{
return Sequence<L1 * L2 * L3 * L4 * L5 * L6 * L7 * L8 * L9,
L2 * L3 * L4 * L5 * L6 * L7 * L8 * L9,
L3 * L4 * L5 * L6 * L7 * L8 * L9,
L4 * L5 * L6 * L7 * L8 * L9,
L5 * L6 * L7 * L8 * L9,
L6 * L7 * L8 * L9,
L7 * L8 * L9,
L8 * L9,
L9,
1>{};
return calculate_default_strides_impl(Sequence<1>{}, Lengths{});
}
// this is ugly, only for 2d
......@@ -186,6 +136,14 @@ struct ConstantTensorDescriptor
return Get1dIndex(multi_id);
}
template <index_t... Is>
__host__ __device__ static constexpr index_t Get1dIndex(Sequence<Is...> multi_id)
{
static_assert(sizeof...(Is) == nDim, "wrong! Dimension not consistent");
return Get1dIndex(Is...);
}
__host__ __device__ static Array<index_t, nDim> GetMultiIndex(index_t id)
{
Array<index_t, nDim> multi_id;
......
src/include/Sequence.hip.hpp
View file @ 569ad66e
......@@ -34,11 +34,15 @@ struct Sequence
template <index_t... IRs>
__host__ __device__ constexpr auto ReorderGivenOld2New(Sequence<IRs...> /*old2new*/) const
{
// don't know how to implement this
// TODO: don't know how to implement this
printf("Sequence::ReorderGivenOld2New not implemented");
assert(false);
}
__host__ __device__ constexpr index_t Front() const { return mData[0]; }
__host__ __device__ constexpr index_t Back() const { return mData[mSize - 1]; }
template <index_t I>
__host__ __device__ constexpr auto PushFront(Number<I>) const
{
......@@ -69,15 +73,98 @@ __host__ __device__ constexpr auto sequence_pop_front(Sequence<I, Is...>)
return Sequence<Is...>{};
}
template <index_t... Is, index_t I>
#if 0
// TODO: for some reason, compiler cannot instantiate this template
template <index_t I, index_t... Is>
__host__ __device__ constexpr auto sequence_pop_back(Sequence<Is..., I>)
{
static_assert(sizeof...(Is) > 0, "empty Sequence!");
return Sequence<Is...>{};
}
#else
// TODO: delete these very ugly mess
template <index_t I0, index_t I1>
__host__ __device__ constexpr auto sequence_pop_back(Sequence<I0, I1>)
{
return Sequence<I0>{};
}
template <index_t I0, index_t I1, index_t I2>
__host__ __device__ constexpr auto sequence_pop_back(Sequence<I0, I1, I2>)
{
return Sequence<I0, I1>{};
}
template <index_t I0, index_t I1, index_t I2, index_t I3>
__host__ __device__ constexpr auto sequence_pop_back(Sequence<I0, I1, I2, I3>)
{
return Sequence<I0, I1, I2>{};
}
template <index_t I0, index_t I1, index_t I2, index_t I3, index_t I4>
__host__ __device__ constexpr auto sequence_pop_back(Sequence<I0, I1, I2, I3, I4>)
{
return Sequence<I0, I1, I2, I3>{};
}
template <index_t I0, index_t I1, index_t I2, index_t I3, index_t I4, index_t I5>
__host__ __device__ constexpr auto sequence_pop_back(Sequence<I0, I1, I2, I3, I4, I5>)
{
return Sequence<I0, I1, I2, I3, I4>{};
}
template <index_t I0, index_t I1, index_t I2, index_t I3, index_t I4, index_t I5, index_t I6>
__host__ __device__ constexpr auto sequence_pop_back(Sequence<I0, I1, I2, I3, I4, I5, I6>)
{
return Sequence<I0, I1, I2, I3, I4, I5>{};
}
template <index_t I0,
index_t I1,
index_t I2,
index_t I3,
index_t I4,
index_t I5,
index_t I6,
index_t I7>
__host__ __device__ constexpr auto sequence_pop_back(Sequence<I0, I1, I2, I3, I4, I5, I6, I7>)
{
return Sequence<I0, I1, I2, I3, I4, I5, I6>{};
}
template <index_t I0,
index_t I1,
index_t I2,
index_t I3,
index_t I4,
index_t I5,
index_t I6,
index_t I7,
index_t I8>
__host__ __device__ constexpr auto sequence_pop_back(Sequence<I0, I1, I2, I3, I4, I5, I6, I7, I8>)
{
return Sequence<I0, I1, I2, I3, I4, I5, I6, I7>{};
}
template <index_t I0,
index_t I1,
index_t I2,
index_t I3,
index_t I4,
index_t I5,
index_t I6,
index_t I7,
index_t I8,
index_t I9>
__host__ __device__ constexpr auto
sequence_pop_back(Sequence<I0, I1, I2, I3, I4, I5, I6, I7, I8, I9>)
{
return Sequence<I0, I1, I2, I3, I4, I5, I6, I7, I8>{};
}
#endif
#if 1
// this is ugly, only for 2 sequences
// TODO: fix these mess
template <class F, index_t... Xs, index_t... Ys>
__host__ __device__ constexpr auto transform_sequences(F f, Sequence<Xs...>, Sequence<Ys...>)
{
......@@ -86,7 +173,6 @@ __host__ __device__ constexpr auto transform_sequences(F f, Sequence<Xs...>, Seq
return Sequence<f(Xs, Ys)...>{};
}
// this is ugly, only for 3 sequences
template <class F, index_t... Xs, index_t... Ys, index_t... Zs>
__host__ __device__ constexpr auto
transform_sequences(F f, Sequence<Xs...>, Sequence<Ys...>, Sequence<Zs...>)
......@@ -98,6 +184,7 @@ transform_sequences(F f, Sequence<Xs...>, Sequence<Ys...>, Sequence<Zs...>)
return Sequence<f(Xs, Ys, Zs)...>{};
}
#else
// TODO:: these doesn't compile
template <index_t NRemain>
struct transform_sequences_impl
{
......
src/include/blockwise_4d_tensor_op.hip.hpp
View file @ 569ad66e
#pragma once
#include "ConstantTensorDescriptor.hip.hpp"
#include "threadwise_nd_tensor_op.hip.hpp"
template <index_t BlockSize, class Float, class DstDesc, class F>
__device__ void
......@@ -957,6 +958,7 @@ struct Blockwise4dTensorCopyReorder3
constexpr auto thread_sub_tensor_desc =
make_ConstantTensorDescriptor(SrcClusterLengths{}, thread_tensor_desc.GetStrides());
#if 1
for(index_t icluster_d0 = 0; icluster_d0 < cluster_per_dims.Get(I0); ++icluster_d0)
{
for(index_t icluster_d1 = 0; icluster_d1 < cluster_per_dims.Get(I1); ++icluster_d1)
......@@ -978,7 +980,7 @@ struct Blockwise4dTensorCopyReorder3
icluster_d2 * thread_sub_tensor_lengths.Get(I2),
icluster_d3 * thread_sub_tensor_lengths.Get(I3));
threadwise_4d_tensor_copy_v2(SrcDesc{},
threadwise_nd_tensor_copy(SrcDesc{},
p_src + src_offset + mSrcMyThreadOffset,
thread_tensor_desc,
p_clipboard + clipboard_offset,
......@@ -988,6 +990,11 @@ struct Blockwise4dTensorCopyReorder3
}
}
}
#else
static_ford<decltype(cluster_per_dims)>{}([=](auto cluster_ids) {
});
#endif
#if 0
if(get_block_1d_id() == 0)
......
src/include/blockwise_batched_gemm.hip.hpp
View file @ 569ad66e
......@@ -254,8 +254,22 @@ struct BlockwiseBatchGemmBlockABlockBThreadCTransANormalBNormalC_V2
if(get_thread_local_1d_id() == 0 && get_block_1d_id() == 0)
{
printf("a: %f %f %f %f %f %f %f %f, b: %f %f %f %f %f %f %f %f\n",
p_a_thread[0], p_a_thread[1], p_a_thread[2], p_a_thread[3], p_a_thread[4], p_a_thread[5], p_a_thread[6], p_a_thread[7],
p_b_thread[0], p_b_thread[1], p_b_thread[2], p_b_thread[3], p_b_thread[4], p_b_thread[5], p_b_thread[6], p_b_thread[7]);
p_a_thread[0],
p_a_thread[1],
p_a_thread[2],
p_a_thread[3],
p_a_thread[4],
p_a_thread[5],
p_a_thread[6],
p_a_thread[7],
p_b_thread[0],
p_b_thread[1],
p_b_thread[2],
p_b_thread[3],
p_b_thread[4],
p_b_thread[5],
p_b_thread[6],
p_b_thread[7]);
}
#endif
......
src/include/common.hip.hpp
View file @ 569ad66e
......@@ -4,6 +4,7 @@
#include "Sequence.hip.hpp"
#include "Array.hip.hpp"
#include "functional.hip.hpp"
#include "functional2.hip.hpp"
#if DEVICE_BACKEND_HIP
#include "amd_inline_asm.hip.hpp"
......
src/include/functional.hip.hpp
View file @ 569ad66e
......@@ -21,7 +21,7 @@ struct static_for_impl<Iter, 0, Increment>
template <class F>
__host__ __device__ void operator()(F) const
{
// do nothing
// no work left, just return
return;
}
};
......@@ -48,7 +48,7 @@ struct static_const_reduce_n
static_assert(NLoop > 1, "out-of-range");
constexpr auto a = f(Number<NLoop - 1>{});
auto b = static_const_reduce_n<NLoop - 1>{}(f, r); // cannot use constexpr here, weird
auto b = static_const_reduce_n<NLoop - 1>{}(f, r); // TODO: cannot use constexpr here, weird
return r(a, b);
}
};
......@@ -70,3 +70,65 @@ __host__ __device__ constexpr auto unpacker(F f)
return [=](auto xs_array){ f(xs...); };
}
#endif
struct forwarder
{
template <typename T>
__host__ __device__ constexpr T operator()(T&& x) const
{
return std::forward<T>(x);
}
};
// Emulate compile time if statement for C++14
// Get the idea from
// "https://baptiste-wicht.com/posts/2015/07/simulate-static_if-with-c11c14.html"
// TODO: use if constexpr, when C++17 is supported
template <bool Predicate>
struct static_if
{
};
template <>
struct static_if<true>
{
using Type = static_if<true>;
template <class F>
__host__ __device__ constexpr auto operator()(F f) const
{
// This is a trick for compiler:
// Pass forwarder to lambda "f" as "auto" argument, and maks sure "f" will use it,
// this will make "f" a generic lambda, so that "f" won't be compiled until here
f(forwarder{});
return Type{};
}
template <class F>
__host__ __device__ static constexpr auto else_(F)
{
return Type{};
}
};
template <>
struct static_if<false>
{
using Type = static_if<false>;
template <class F>
__host__ __device__ constexpr auto operator()(F) const
{
return Type{};
}
template <class F>
__host__ __device__ static constexpr auto else_(F f)
{
// This is a trick for compiler:
// Pass forwarder to lambda "f" as "auto" argument, and maks sure "f" will use it,
// this will make "f" a generic lambda, so that "f" won't be compiled until here
f(forwarder{});
return Type{};
}
};
src/include/functional2.hip.hpp 0 → 100644
View file @ 569ad66e
#pragma once
#include "Sequence.hip.hpp"
template <index_t RemainDim>
struct static_ford_impl
{
// F signature: F(Sequence<...> multi_id)
// CurrentMultiIndex: Sequence<...>
// RemainLengths: Sequence<...>
template <class F, class CurrentMultiIndex, class RemainLengths>
__host__ __device__ void operator()(F f, CurrentMultiIndex, RemainLengths) const
{
static_assert(RemainLengths::GetSize() == RemainDim, "wrong!");
static_assert(RemainDim > 1, "wrong!");
constexpr auto next_length = RemainLengths{}.Front();
static_for<0, next_length, 1>{}([=](auto I) {
static_ford_impl<RemainDim - 1>{}(
f, CurrentMultiIndex{}.PushBack(I), RemainLengths{}.PopFront());
});
}
};
template <>
struct static_ford_impl<1>
{
// F signature: F(Sequence<Is...> multi_id)
// CurrentMultiIndex: Sequence<...>
// RemainLengths: Sequence<...>
template <class F, class CurrentMultiIndex, class RemainLengths>
__host__ __device__ void operator()(F f, CurrentMultiIndex, RemainLengths) const
{
static_assert(RemainLengths::GetSize() == 1, "wrong!");
constexpr index_t last_length = RemainLengths{}.Front();
static_for<0, last_length, 1>{}([=](auto I) { f(CurrentMultiIndex{}.PushBack(I)); });
}
};
// Lengths is Sequence<...>
template <class Lengths>
struct static_ford
{
// F signature: F(Sequence<Is...> multi_id)
template <class F>
__host__ __device__ void operator()(F f) const
{
constexpr index_t first_length = Lengths{}.Front();
static_for<0, first_length, 1>{}([=](auto I) {
static_ford_impl<Lengths::GetSize() - 1>{}(
f, Sequence<I.Get()>{}, Lengths{}.PopFront());
});
}
};
template <index_t RemainDim>
struct ford_impl
{
// F signature: F(Array<...> multi_id)
// CurrentMultiIndex: Array<...>
// RemainLengths: Sequence<...>
template <class F, class CurrentMultiIndex, class RemainLengths>
__host__ __device__ void
operator()(F f, CurrentMultiIndex current_multi_id, RemainLengths) const
{
static_assert(RemainLengths::GetSize() == RemainDim, "wrong!");
static_assert(RemainDim > 1, "wrong!");
constexpr auto next_length = RemainLengths{}.Front();
for(index_t i = 0; i < next_length; ++i)
{
ford_impl<RemainDim - 1>{}(f, current_multi_id.PushBack(i), RemainLengths{}.PopFront());
}
}
};
template <>
struct ford_impl<1>
{
// F signature: F(Array<...> multi_id)
// CurrentMultiIndex: Array<...>
// RemainLengths: Sequence<...>
template <class F, class CurrentMultiIndex, class RemainLengths>
__host__ __device__ void
operator()(F f, CurrentMultiIndex current_multi_id, RemainLengths) const
{
static_assert(RemainLengths::GetSize() == 1, "wrong!");
constexpr index_t last_length = RemainLengths{}.Front();
for(index_t i = 0; i < last_length; ++i)
{
f(current_multi_id.PushBack(i));
}
}
};
// Lengths is Sequence<...>
template <class Lengths>
struct ford
{
// F signature: F(Array<...> multi_id)
template <class F>
__host__ __device__ void operator()(F f) const
{
constexpr index_t first_length = Lengths{}.Front();
for(index_t i = 0; i < first_length; ++i)
{
ford_impl<Lengths::GetSize() - 1>{}(f, Array<index_t, 1>{i}, Lengths{}.PopFront());
}
}
};
src/include/gridwise_convolution_implicit_gemm_v1r1_chwn_cyxk_khwn.hip.hpp
View file @ 569ad66e
......@@ -32,10 +32,10 @@ template <index_t GridSize,
index_t GemmKPerThreadLoop,
index_t GemmDataPerReadA,
index_t GemmDataPerReadB,
class InBlockCopyThreadPerDims,
index_t InBlockCopyDataPerRead,
index_t WeiBlockCopyDataPerRead,
index_t OutThreadCopyDataPerWrite>
class InBlockCopyClusterLengths_CHWN,
index_t InBlockCopyDataPerRead_N,
index_t WeiBlockCopyDataPerRead_K,
index_t OutThreadCopyDataPerWrite_N>
struct GridwiseConvolutionImplicitGemm_v1r1_chwn_cyxk_khwn
{
__device__ void Run(const Float* const __restrict__ p_in_global,
......@@ -43,28 +43,30 @@ struct GridwiseConvolutionImplicitGemm_v1r1_chwn_cyxk_khwn
Float* const __restrict__ p_out_global) const
{
// be careful of this assertion
static_assert(
NPerThread <= NPerBlock && NPerBlock % NPerThread == 0,
"wrong! should satisfy: NPerThread <= NPerBlock && NPerBlock % NPerThread == 0");
static_assert(NPerBlock % NPerThread == 0 && (GemmNPerThreadSubC <= NPerBlock &&
NPerBlock % GemmNPerThreadSubC == 0) ||
(GemmNPerThreadSubC >= NPerBlock && NPerThread == NPerBlock &&
GemmNPerThreadSubC % NPerThread == 0),
"wrong!");
constexpr auto I0 = Number<0>{};
constexpr auto I1 = Number<1>{};
constexpr auto I2 = Number<2>{};
constexpr auto I3 = Number<3>{};
constexpr auto in_chwn_global_desc = InGlobalDesc{};
constexpr auto wei_cyxk_global_desc = WeiGlobalDesc{};
constexpr auto out_khwn_global_desc = OutGlobalDesc{};
constexpr auto in_c_h_w_n_global_desc = InGlobalDesc{};
constexpr auto wei_c_y_x_k_global_desc = WeiGlobalDesc{};
constexpr auto out_k_h_w_n_global_desc = OutGlobalDesc{};
constexpr index_t C = in_chwn_global_desc.GetLength(I0);
constexpr index_t C = in_c_h_w_n_global_desc.GetLength(I0);
constexpr index_t K = out_khwn_global_desc.GetLength(I0);
constexpr index_t Ho = out_khwn_global_desc.GetLength(I1);
constexpr index_t Wo = out_khwn_global_desc.GetLength(I2);
constexpr index_t N = out_khwn_global_desc.GetLength(I3);
constexpr index_t K = out_k_h_w_n_global_desc.GetLength(I0);
constexpr index_t Ho = out_k_h_w_n_global_desc.GetLength(I1);
constexpr index_t Wo = out_k_h_w_n_global_desc.GetLength(I2);
constexpr index_t N = out_k_h_w_n_global_desc.GetLength(I3);
constexpr index_t Y = wei_cyxk_global_desc.GetLength(I1);
constexpr index_t X = wei_cyxk_global_desc.GetLength(I2);
constexpr index_t Y = wei_c_y_x_k_global_desc.GetLength(I1);
constexpr index_t X = wei_c_y_x_k_global_desc.GetLength(I2);
constexpr index_t HiPerBlock = HoPerBlock + Y - 1;
constexpr index_t WiPerBlock = WoPerBlock + X - 1;
......@@ -95,24 +97,35 @@ struct GridwiseConvolutionImplicitGemm_v1r1_chwn_cyxk_khwn
const index_t wi_block_data_begin = wo_block_data_begin;
// flattend (2d) tensor view of gridwise weight
constexpr auto wei_ek_global_desc = make_ConstantTensorDescriptor(Sequence<C * Y * X, K>{});
constexpr auto wei_cyx_k_global_desc =
make_ConstantTensorDescriptor(Sequence<C * Y * X, K>{});
// tensor view of blockwise input and weight in LDS
// be careful of alignment
constexpr index_t max_align = mod_conv::max(
InBlockCopyDataPerRead, WeiBlockCopyDataPerRead, GemmDataPerReadA, GemmDataPerReadB);
constexpr index_t max_align = mod_conv::max(InBlockCopyDataPerRead_N,
WeiBlockCopyDataPerRead_K,
GemmDataPerReadA,
GemmDataPerReadB);
constexpr auto in_c_h_w_n_block_desc = make_ConstantTensorDescriptor_aligned(
Sequence<CPerBlock, HiPerBlock, WiPerBlock, NPerBlock>{},
Number<InBlockCopyDataPerRead_N>{});
constexpr auto in_chwn_block_desc = make_ConstantTensorDescriptor_aligned(
Sequence<CPerBlock, HiPerBlock, WiPerBlock, NPerBlock>{}, Number<max_align>{});
// this check is ad-hoc
// TODO: need to properly implement tensor descriptor with alignment
static_assert(in_c_h_w_n_block_desc.GetStride(I1) % GemmDataPerReadB == 0,
"GemmDataPerReadB alignment requirement is not meet");
constexpr auto wei_ek_block_desc = make_ConstantTensorDescriptor_aligned(
Sequence<CPerBlock * Y * X, KPerBlock>{}, Number<max_align>{});
constexpr auto wei_cyx_k_block_desc = make_ConstantTensorDescriptor_aligned(
Sequence<CPerBlock * Y * X, KPerBlock>{},
Number<mod_conv::max(WeiBlockCopyDataPerRead_K, GemmDataPerReadA)>{});
constexpr auto wei_cyxk_block_desc = make_ConstantTensorDescriptor_aligned(
Sequence<CPerBlock, Y, X, KPerBlock>{}, Number<max_align>{});
constexpr auto wei_c_y_x_k_block_desc = make_ConstantTensorDescriptor_aligned(
Sequence<CPerBlock, Y, X, KPerBlock>{},
Number<mod_conv::max(WeiBlockCopyDataPerRead_K, GemmDataPerReadA)>{});
// tensor view of threadwise output in register
constexpr auto out_khwn_thread_desc = make_ConstantTensorDescriptor(
constexpr auto out_k_h_w_n_thread_desc = make_ConstantTensorDescriptor(
Sequence<KPerThread, HoPerThread, WoPerThread, NPerThread>{});
// blockwise copy
......@@ -121,18 +134,18 @@ struct GridwiseConvolutionImplicitGemm_v1r1_chwn_cyxk_khwn
#if 0
Blockwise4dTensorCopy1<BlockSize,
Float,
decltype(in_chwn_global_desc),
decltype(in_chwn_block_desc),
decltype(in_chwn_block_desc.GetLengths()),
InBlockCopyDataPerRead>{};
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()),
InBlockCopyDataPerRead_N>{};
#else
Blockwise4dTensorCopy3<BlockSize,
Float,
decltype(in_chwn_global_desc),
decltype(in_chwn_block_desc),
decltype(in_chwn_block_desc.GetLengths()),
InBlockCopyThreadPerDims,
InBlockCopyDataPerRead>{};
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()),
InBlockCopyClusterLengths_CHWN,
InBlockCopyDataPerRead_N>{};
#endif
// blockwise wei copy
......@@ -140,10 +153,10 @@ struct GridwiseConvolutionImplicitGemm_v1r1_chwn_cyxk_khwn
const auto blockwise_wei_copy =
Blockwise2dTensorCopy3<BlockSize,
Float,
decltype(wei_ek_global_desc),
decltype(wei_ek_block_desc),
decltype(wei_ek_block_desc.GetLengths()),
WeiBlockCopyDataPerRead>{};
decltype(wei_cyx_k_global_desc),
decltype(wei_cyx_k_block_desc),
decltype(wei_cyx_k_block_desc.GetLengths()),
WeiBlockCopyDataPerRead_K>{};
// a series of blockwise batched GEMM
// C_matrix += transpose(A_matrix) * B_matrix
......@@ -151,28 +164,30 @@ struct GridwiseConvolutionImplicitGemm_v1r1_chwn_cyxk_khwn
// A_matrix[C,K] is a sub-matrix of wei_block[C,Y,X,K]
// B_matrix[C,Wo*N] is a sub-matrix of in_block[C,Hi,Wi,N]
// C_matrix[K,Wo*N] is a sub-matrix of out_block[K,Ho,Wo,N]
constexpr auto a_cxk_block_mtx_desc = make_ConstantMatrixDescriptor(
Number<CPerBlock>{}, Number<KPerBlock>{}, Number<wei_cyxk_block_desc.GetStride(I0)>{});
constexpr auto a_c_k_block_mtx_desc =
make_ConstantMatrixDescriptor(Number<CPerBlock>{},
Number<KPerBlock>{},
Number<wei_c_y_x_k_block_desc.GetStride(I0)>{});
constexpr auto b_cxwn_block_mtx_desc =
constexpr auto b_c_wn_block_mtx_desc =
make_ConstantMatrixDescriptor(Number<CPerBlock>{},
Number<WoPerBlock * NPerBlock>{},
Number<in_chwn_block_desc.GetStride(I0)>{});
Number<in_c_h_w_n_block_desc.GetStride(I0)>{});
constexpr auto c_kxwn_thread_mtx_desc =
constexpr auto c_k_wn_thread_mtx_desc =
make_ConstantMatrixDescriptor(Number<KPerThread>{},
Number<WoPerThread * NPerThread>{},
Number<out_khwn_thread_desc.GetStride(I0)>{});
Number<out_k_h_w_n_thread_desc.GetStride(I0)>{});
const auto blockwise_batch_gemm =
BlockwiseBatchGemmBlockABlockBThreadCTransANormalBNormalC_V2<
BlockSize,
decltype(a_cxk_block_mtx_desc),
decltype(b_cxwn_block_mtx_desc),
decltype(c_kxwn_thread_mtx_desc),
decltype(a_c_k_block_mtx_desc),
decltype(b_c_wn_block_mtx_desc),
decltype(c_k_wn_thread_mtx_desc),
0,
in_chwn_block_desc.GetStride(I1),
out_khwn_thread_desc.GetStride(I1),
in_c_h_w_n_block_desc.GetStride(I1),
out_k_h_w_n_thread_desc.GetStride(I1),
HoPerBlock,
GemmMPerThreadSubC,
GemmNPerThreadSubC,
......@@ -186,30 +201,33 @@ struct GridwiseConvolutionImplicitGemm_v1r1_chwn_cyxk_khwn
GemmDataPerReadB>{};
// LDS: be careful of alignment
constexpr index_t in_block_space = in_chwn_block_desc.GetElementSpace(Number<max_align>{});
constexpr index_t in_block_space =
in_c_h_w_n_block_desc.GetElementSpace(Number<max_align>{});
constexpr index_t wei_block_space =
wei_cyxk_block_desc.GetElementSpace(Number<max_align>{});
wei_c_y_x_k_block_desc.GetElementSpace(Number<max_align>{});
__shared__ Float p_in_block[in_block_space];
__shared__ Float p_wei_block[wei_block_space];
// register
Float p_out_thread[out_khwn_thread_desc.GetElementSpace()];
// C++ lambda doesn't capture array, use pointer instead
Float p_out_thread_data[out_k_h_w_n_thread_desc.GetElementSpace()];
Float* const p_out_thread = p_out_thread_data;
// set threadwise output tensor to 0
threadwise_4d_tensor_set_zero(out_khwn_thread_desc, p_out_thread);
threadwise_4d_tensor_set_zero(out_k_h_w_n_thread_desc, p_out_thread);
const Float* p_in_global_block_offset =
p_in_global + in_chwn_global_desc.Get1dIndex(
p_in_global + in_c_h_w_n_global_desc.Get1dIndex(
0, hi_block_data_begin, wi_block_data_begin, n_block_data_begin);
const Float* p_wei_global_block_offset =
p_wei_global + wei_cyxk_global_desc.Get1dIndex(0, 0, 0, k_block_data_begin);
p_wei_global + wei_c_y_x_k_global_desc.Get1dIndex(0, 0, 0, k_block_data_begin);
for(index_t c_block_data_begin = 0; c_block_data_begin < C; c_block_data_begin += CPerBlock,
p_in_global_block_offset += CPerBlock * in_chwn_global_desc.GetStride(I0),
p_wei_global_block_offset += CPerBlock * wei_cyxk_global_desc.GetStride(I0),
p_in_global_block_offset += CPerBlock * in_c_h_w_n_global_desc.GetStride(I0),
p_wei_global_block_offset += CPerBlock * wei_c_y_x_k_global_desc.GetStride(I0),
__syncthreads())
{
#if 1
......@@ -241,71 +259,52 @@ struct GridwiseConvolutionImplicitGemm_v1r1_chwn_cyxk_khwn
#else
blockwise_batch_gemm.Run_asm
#endif
(p_wei_block + wei_cyxk_block_desc.Get1dIndex(0, y, x, 0),
p_in_block + in_chwn_block_desc.Get1dIndex(0, y, x, 0),
(p_wei_block + wei_c_y_x_k_block_desc.Get1dIndex(0, y, x, 0),
p_in_block + in_c_h_w_n_block_desc.Get1dIndex(0, y, x, 0),
p_out_thread);
}
}
}
// output: register to global mem,
#if 0
const auto c_thread_mtx_begin =
blockwise_batch_gemm.GetBeginOfThreadMatrixC(get_thread_local_1d_id());
for(index_t k = 0; k < out_khwn_thread_desc.GetLength(I0); ++k)
{
for(index_t ho = 0; ho < out_khwn_thread_desc.GetLength(I1); ++ho)
{
for(index_t wo = 0; wo < out_khwn_thread_desc.GetLength(I2); ++wo)
{
for(index_t n = 0; n < out_khwn_thread_desc.GetLength(I3); ++n)
{
const index_t b = out_khwn_thread_desc.Get1dIndex(0, 0, wo, n);
const auto c_thread_mtx_distance =
blockwise_batch_gemm.GetDistanceFromBeginOfThreadMatrixC(ho, k, b);
const index_t ho_thread =
c_thread_mtx_begin.batch + c_thread_mtx_distance.batch;
const index_t k_thread = c_thread_mtx_begin.row + c_thread_mtx_distance.row;
const index_t b_thread = c_thread_mtx_begin.col + c_thread_mtx_distance.col;
const index_t wo_thread = b_thread / NPerBlock;
const index_t n_thread = b_thread % NPerBlock;
p_out_global[out_khwn_global_desc.Get1dIndex(k_block_data_begin + k_thread,
ho_block_data_begin + ho_thread,
wo_block_data_begin + wo_thread,
n_block_data_begin + n_thread)] =
p_out_thread[out_khwn_thread_desc.Get1dIndex(k, ho, wo, n)];
}
}
}
}
#elif 1
// output: register to global mem,
const auto c_thread_mtx_begin =
blockwise_batch_gemm.GetBeginOfThreadMatrixC(get_thread_local_1d_id());
const index_t k_thread_data_begin = c_thread_mtx_begin.row;
const index_t ho_thread_data_begin = c_thread_mtx_begin.batch;
const index_t wo_thread_data_begin = c_thread_mtx_begin.col / NPerBlock;
const index_t n_thread_data_begin =
c_thread_mtx_begin.col - NPerBlock * wo_thread_data_begin;
const index_t n_thread_data_begin = c_thread_mtx_begin.col % NPerBlock;
static_if<GemmNPerThreadSubC <= NPerBlock>{}(
[&](auto f_dummy) { // f_dummy do nothing but perfect forwarding. Using this trick to
// make this lambda a generic lambda, so it won't be compiled until
// instantiated
static_assert((f_dummy(GemmNPerThreadSubC) <= NPerBlock &&
NPerBlock % GemmNPerThreadSubC == 0),
"wrong!");
// output is a 10d tensor
constexpr index_t N2 = GemmNPerThreadSubC;
constexpr index_t N1 = NPerBlock / N2;
constexpr index_t W2 =
(GemmNLevel0Cluster * GemmNLevel1Cluster) / (NPerBlock / GemmNPerThreadSubC);
constexpr index_t W2 = (GemmNLevel0Cluster * GemmNLevel1Cluster) /
f_dummy(NPerBlock / GemmNPerThreadSubC);
constexpr index_t W1 = WoPerBlock / W2;
constexpr index_t K2 = GemmMPerThreadSubC;
constexpr index_t K1 = KPerBlock / KPerThread;
constexpr auto out_10d_global_desc = make_ConstantTensorDescriptor(
Sequence<K / (K1 * K2), K1, K2, Ho, Wo / (W1 * W2), W1, W2, N / (N1 * N2), N1, N2>{});
constexpr auto out_10d_global_desc =
make_ConstantTensorDescriptor(Sequence<K / (K1 * K2),
K1,
K2,
Ho,
Wo / (W1 * W2),
W1,
W2,
N / f_dummy(N1 * N2),
N1,
N2>{});
constexpr auto out_10d_thread_desc = make_ConstantTensorDescriptor(
Sequence<KPerThread / K2, 1, K2, HoPerThread, 1, W1, 1, 1, 1, N2>{});
......@@ -313,24 +312,87 @@ struct GridwiseConvolutionImplicitGemm_v1r1_chwn_cyxk_khwn
#if 0
if(get_thread_local_1d_id() == 0 && get_block_1d_id() == 0)
{
print_ConstantTensorDescriptor(out_khwn_thread_desc, "out_khwn_thread_desc");
print_ConstantTensorDescriptor(out_k_h_w_n_thread_desc,
"out_k_h_w_n_thread_desc");
print_ConstantTensorDescriptor(out_10d_thread_desc, "out_10d_thread_desc");
print_ConstantTensorDescriptor(out_khwn_global_desc, "out_khwn_global_desc");
print_ConstantTensorDescriptor(out_k_h_w_n_global_desc,
"out_k_h_w_n_global_desc");
print_ConstantTensorDescriptor(out_10d_global_desc, "out_10d_global_desc");
}
#endif
threadwise_10d_tensor_copy(out_10d_thread_desc,
threadwise_nd_tensor_copy(out_10d_thread_desc,
p_out_thread,
out_10d_global_desc,
p_out_global + out_khwn_global_desc.Get1dIndex(
p_out_global +
out_k_h_w_n_global_desc.Get1dIndex(
k_block_data_begin + k_thread_data_begin,
ho_block_data_begin + ho_thread_data_begin,
wo_block_data_begin + wo_thread_data_begin,
n_block_data_begin + n_thread_data_begin),
out_10d_thread_desc.GetLengths(),
Number<OutThreadCopyDataPerWrite>{});
Number<OutThreadCopyDataPerWrite_N>{});
})
.else_([&](auto f_dummy) {
static_assert(f_dummy(GemmNPerThreadSubC) >= NPerBlock && NPerThread == NPerBlock &&
GemmNPerThreadSubC % NPerThread == 0,
"wrong!");
// output is a 10d tensor
constexpr index_t N1 = NPerBlock;
constexpr index_t W3 = GemmNPerThreadSubC / NPerBlock;
constexpr index_t W2 = GemmNLevel0Cluster * GemmNLevel1Cluster;
constexpr index_t W1 = WoPerBlock / f_dummy(W2 * W3);
constexpr index_t K2 = GemmMPerThreadSubC;
constexpr index_t K1 = KPerBlock / KPerThread;
constexpr auto out_10d_global_desc =
make_ConstantTensorDescriptor(Sequence<K / (K1 * K2),
K1,
K2,
Ho,
Wo / (W1 * W2 * W3),
W1,
W2,
W3,
N / N1,
N1>{});
constexpr auto out_10d_thread_desc = make_ConstantTensorDescriptor(
Sequence<KPerThread / K2, 1, K2, HoPerThread, 1, W1, 1, W3, 1, N1>{});
#if 0
if(get_thread_local_1d_id() == 0 && get_block_1d_id() == 0)
{
print_ConstantTensorDescriptor(out_k_h_w_n_thread_desc,
"out_k_h_w_n_thread_desc");
print_ConstantTensorDescriptor(out_10d_thread_desc, "out_10d_thread_desc");
print_ConstantTensorDescriptor(out_k_h_w_n_global_desc,
"out_k_h_w_n_global_desc");
print_ConstantTensorDescriptor(out_10d_global_desc, "out_10d_global_desc");
for(index_t i = 0; i < 64; ++i)
{
printf("out %f, ", p_out_thread[i]);
}
}
#endif
threadwise_nd_tensor_copy(out_10d_thread_desc,
p_out_thread,
out_10d_global_desc,
p_out_global +
out_k_h_w_n_global_desc.Get1dIndex(
k_block_data_begin + k_thread_data_begin,
ho_block_data_begin + ho_thread_data_begin,
wo_block_data_begin + wo_thread_data_begin,
n_block_data_begin + n_thread_data_begin),
out_10d_thread_desc.GetLengths(),
Number<OutThreadCopyDataPerWrite_N>{});
});
}
};
src/include/gridwise_convolution_implicit_gemm_v1r1_lds_double_buffer_chwn_cyxk_khwn.hip.hpp deleted 100644 → 0
View file @ 87d8740b
#pragma once
#include "common.hip.hpp"
#include "ConstantTensorDescriptor.hip.hpp"
#include "ConstantMatrixDescriptor.hip.hpp"
#include "blockwise_4d_tensor_op.hip.hpp"
#include "blockwise_2d_tensor_op.hip.hpp"
#include "threadwise_nd_tensor_op.hip.hpp"
#include "threadwise_4d_tensor_op.hip.hpp"
#include "blockwise_batched_gemm.hip.hpp"
template <index_t GridSize,
index_t BlockSize,
class Float,
class InGlobalDesc,
class WeiGlobalDesc,
class OutGlobalDesc,
index_t NPerBlock,
index_t KPerBlock,
index_t CPerBlock,
index_t HoPerBlock,
index_t WoPerBlock,
index_t NPerThread,
index_t KPerThread,
index_t HoPerThread,
index_t WoPerThread,
index_t GemmMPerThreadSubC,
index_t GemmNPerThreadSubC,
index_t GemmMLevel0Cluster,
index_t GemmNLevel0Cluster,
index_t GemmMLevel1Cluster,
index_t GemmNLevel1Cluster,
index_t GemmKPerThreadLoop,
index_t GemmDataPerReadA,
index_t GemmDataPerReadB,
class InBlockCopyThreadPerDims,
index_t InBlockCopyDataPerRead,
index_t WeiBlockCopyDataPerRead,
index_t OutThreadCopyDataPerWrite>
struct GridwiseConvolutionImplicitGemm_v1r1_lds_double_buffer_chwn_cyxk_khwn
{
__device__ void Run(const Float* const __restrict__ p_in_global,
const Float* const __restrict__ p_wei_global,
Float* const __restrict__ p_out_global) const
{
// be careful of this assertion
static_assert(
NPerThread <= NPerBlock && NPerBlock % NPerThread == 0,
"wrong! should satisfy: NPerThread <= NPerBlock && NPerBlock % NPerThread == 0");
constexpr auto I0 = Number<0>{};
constexpr auto I1 = Number<1>{};
constexpr auto I2 = Number<2>{};
constexpr auto I3 = Number<3>{};
constexpr auto in_chwn_global_desc = InGlobalDesc{};
constexpr auto wei_cyxk_global_desc = WeiGlobalDesc{};
constexpr auto out_khwn_global_desc = OutGlobalDesc{};
constexpr index_t C = in_chwn_global_desc.GetLength(I0);
constexpr index_t K = out_khwn_global_desc.GetLength(I0);
constexpr index_t Ho = out_khwn_global_desc.GetLength(I1);
constexpr index_t Wo = out_khwn_global_desc.GetLength(I2);
constexpr index_t N = out_khwn_global_desc.GetLength(I3);
constexpr index_t Y = wei_cyxk_global_desc.GetLength(I1);
constexpr index_t X = wei_cyxk_global_desc.GetLength(I2);
constexpr index_t HiPerBlock = HoPerBlock + Y - 1;
constexpr index_t WiPerBlock = WoPerBlock + X - 1;
// assert for LDS double buffer
static_assert(C % (2 * CPerBlock) == 0, "C cannot be evenly divided");
// divide block work: [K, Ho, Wo, N]
static_assert(N % NPerBlock == 0 && K % KPerBlock == 0 && C % CPerBlock == 0 &&
Ho % HoPerBlock == 0 && Wo % WoPerBlock == 0,
"wrong! cannot evenly divide work for workgroup ");
constexpr index_t KBlockWork = (K + KPerBlock - 1) / KPerBlock;
constexpr index_t HBlockWork = (Ho + HoPerBlock - 1) / HoPerBlock;
constexpr index_t WBlockWork = (Wo + WoPerBlock - 1) / WoPerBlock;
constexpr index_t NBlockWork = (N + NPerBlock - 1) / NPerBlock;
const index_t k_block_work_id = get_block_1d_id() / (HBlockWork * WBlockWork * NBlockWork);
index_t itmp = get_block_1d_id() - k_block_work_id * (HBlockWork * WBlockWork * NBlockWork);
const index_t h_block_work_id = itmp / (WBlockWork * NBlockWork);
itmp -= h_block_work_id * (WBlockWork * NBlockWork);
const index_t w_block_work_id = itmp / NBlockWork;
const index_t n_block_work_id = itmp - w_block_work_id * NBlockWork;
const index_t k_block_data_begin = k_block_work_id * KPerBlock;
const index_t ho_block_data_begin = h_block_work_id * HoPerBlock;
const index_t wo_block_data_begin = w_block_work_id * WoPerBlock;
const index_t n_block_data_begin = n_block_work_id * NPerBlock;
const index_t hi_block_data_begin = ho_block_data_begin;
const index_t wi_block_data_begin = wo_block_data_begin;
// flattend (2d) tensor view of gridwise weight
constexpr auto wei_ek_global_desc = make_ConstantTensorDescriptor(Sequence<C * Y * X, K>{});
// tensor view of blockwise input and weight in LDS
// be careful of alignment
constexpr index_t max_align =
mod_conv::max(index_t(4), InBlockCopyDataPerRead, WeiBlockCopyDataPerRead);
constexpr auto in_chwn_block_desc = make_ConstantTensorDescriptor_aligned(
Sequence<CPerBlock, HiPerBlock, WiPerBlock, NPerBlock>{}, Number<max_align>{});
constexpr auto wei_ek_block_desc = make_ConstantTensorDescriptor_aligned(
Sequence<CPerBlock * Y * X, KPerBlock>{}, Number<max_align>{});
constexpr auto wei_cyxk_block_desc = make_ConstantTensorDescriptor_aligned(
Sequence<CPerBlock, Y, X, KPerBlock>{}, Number<max_align>{});
// tensor view of threadwise output in register
constexpr auto out_khwn_thread_desc = make_ConstantTensorDescriptor(
Sequence<KPerThread, HoPerThread, WoPerThread, NPerThread>{});
// blockwise copy
// input: format is [C, Hi, Wi, N]
const auto blockwise_in_copy =
Blockwise4dTensorCopy3<BlockSize,
Float,
decltype(in_chwn_global_desc),
decltype(in_chwn_block_desc),
decltype(in_chwn_block_desc.GetLengths()),
InBlockCopyThreadPerDims,
InBlockCopyDataPerRead>{};
// blockwise wei copy
// format is [CPerBlock*Y*X,KPerBlock]
const auto blockwise_wei_copy =
Blockwise2dTensorCopy3<BlockSize,
Float,
decltype(wei_ek_global_desc),
decltype(wei_ek_block_desc),
decltype(wei_ek_block_desc.GetLengths()),
WeiBlockCopyDataPerRead>{};
// a series of blockwise batched GEMM
// C_matrix += transpose(A_matrix) * B_matrix
// A_matrix and B_matrix saved in LDS, C_matrix saved in register
// A_matrix[C,K] is a sub-matrix of wei_block[C,Y,X,K]
// B_matrix[C,Wo*N] is a sub-matrix of in_block[C,Hi,Wi,N]
// C_matrix[K,Wo*N] is a sub-matrix of out_block[K,Ho,Wo,N]
constexpr auto a_cxk_block_mtx_desc = make_ConstantMatrixDescriptor(
Number<CPerBlock>{}, Number<KPerBlock>{}, Number<wei_cyxk_block_desc.GetStride(I0)>{});
constexpr auto b_cxwn_block_mtx_desc =
make_ConstantMatrixDescriptor(Number<CPerBlock>{},
Number<WoPerBlock * NPerBlock>{},
Number<in_chwn_block_desc.GetStride(I0)>{});
constexpr auto c_kxwn_thread_mtx_desc =
make_ConstantMatrixDescriptor(Number<KPerThread>{},
Number<WoPerThread * NPerThread>{},
Number<out_khwn_thread_desc.GetStride(I0)>{});
const auto blockwise_batch_gemm =
BlockwiseBatchGemmBlockABlockBThreadCTransANormalBNormalC_V2<
BlockSize,
decltype(a_cxk_block_mtx_desc),
decltype(b_cxwn_block_mtx_desc),
decltype(c_kxwn_thread_mtx_desc),
0,
in_chwn_block_desc.GetStride(I1),
out_khwn_thread_desc.GetStride(I1),
HoPerBlock,
GemmMPerThreadSubC,
GemmNPerThreadSubC,
GemmMLevel0Cluster,
GemmNLevel0Cluster,
GemmMLevel1Cluster,
GemmNLevel1Cluster,
GemmKPerThreadLoop,
HoPerThread,
GemmDataPerReadA,
GemmDataPerReadB>{};
// LDS: be careful of alignment
constexpr index_t in_block_space = in_chwn_block_desc.GetElementSpace(Number<max_align>{});
constexpr index_t wei_block_space =
wei_cyxk_block_desc.GetElementSpace(Number<max_align>{});
// LDS double buffer
__shared__ Float p_in_block_double[2 * in_block_space];
__shared__ Float p_wei_block_double[2 * wei_block_space];
const Float* p_in_global_block_offset =
p_in_global + in_chwn_global_desc.Get1dIndex(
0, hi_block_data_begin, wi_block_data_begin, n_block_data_begin);
const Float* p_wei_global_block_offset =
p_wei_global + wei_cyxk_global_desc.Get1dIndex(0, 0, 0, k_block_data_begin);
// preload data into LDS
{
Float p_in_register_clipboard[blockwise_in_copy.GetRegisterClipboardSize()];
Float p_wei_register_clipboard[blockwise_wei_copy.GetRegisterClipboardSize()];
blockwise_in_copy.RunLoadRegisterClipboard(p_in_global_block_offset,
p_in_register_clipboard);
blockwise_wei_copy.RunLoadRegisterClipboard(p_wei_global_block_offset,
p_wei_register_clipboard);
blockwise_in_copy.RunStoreRegisterClipboard(p_in_register_clipboard, p_in_block_double);
blockwise_wei_copy.RunStoreRegisterClipboard(p_wei_register_clipboard,
p_wei_block_double);
}
// register
Float p_out_thread[out_khwn_thread_desc.GetElementSpace()];
// set threadwise output tensor to 0
threadwise_4d_tensor_set_zero(out_khwn_thread_desc, p_out_thread);
for(index_t c_block_data_begin = 0; c_block_data_begin + 2 * CPerBlock < C;
c_block_data_begin += 2 * CPerBlock)
{
#pragma unroll
for(index_t iloop = 0; iloop < 2; ++iloop)
{
const bool even_loop = (iloop % 2 == 0);
Float* p_in_block_now =
even_loop ? p_in_block_double : p_in_block_double + in_block_space;
Float* p_wei_block_now =
even_loop ? p_wei_block_double : p_wei_block_double + wei_block_space;
Float* p_in_block_next =
even_loop ? p_in_block_double + in_block_space : p_in_block_double;
Float* p_wei_block_next =
even_loop ? p_wei_block_double + wei_block_space : p_wei_block_double;
// load next data
Float p_in_register_clipboard[blockwise_in_copy.GetRegisterClipboardSize()];
Float p_wei_register_clipboard[blockwise_wei_copy.GetRegisterClipboardSize()];
p_in_global_block_offset += CPerBlock * in_chwn_global_desc.GetStride(I0);
p_wei_global_block_offset += CPerBlock * wei_cyxk_global_desc.GetStride(I0);
__syncthreads();
blockwise_in_copy.RunLoadRegisterClipboard(p_in_global_block_offset,
p_in_register_clipboard);
blockwise_wei_copy.RunLoadRegisterClipboard(p_wei_global_block_offset,
p_wei_register_clipboard);
// a series of batched GEMM
for(index_t y = 0; y < Y; ++y)
{
for(index_t x = 0; x < X; ++x)
{
blockwise_batch_gemm.Run(
p_wei_block_now + wei_cyxk_block_desc.Get1dIndex(0, y, x, 0),
p_in_block_now + in_chwn_block_desc.Get1dIndex(0, y, x, 0),
p_out_thread);
}
}
blockwise_in_copy.RunStoreRegisterClipboard(p_in_register_clipboard,
p_in_block_next);
blockwise_wei_copy.RunStoreRegisterClipboard(p_wei_register_clipboard,
p_wei_block_next);
}
}
// tail
{
// even
p_in_global_block_offset += CPerBlock * in_chwn_global_desc.GetStride(I0);
p_wei_global_block_offset += CPerBlock * wei_cyxk_global_desc.GetStride(I0);
__syncthreads();
Float p_in_register_clipboard[blockwise_in_copy.GetRegisterClipboardSize()];
Float p_wei_register_clipboard[blockwise_wei_copy.GetRegisterClipboardSize()];
blockwise_in_copy.RunLoadRegisterClipboard(p_in_global_block_offset,
p_in_register_clipboard);
blockwise_wei_copy.RunLoadRegisterClipboard(p_wei_global_block_offset,
p_wei_register_clipboard);
for(index_t y = 0; y < Y; ++y)
{
for(index_t x = 0; x < X; ++x)
{
blockwise_batch_gemm.Run(
p_wei_block_double + wei_cyxk_block_desc.Get1dIndex(0, y, x, 0),
p_in_block_double + in_chwn_block_desc.Get1dIndex(0, y, x, 0),
p_out_thread);
}
}
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
__syncthreads();
for(index_t y = 0; y < Y; ++y)
{
for(index_t x = 0; x < X; ++x)
{
blockwise_batch_gemm.Run(p_wei_block_double + wei_block_space +
wei_cyxk_block_desc.Get1dIndex(0, y, x, 0),
p_in_block_double + in_block_space +
in_chwn_block_desc.Get1dIndex(0, y, x, 0),
p_out_thread);
}
}
}
// output: register to global mem,
#if 0
const auto c_thread_mtx_begin =
blockwise_batch_gemm.GetBeginOfThreadMatrixC(get_thread_local_1d_id());
for(index_t k = 0; k < out_khwn_thread_desc.GetLength(I0); ++k)
{
for(index_t ho = 0; ho < out_khwn_thread_desc.GetLength(I1); ++ho)
{
for(index_t wo = 0; wo < out_khwn_thread_desc.GetLength(I2); ++wo)
{
for(index_t n = 0; n < out_khwn_thread_desc.GetLength(I3); ++n)
{
const index_t b = out_khwn_thread_desc.Get1dIndex(0, 0, wo, n);
const auto c_thread_mtx_distance =
blockwise_batch_gemm.GetDistanceFromBeginOfThreadMatrixC(ho, k, b);
const index_t ho_thread =
c_thread_mtx_begin.batch + c_thread_mtx_distance.batch;
const index_t k_thread = c_thread_mtx_begin.row + c_thread_mtx_distance.row;
const index_t b_thread = c_thread_mtx_begin.col + c_thread_mtx_distance.col;
const index_t wo_thread = b_thread / NPerBlock;
const index_t n_thread = b_thread % NPerBlock;
p_out_global[out_khwn_global_desc.Get1dIndex(k_block_data_begin + k_thread,
ho_block_data_begin + ho_thread,
wo_block_data_begin + wo_thread,
n_block_data_begin + n_thread)] =
p_out_thread[out_khwn_thread_desc.Get1dIndex(k, ho, wo, n)];
}
}
}
}
#elif 1
const auto c_thread_mtx_begin =
blockwise_batch_gemm.GetBeginOfThreadMatrixC(get_thread_local_1d_id());
const index_t k_thread_data_begin = c_thread_mtx_begin.row;
const index_t ho_thread_data_begin = c_thread_mtx_begin.batch;
const index_t wo_thread_data_begin = c_thread_mtx_begin.col / NPerBlock;
const index_t n_thread_data_begin =
c_thread_mtx_begin.col - NPerBlock * wo_thread_data_begin;
// output is a 10d tensor
constexpr index_t N2 = GemmNPerThreadSubC;
constexpr index_t N1 = NPerBlock / N2;
constexpr index_t W2 =
(GemmNLevel0Cluster * GemmNLevel1Cluster) / (NPerBlock / GemmNPerThreadSubC);
constexpr index_t W1 = WoPerBlock / W2;
constexpr index_t K2 = GemmMPerThreadSubC;
constexpr index_t K1 = KPerBlock / KPerThread;
constexpr auto out_10d_global_desc = make_ConstantTensorDescriptor(
Sequence<K / (K1 * K2), K1, K2, Ho, Wo / (W1 * W2), W1, W2, N / (N1 * N2), N1, N2>{});
constexpr auto out_10d_thread_desc = make_ConstantTensorDescriptor(
Sequence<KPerThread / K2, 1, K2, HoPerThread, 1, W1, 1, 1, 1, N2>{});
#if 0
if(get_thread_local_1d_id() == 0 && get_block_1d_id() == 0)
{
print_ConstantTensorDescriptor(out_khwn_thread_desc, "out_khwn_thread_desc");
print_ConstantTensorDescriptor(out_10d_thread_desc, "out_10d_thread_desc");
print_ConstantTensorDescriptor(out_khwn_global_desc, "out_khwn_global_desc");
print_ConstantTensorDescriptor(out_10d_global_desc, "out_10d_global_desc");
}
#endif
threadwise_10d_tensor_copy(out_10d_thread_desc,
p_out_thread,
out_10d_global_desc,
p_out_global + out_khwn_global_desc.Get1dIndex(
k_block_data_begin + k_thread_data_begin,
ho_block_data_begin + ho_thread_data_begin,
wo_block_data_begin + wo_thread_data_begin,
n_block_data_begin + n_thread_data_begin),
out_10d_thread_desc.GetLengths(),
Number<OutThreadCopyDataPerWrite>{});
#endif
}
};
src/include/gridwise_convolution_implicit_gemm_v1r2_chwn_cyxk_khwn.hip.hpp
View file @ 569ad66e
......@@ -33,10 +33,10 @@ template <index_t GridSize,
index_t GemmKPerThreadLoop,
index_t GemmDataPerReadA,
index_t GemmDataPerReadB,
class InBlockCopyThreadPerDims,
index_t InBlockCopyDataPerRead,
index_t WeiBlockCopyDataPerRead,
index_t OutThreadCopyDataPerWrite>
class InBlockCopyClusterLengths_CHWN,
index_t InBlockCopyDataPerRead_N,
index_t WeiBlockCopyDataPerRead_K,
index_t OutThreadCopyDataPerWrite_N>
struct GridwiseConvolutionImplicitGemm_v1r2_chwn_cyxk_khwn
{
__device__ void Run(const Float* const __restrict__ p_in_global,
......@@ -44,9 +44,11 @@ struct GridwiseConvolutionImplicitGemm_v1r2_chwn_cyxk_khwn
Float* const __restrict__ p_out_global) const
{
// be careful of this assertion
static_assert(
NPerThread <= NPerBlock && NPerBlock % NPerThread == 0,
"wrong! should satisfy: NPerThread <= NPerBlock && NPerBlock % NPerThread == 0");
static_assert(NPerBlock % NPerThread == 0 && (GemmNPerThreadSubC <= NPerBlock &&
NPerBlock % GemmNPerThreadSubC == 0) ||
(GemmNPerThreadSubC >= NPerBlock && NPerThread == NPerBlock &&
GemmNPerThreadSubC % NPerThread == 0),
"wrong!");
constexpr auto I0 = Number<0>{};
constexpr auto I1 = Number<1>{};
......@@ -101,14 +103,23 @@ struct GridwiseConvolutionImplicitGemm_v1r2_chwn_cyxk_khwn
// LDS tensor view
// be careful of alignment
constexpr index_t max_align = mod_conv::max(
InBlockCopyDataPerRead, WeiBlockCopyDataPerRead, GemmDataPerReadA, GemmDataPerReadB);
constexpr index_t max_align = mod_conv::max(InBlockCopyDataPerRead_N,
WeiBlockCopyDataPerRead_K,
GemmDataPerReadA,
GemmDataPerReadB);
constexpr auto in_c_h_w_n_block_desc = make_ConstantTensorDescriptor_aligned(
Sequence<CPerBlock, HoPerBlock, WiPerBlock, NPerBlock>{}, Number<max_align>{});
Sequence<CPerBlock, HoPerBlock, WiPerBlock, NPerBlock>{},
Number<InBlockCopyDataPerRead_N>{});
// this check is ad-hoc
// TODO: need to properly implement tensor descriptor with alignment
static_assert(in_c_h_w_n_block_desc.GetStride(I1) % GemmDataPerReadB == 0,
"GemmDataPerReadB alignment requirement is not meet");
constexpr auto wei_c_x_k_block_desc = make_ConstantTensorDescriptor_aligned(
Sequence<CPerBlock, X, KPerBlock>{}, Number<max_align>{});
Sequence<CPerBlock, X, KPerBlock>{},
Number<mod_conv::max(WeiBlockCopyDataPerRead_K, GemmDataPerReadA)>{});
// tensor view of threadwise output in register
constexpr auto out_k_h_w_n_thread_desc = make_ConstantTensorDescriptor(
......@@ -116,14 +127,14 @@ struct GridwiseConvolutionImplicitGemm_v1r2_chwn_cyxk_khwn
// blockwise copy
// input: format is [C, Hi, Wi, N]
#if 0
#if 1
const auto blockwise_in_copy =
Blockwise4dTensorCopy1<BlockSize,
Float,
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()),
InBlockCopyDataPerRead>{};
InBlockCopyDataPerRead_N>{};
#else
const auto blockwise_in_copy =
Blockwise4dTensorCopy3<BlockSize,
......@@ -131,8 +142,8 @@ struct GridwiseConvolutionImplicitGemm_v1r2_chwn_cyxk_khwn
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()),
InBlockCopyThreadPerDims,
InBlockCopyDataPerRead>{};
InBlockCopyClusterLengths_CHWN,
InBlockCopyDataPerRead_N>{};
#endif
// blockwise wei copy
......@@ -143,7 +154,7 @@ struct GridwiseConvolutionImplicitGemm_v1r2_chwn_cyxk_khwn
decltype(wei_c_x_k_global_desc),
decltype(wei_c_x_k_block_desc),
decltype(wei_c_x_k_block_desc.GetLengths()),
WeiBlockCopyDataPerRead>{};
WeiBlockCopyDataPerRead_K>{};
// a series of blockwise batched GEMM
// C_matrix += transpose(A_matrix) * B_matrix
......@@ -195,7 +206,9 @@ struct GridwiseConvolutionImplicitGemm_v1r2_chwn_cyxk_khwn
__shared__ Float p_wei_block[wei_block_space];
// register
Float p_out_thread[out_k_h_w_n_thread_desc.GetElementSpace()];
// C++ lambda doesn't capture array, use pointer instead
Float p_out_thread_data[out_k_h_w_n_thread_desc.GetElementSpace()];
Float* const p_out_thread = p_out_thread_data;
#if 0
if(get_thread_local_1d_id() == 0 && get_block_1d_id() == 0)
......@@ -293,22 +306,38 @@ struct GridwiseConvolutionImplicitGemm_v1r2_chwn_cyxk_khwn
const index_t k_thread_data_begin = c_thread_mtx_begin.row;
const index_t ho_thread_data_begin = c_thread_mtx_begin.batch;
const index_t wo_thread_data_begin = c_thread_mtx_begin.col / NPerBlock;
const index_t n_thread_data_begin =
c_thread_mtx_begin.col - NPerBlock * wo_thread_data_begin;
const index_t n_thread_data_begin = c_thread_mtx_begin.col % NPerBlock;
static_if<GemmNPerThreadSubC <= NPerBlock>{}(
[&](auto f_dummy) { // f_dummy do nothing but perfect forwarding. Using this trick to
// make this lambda a generic lambda, so it won't be compiled until
// instantiated
static_assert((f_dummy(GemmNPerThreadSubC) <= NPerBlock &&
NPerBlock % GemmNPerThreadSubC == 0),
"wrong!");
// output is a 10d tensor
constexpr index_t N2 = GemmNPerThreadSubC;
constexpr index_t N1 = NPerBlock / N2;
constexpr index_t W2 =
(GemmNLevel0Cluster * GemmNLevel1Cluster) / (NPerBlock / GemmNPerThreadSubC);
constexpr index_t W2 = (GemmNLevel0Cluster * GemmNLevel1Cluster) /
f_dummy(NPerBlock / GemmNPerThreadSubC);
constexpr index_t W1 = WoPerBlock / W2;
constexpr index_t K2 = GemmMPerThreadSubC;
constexpr index_t K1 = KPerBlock / KPerThread;
constexpr auto out_10d_global_desc = make_ConstantTensorDescriptor(
Sequence<K / (K1 * K2), K1, K2, Ho, Wo / (W1 * W2), W1, W2, N / (N1 * N2), N1, N2>{});
constexpr auto out_10d_global_desc =
make_ConstantTensorDescriptor(Sequence<K / (K1 * K2),
K1,
K2,
Ho,
Wo / (W1 * W2),
W1,
W2,
N / f_dummy(N1 * N2),
N1,
N2>{});
constexpr auto out_10d_thread_desc = make_ConstantTensorDescriptor(
Sequence<KPerThread / K2, 1, K2, HoPerThread, 1, W1, 1, 1, 1, N2>{});
......@@ -316,23 +345,87 @@ struct GridwiseConvolutionImplicitGemm_v1r2_chwn_cyxk_khwn
#if 0
if(get_thread_local_1d_id() == 0 && get_block_1d_id() == 0)
{
print_ConstantTensorDescriptor(out_khwn_thread_desc, "out_khwn_thread_desc");
print_ConstantTensorDescriptor(out_k_h_w_n_thread_desc,
"out_k_h_w_n_thread_desc");
print_ConstantTensorDescriptor(out_10d_thread_desc, "out_10d_thread_desc");
print_ConstantTensorDescriptor(out_k_h_w_n_global_desc,
"out_k_h_w_n_global_desc");
print_ConstantTensorDescriptor(out_10d_global_desc, "out_10d_global_desc");
}
#endif
threadwise_nd_tensor_copy(out_10d_thread_desc,
p_out_thread,
out_10d_global_desc,
p_out_global +
out_k_h_w_n_global_desc.Get1dIndex(
k_block_data_begin + k_thread_data_begin,
ho_block_data_begin + ho_thread_data_begin,
wo_block_data_begin + wo_thread_data_begin,
n_block_data_begin + n_thread_data_begin),
out_10d_thread_desc.GetLengths(),
Number<OutThreadCopyDataPerWrite_N>{});
})
.else_([&](auto f_dummy) {
static_assert(f_dummy(GemmNPerThreadSubC) >= NPerBlock && NPerThread == NPerBlock &&
GemmNPerThreadSubC % NPerThread == 0,
"wrong!");
// output is a 10d tensor
constexpr index_t N1 = NPerBlock;
constexpr index_t W3 = GemmNPerThreadSubC / NPerBlock;
constexpr index_t W2 = GemmNLevel0Cluster * GemmNLevel1Cluster;
constexpr index_t W1 = WoPerBlock / f_dummy(W2 * W3);
constexpr index_t K2 = GemmMPerThreadSubC;
constexpr index_t K1 = KPerBlock / KPerThread;
constexpr auto out_10d_global_desc =
make_ConstantTensorDescriptor(Sequence<K / (K1 * K2),
K1,
K2,
Ho,
Wo / (W1 * W2 * W3),
W1,
W2,
W3,
N / N1,
N1>{});
constexpr auto out_10d_thread_desc = make_ConstantTensorDescriptor(
Sequence<KPerThread / K2, 1, K2, HoPerThread, 1, W1, 1, W3, 1, N1>{});
#if 0
if(get_thread_local_1d_id() == 0 && get_block_1d_id() == 0)
{
print_ConstantTensorDescriptor(out_k_h_w_n_thread_desc,
"out_k_h_w_n_thread_desc");
print_ConstantTensorDescriptor(out_10d_thread_desc, "out_10d_thread_desc");
print_ConstantTensorDescriptor(out_khwn_global_desc, "out_khwn_global_desc");
print_ConstantTensorDescriptor(out_k_h_w_n_global_desc,
"out_k_h_w_n_global_desc");
print_ConstantTensorDescriptor(out_10d_global_desc, "out_10d_global_desc");
for(index_t i = 0; i < 64; ++i)
{
printf("out %f, ", p_out_thread[i]);
}
}
#endif
threadwise_10d_tensor_copy(out_10d_thread_desc,
threadwise_nd_tensor_copy(out_10d_thread_desc,
p_out_thread,
out_10d_global_desc,
p_out_global + out_k_h_w_n_global_desc.Get1dIndex(
p_out_global +
out_k_h_w_n_global_desc.Get1dIndex(
k_block_data_begin + k_thread_data_begin,
ho_block_data_begin + ho_thread_data_begin,
wo_block_data_begin + wo_thread_data_begin,
n_block_data_begin + n_thread_data_begin),
out_10d_thread_desc.GetLengths(),
Number<OutThreadCopyDataPerWrite>{});
Number<OutThreadCopyDataPerWrite_N>{});
});
}
};
src/include/gridwise_convolution_implicit_gemm_v1r2_nchw_cyxk_khwn.hip.hpp
View file @ 569ad66e
......@@ -39,7 +39,7 @@ template <index_t GridSize,
index_t InBlockReorderDataPerRead_W,
index_t InBlockReorderDataPerWrite_N,
class WeiBlockCopyClusterLengths_CXK,
index_t WeiBlockCopyDataPerRead_C,
index_t WeiBlockCopyDataPerRead_K,
index_t OutThreadCopyDataPerWrite_N>
struct GridwiseConvolutionImplicitGemm_v1r2_nchw_cyxk_khwn
{
......@@ -106,7 +106,7 @@ struct GridwiseConvolutionImplicitGemm_v1r2_nchw_cyxk_khwn
// LDS tensor view
// be careful of alignment
constexpr index_t max_align = mod_conv::max(InBlockReorderDataPerWrite_N,
WeiBlockCopyDataPerRead_C,
WeiBlockCopyDataPerRead_K,
GemmDataPerReadA,
GemmDataPerReadB);
......@@ -146,7 +146,7 @@ struct GridwiseConvolutionImplicitGemm_v1r2_nchw_cyxk_khwn
decltype(wei_c_x_k_block_desc),
decltype(wei_c_x_k_block_desc.GetLengths()),
WeiBlockCopyClusterLengths_CXK,
WeiBlockCopyDataPerRead_C>{};
WeiBlockCopyDataPerRead_K>{};
// a series of blockwise batched GEMM
// C_matrix += transpose(A_matrix) * B_matrix
......@@ -216,6 +216,7 @@ struct GridwiseConvolutionImplicitGemm_v1r2_nchw_cyxk_khwn
// set threadwise output tensor to 0
threadwise_4d_tensor_set_zero(out_k_h_w_n_thread_desc, p_out_thread);
#if 0
const Float* p_in_global_block_offset =
p_in_global + in_n_c_h_w_global_desc.Get1dIndex(
n_block_data_begin, 0, hi_block_data_begin, wi_block_data_begin);
......@@ -229,7 +230,6 @@ struct GridwiseConvolutionImplicitGemm_v1r2_nchw_cyxk_khwn
{
for(index_t y = 0; y < Y; ++y)
{
#if 1
blockwise_in_copy_reorder.Run(p_in_global_block_offset +
in_n_c_h_w_global_desc.Get1dIndex(0, 0, y, 0),
p_in_block);
......@@ -237,24 +237,49 @@ struct GridwiseConvolutionImplicitGemm_v1r2_nchw_cyxk_khwn
blockwise_wei_copy.Run(p_wei_global_block_offset +
wei_c_y_x_k_global_desc.Get1dIndex(0, y, 0, 0),
p_wei_block);
__syncthreads();
for(index_t x = 0; x < X; ++x)
{
blockwise_batch_gemm.Run(p_wei_block + wei_c_x_k_block_desc.Get1dIndex(0, x, 0),
p_in_block +
in_c_h_w_n_block_desc.Get1dIndex(0, 0, x, 0),
p_out_thread);
}
__syncthreads();
}
}
#else
for(index_t y = 0; y < Y; ++y)
{
const Float* p_in_global_block_offset =
p_in_global +
in_n_c_h_w_global_desc.Get1dIndex(
n_block_data_begin, 0, hi_block_data_begin + y, wi_block_data_begin);
const Float* p_wei_global_block_offset =
p_wei_global + wei_c_y_x_k_global_desc.Get1dIndex(0, y, 0, k_block_data_begin);
for(index_t c_block_data_begin = 0; c_block_data_begin < C;
c_block_data_begin += CPerBlock,
p_in_global_block_offset +=
CPerBlock * in_n_c_h_w_global_desc.GetStride(I1),
p_wei_global_block_offset +=
CPerBlock * wei_c_y_x_k_global_desc.GetStride(I0))
{
Float p_in_clipboard[blockwise_in_copy_reorder.GetRegisterClipboardSize()];
Float p_wei_clipboard[blockwise_wei_copy.GetRegisterClipboardSize()];
blockwise_in_copy_reorder.RunLoadRegisterClipboard(
p_in_global_block_offset + in_n_c_h_w_global_desc.Get1dIndex(0, 0, y, 0),
blockwise_in_copy_reorder.RunLoadRegisterClipboard(p_in_global_block_offset,
p_in_clipboard);
blockwise_wei_copy.RunLoadRegisterClipboard(
p_wei_global_block_offset + wei_c_y_x_k_global_desc.Get1dIndex(0, y, 0, 0),
blockwise_wei_copy.RunLoadRegisterClipboard(p_wei_global_block_offset,
p_wei_clipboard);
blockwise_wei_copy.RunStoreRegisterClipboard(p_wei_clipboard, p_wei_block);
blockwise_in_copy_reorder.RunStoreRegisterClipboard(p_in_clipboard, p_in_block);
#endif
__syncthreads();
for(index_t x = 0; x < X; ++x)
......@@ -268,6 +293,7 @@ struct GridwiseConvolutionImplicitGemm_v1r2_nchw_cyxk_khwn
__syncthreads();
}
}
#endif
// output: register to global mem,
const auto c_thread_mtx_begin =
......
src/include/gridwise_convolution_implicit_gemm_v1r3_chwn_cyxk_khwn.hip.hpp
View file @ 569ad66e
......@@ -43,9 +43,11 @@ struct GridwiseConvolutionImplicitGemm_v1r3_chwn_cyxk_khwn
Float* const __restrict__ p_out_global) const
{
// be careful of this assertion
static_assert(
NPerThread <= NPerBlock && NPerBlock % NPerThread == 0,
"wrong! should satisfy: NPerThread <= NPerBlock && NPerBlock % NPerThread == 0");
static_assert(NPerBlock % NPerThread == 0 && (GemmNPerThreadSubC <= NPerBlock &&
NPerBlock % GemmNPerThreadSubC == 0) ||
(GemmNPerThreadSubC >= NPerBlock && NPerThread == NPerBlock &&
GemmNPerThreadSubC % NPerThread == 0),
"wrong!");
constexpr auto I0 = Number<0>{};
constexpr auto I1 = Number<1>{};
......@@ -66,9 +68,6 @@ struct GridwiseConvolutionImplicitGemm_v1r3_chwn_cyxk_khwn
constexpr index_t Y = wei_c_y_x_k_global_desc.GetLength(I1);
constexpr index_t X = wei_c_y_x_k_global_desc.GetLength(I2);
constexpr index_t HiPerBlock = HoPerBlock + Y - 1;
constexpr index_t WiPerBlock = WoPerBlock + X - 1;
// divide block work: [K, Ho, Wo, N]
static_assert(N % NPerBlock == 0 && K % KPerBlock == 0 && C % CPerBlock == 0 &&
Ho % HoPerBlock == 0 && Wo % WoPerBlock == 0,
......@@ -106,10 +105,17 @@ struct GridwiseConvolutionImplicitGemm_v1r3_chwn_cyxk_khwn
GemmDataPerReadB);
constexpr auto in_c_h_w_n_block_desc = make_ConstantTensorDescriptor_aligned(
Sequence<CPerBlock, HoPerBlock, WoPerBlock, NPerBlock>{}, Number<max_align>{});
Sequence<CPerBlock, HoPerBlock, WoPerBlock, NPerBlock>{},
Number<InBlockCopyDataPerRead_N>{});
// this check is ad-hoc
// TODO: need to properly implement tensor descriptor with alignment
static_assert(in_c_h_w_n_block_desc.GetStride(I1) % GemmDataPerReadB == 0,
"GemmDataPerReadB alignment requirement is not meet");
constexpr auto wei_c_k_block_desc = make_ConstantTensorDescriptor_aligned(
Sequence<CPerBlock, KPerBlock>{}, Number<max_align>{});
Sequence<CPerBlock, KPerBlock>{},
Number<mod_conv::max(WeiBlockCopyDataPerRead_K, GemmDataPerReadA)>{});
// tensor view of threadwise output in register
constexpr auto out_k_h_w_n_thread_desc = make_ConstantTensorDescriptor(
......@@ -177,6 +183,7 @@ struct GridwiseConvolutionImplicitGemm_v1r3_chwn_cyxk_khwn
GemmDataPerReadB>{};
// LDS: be careful of alignment
// TODO:: need to properly implement tensor descriptor with alignment
constexpr index_t in_block_space =
in_c_h_w_n_block_desc.GetElementSpace(Number<max_align>{});
constexpr index_t wei_block_space = wei_c_k_block_desc.GetElementSpace(Number<max_align>{});
......@@ -185,7 +192,9 @@ struct GridwiseConvolutionImplicitGemm_v1r3_chwn_cyxk_khwn
__shared__ Float p_wei_block[wei_block_space];
// register
Float p_out_thread[out_k_h_w_n_thread_desc.GetElementSpace()];
// C++ lambda doesn't capture array, use pointer instead
Float p_out_thread_data[out_k_h_w_n_thread_desc.GetElementSpace()];
Float* const p_out_thread = p_out_thread_data;
#if 0
if(get_thread_local_1d_id() == 0 && get_block_1d_id() == 0)
......@@ -276,22 +285,38 @@ struct GridwiseConvolutionImplicitGemm_v1r3_chwn_cyxk_khwn
const index_t k_thread_data_begin = c_thread_mtx_begin.row;
const index_t ho_thread_data_begin = c_thread_mtx_begin.batch;
const index_t wo_thread_data_begin = c_thread_mtx_begin.col / NPerBlock;
const index_t n_thread_data_begin =
c_thread_mtx_begin.col - NPerBlock * wo_thread_data_begin;
const index_t n_thread_data_begin = c_thread_mtx_begin.col % NPerBlock;
static_if<GemmNPerThreadSubC <= NPerBlock>{}(
[&](auto f_dummy) { // f_dummy do nothing but perfect forwarding. Using this trick to
// make this lambda a generic lambda, so it won't be compiled until
// instantiated
static_assert((f_dummy(GemmNPerThreadSubC) <= NPerBlock &&
NPerBlock % GemmNPerThreadSubC == 0),
"wrong!");
// output is a 10d tensor
constexpr index_t N2 = GemmNPerThreadSubC;
constexpr index_t N1 = NPerBlock / N2;
constexpr index_t W2 =
(GemmNLevel0Cluster * GemmNLevel1Cluster) / (NPerBlock / GemmNPerThreadSubC);
constexpr index_t W2 = (GemmNLevel0Cluster * GemmNLevel1Cluster) /
f_dummy(NPerBlock / GemmNPerThreadSubC);
constexpr index_t W1 = WoPerBlock / W2;
constexpr index_t K2 = GemmMPerThreadSubC;
constexpr index_t K1 = KPerBlock / KPerThread;
constexpr auto out_10d_global_desc = make_ConstantTensorDescriptor(
Sequence<K / (K1 * K2), K1, K2, Ho, Wo / (W1 * W2), W1, W2, N / (N1 * N2), N1, N2>{});
constexpr auto out_10d_global_desc =
make_ConstantTensorDescriptor(Sequence<K / (K1 * K2),
K1,
K2,
Ho,
Wo / (W1 * W2),
W1,
W2,
N / f_dummy(N1 * N2),
N1,
N2>{});
constexpr auto out_10d_thread_desc = make_ConstantTensorDescriptor(
Sequence<KPerThread / K2, 1, K2, HoPerThread, 1, W1, 1, 1, 1, N2>{});
......@@ -299,23 +324,87 @@ struct GridwiseConvolutionImplicitGemm_v1r3_chwn_cyxk_khwn
#if 0
if(get_thread_local_1d_id() == 0 && get_block_1d_id() == 0)
{
print_ConstantTensorDescriptor(out_khwn_thread_desc, "out_khwn_thread_desc");
print_ConstantTensorDescriptor(out_k_h_w_n_thread_desc,
"out_k_h_w_n_thread_desc");
print_ConstantTensorDescriptor(out_10d_thread_desc, "out_10d_thread_desc");
print_ConstantTensorDescriptor(out_khwn_global_desc, "out_khwn_global_desc");
print_ConstantTensorDescriptor(out_k_h_w_n_global_desc,
"out_k_h_w_n_global_desc");
print_ConstantTensorDescriptor(out_10d_global_desc, "out_10d_global_desc");
}
#endif
threadwise_10d_tensor_copy(out_10d_thread_desc,
threadwise_nd_tensor_copy(out_10d_thread_desc,
p_out_thread,
out_10d_global_desc,
p_out_global +
out_k_h_w_n_global_desc.Get1dIndex(
k_block_data_begin + k_thread_data_begin,
ho_block_data_begin + ho_thread_data_begin,
wo_block_data_begin + wo_thread_data_begin,
n_block_data_begin + n_thread_data_begin),
out_10d_thread_desc.GetLengths(),
Number<OutThreadCopyDataPerWrite_N>{});
})
.else_([&](auto f_dummy) {
static_assert(f_dummy(GemmNPerThreadSubC) >= NPerBlock && NPerThread == NPerBlock &&
GemmNPerThreadSubC % NPerThread == 0,
"wrong!");
// output is a 10d tensor
constexpr index_t N1 = NPerBlock;
constexpr index_t W3 = GemmNPerThreadSubC / NPerBlock;
constexpr index_t W2 = GemmNLevel0Cluster * GemmNLevel1Cluster;
constexpr index_t W1 = WoPerBlock / f_dummy(W2 * W3);
constexpr index_t K2 = GemmMPerThreadSubC;
constexpr index_t K1 = KPerBlock / KPerThread;
constexpr auto out_10d_global_desc =
make_ConstantTensorDescriptor(Sequence<K / (K1 * K2),
K1,
K2,
Ho,
Wo / (W1 * W2 * W3),
W1,
W2,
W3,
N / N1,
N1>{});
constexpr auto out_10d_thread_desc = make_ConstantTensorDescriptor(
Sequence<KPerThread / K2, 1, K2, HoPerThread, 1, W1, 1, W3, 1, N1>{});
#if 0
if(get_thread_local_1d_id() == 0 && get_block_1d_id() == 0)
{
print_ConstantTensorDescriptor(out_k_h_w_n_thread_desc,
"out_k_h_w_n_thread_desc");
print_ConstantTensorDescriptor(out_10d_thread_desc, "out_10d_thread_desc");
print_ConstantTensorDescriptor(out_k_h_w_n_global_desc,
"out_k_h_w_n_global_desc");
print_ConstantTensorDescriptor(out_10d_global_desc, "out_10d_global_desc");
for(index_t i = 0; i < 64; ++i)
{
printf("out %f, ", p_out_thread[i]);
}
}
#endif
threadwise_nd_tensor_copy(out_10d_thread_desc,
p_out_thread,
out_10d_global_desc,
p_out_global + out_k_h_w_n_global_desc.Get1dIndex(
p_out_global +
out_k_h_w_n_global_desc.Get1dIndex(
k_block_data_begin + k_thread_data_begin,
ho_block_data_begin + ho_thread_data_begin,
wo_block_data_begin + wo_thread_data_begin,
n_block_data_begin + n_thread_data_begin),
out_10d_thread_desc.GetLengths(),
Number<OutThreadCopyDataPerWrite_N>{});
});
}
};
src/include/gridwise_convolution_implicit_gemm_v1r3_lds_double_buffer_chwn_cyxk_khwn.hip.hpp
View file @ 569ad66e
......@@ -43,9 +43,11 @@ struct GridwiseConvolutionImplicitGemm_v1r3_lds_double_buffer_chwn_cyxk_khwn
Float* const __restrict__ p_out_global) const
{
// be careful of this assertion
static_assert(
NPerThread <= NPerBlock && NPerBlock % NPerThread == 0,
"wrong! should satisfy: NPerThread <= NPerBlock && NPerBlock % NPerThread == 0");
static_assert(NPerBlock % NPerThread == 0 && (GemmNPerThreadSubC <= NPerBlock &&
NPerBlock % GemmNPerThreadSubC == 0) ||
(GemmNPerThreadSubC >= NPerBlock && NPerThread == NPerBlock &&
GemmNPerThreadSubC % NPerThread == 0),
"wrong!");
constexpr auto I0 = Number<0>{};
constexpr auto I1 = Number<1>{};
......@@ -109,10 +111,17 @@ struct GridwiseConvolutionImplicitGemm_v1r3_lds_double_buffer_chwn_cyxk_khwn
GemmDataPerReadB);
constexpr auto in_c_h_w_n_block_desc = make_ConstantTensorDescriptor_aligned(
Sequence<CPerBlock, HoPerBlock, WoPerBlock, NPerBlock>{}, Number<max_align>{});
Sequence<CPerBlock, HoPerBlock, WoPerBlock, NPerBlock>{},
Number<InBlockCopyDataPerRead_N>{});
// this check is ad-hoc
// TODO: need to properly implement tensor descriptor with alignment
static_assert(in_c_h_w_n_block_desc.GetStride(I1) % GemmDataPerReadB == 0,
"GemmDataPerReadB alignment requirement is not meet");
constexpr auto wei_c_k_block_desc = make_ConstantTensorDescriptor_aligned(
Sequence<CPerBlock, KPerBlock>{}, Number<max_align>{});
Sequence<CPerBlock, KPerBlock>{},
Number<mod_conv::max(WeiBlockCopyDataPerRead_K, GemmDataPerReadA)>{});
// tensor view of threadwise output in register
constexpr auto out_k_h_w_n_thread_desc = make_ConstantTensorDescriptor(
......@@ -199,7 +208,9 @@ struct GridwiseConvolutionImplicitGemm_v1r3_lds_double_buffer_chwn_cyxk_khwn
__shared__ Float p_wei_block_double[2 * wei_block_space];
// register
Float p_out_thread[out_k_h_w_n_thread_desc.GetElementSpace()];
// C++ lambda doesn't capture array, use pointer instead
Float p_out_thread_data[out_k_h_w_n_thread_desc.GetElementSpace()];
Float* const p_out_thread = p_out_thread_data;
#if 0
if(get_thread_local_1d_id() == 0 && get_block_1d_id() == 0)
......@@ -336,22 +347,38 @@ struct GridwiseConvolutionImplicitGemm_v1r3_lds_double_buffer_chwn_cyxk_khwn
const index_t k_thread_data_begin = c_thread_mtx_begin.row;
const index_t ho_thread_data_begin = c_thread_mtx_begin.batch;
const index_t wo_thread_data_begin = c_thread_mtx_begin.col / NPerBlock;
const index_t n_thread_data_begin =
c_thread_mtx_begin.col - NPerBlock * wo_thread_data_begin;
const index_t n_thread_data_begin = c_thread_mtx_begin.col % NPerBlock;
static_if<GemmNPerThreadSubC <= NPerBlock>{}(
[&](auto f_dummy) { // f_dummy do nothing but perfect forwarding. Using this trick to
// make this lambda a generic lambda, so it won't be compiled until
// instantiated
static_assert((f_dummy(GemmNPerThreadSubC) <= NPerBlock &&
NPerBlock % GemmNPerThreadSubC == 0),
"wrong!");
// output is a 10d tensor
constexpr index_t N2 = GemmNPerThreadSubC;
constexpr index_t N1 = NPerBlock / N2;
constexpr index_t W2 =
(GemmNLevel0Cluster * GemmNLevel1Cluster) / (NPerBlock / GemmNPerThreadSubC);
constexpr index_t W2 = (GemmNLevel0Cluster * GemmNLevel1Cluster) /
f_dummy(NPerBlock / GemmNPerThreadSubC);
constexpr index_t W1 = WoPerBlock / W2;
constexpr index_t K2 = GemmMPerThreadSubC;
constexpr index_t K1 = KPerBlock / KPerThread;
constexpr auto out_10d_global_desc = make_ConstantTensorDescriptor(
Sequence<K / (K1 * K2), K1, K2, Ho, Wo / (W1 * W2), W1, W2, N / (N1 * N2), N1, N2>{});
constexpr auto out_10d_global_desc =
make_ConstantTensorDescriptor(Sequence<K / (K1 * K2),
K1,
K2,
Ho,
Wo / (W1 * W2),
W1,
W2,
N / f_dummy(N1 * N2),
N1,
N2>{});
constexpr auto out_10d_thread_desc = make_ConstantTensorDescriptor(
Sequence<KPerThread / K2, 1, K2, HoPerThread, 1, W1, 1, 1, 1, N2>{});
......@@ -359,23 +386,87 @@ struct GridwiseConvolutionImplicitGemm_v1r3_lds_double_buffer_chwn_cyxk_khwn
#if 0
if(get_thread_local_1d_id() == 0 && get_block_1d_id() == 0)
{
print_ConstantTensorDescriptor(out_khwn_thread_desc, "out_khwn_thread_desc");
print_ConstantTensorDescriptor(out_k_h_w_n_thread_desc,
"out_k_h_w_n_thread_desc");
print_ConstantTensorDescriptor(out_10d_thread_desc, "out_10d_thread_desc");
print_ConstantTensorDescriptor(out_k_h_w_n_global_desc,
"out_k_h_w_n_global_desc");
print_ConstantTensorDescriptor(out_10d_global_desc, "out_10d_global_desc");
}
#endif
threadwise_nd_tensor_copy(out_10d_thread_desc,
p_out_thread,
out_10d_global_desc,
p_out_global +
out_k_h_w_n_global_desc.Get1dIndex(
k_block_data_begin + k_thread_data_begin,
ho_block_data_begin + ho_thread_data_begin,
wo_block_data_begin + wo_thread_data_begin,
n_block_data_begin + n_thread_data_begin),
out_10d_thread_desc.GetLengths(),
Number<OutThreadCopyDataPerWrite_N>{});
})
.else_([&](auto f_dummy) {
static_assert(f_dummy(GemmNPerThreadSubC) >= NPerBlock && NPerThread == NPerBlock &&
GemmNPerThreadSubC % NPerThread == 0,
"wrong!");
// output is a 10d tensor
constexpr index_t N1 = NPerBlock;
constexpr index_t W3 = GemmNPerThreadSubC / NPerBlock;
constexpr index_t W2 = GemmNLevel0Cluster * GemmNLevel1Cluster;
constexpr index_t W1 = WoPerBlock / f_dummy(W2 * W3);
constexpr index_t K2 = GemmMPerThreadSubC;
constexpr index_t K1 = KPerBlock / KPerThread;
constexpr auto out_10d_global_desc =
make_ConstantTensorDescriptor(Sequence<K / (K1 * K2),
K1,
K2,
Ho,
Wo / (W1 * W2 * W3),
W1,
W2,
W3,
N / N1,
N1>{});
constexpr auto out_10d_thread_desc = make_ConstantTensorDescriptor(
Sequence<KPerThread / K2, 1, K2, HoPerThread, 1, W1, 1, W3, 1, N1>{});
#if 0
if(get_thread_local_1d_id() == 0 && get_block_1d_id() == 0)
{
print_ConstantTensorDescriptor(out_k_h_w_n_thread_desc,
"out_k_h_w_n_thread_desc");
print_ConstantTensorDescriptor(out_10d_thread_desc, "out_10d_thread_desc");
print_ConstantTensorDescriptor(out_khwn_global_desc, "out_khwn_global_desc");
print_ConstantTensorDescriptor(out_k_h_w_n_global_desc,
"out_k_h_w_n_global_desc");
print_ConstantTensorDescriptor(out_10d_global_desc, "out_10d_global_desc");
for(index_t i = 0; i < 64; ++i)
{
printf("out %f, ", p_out_thread[i]);
}
}
#endif
threadwise_10d_tensor_copy(out_10d_thread_desc,
threadwise_nd_tensor_copy(out_10d_thread_desc,
p_out_thread,
out_10d_global_desc,
p_out_global + out_k_h_w_n_global_desc.Get1dIndex(
p_out_global +
out_k_h_w_n_global_desc.Get1dIndex(
k_block_data_begin + k_thread_data_begin,
ho_block_data_begin + ho_thread_data_begin,
wo_block_data_begin + wo_thread_data_begin,
n_block_data_begin + n_thread_data_begin),
out_10d_thread_desc.GetLengths(),
Number<OutThreadCopyDataPerWrite_N>{});
});
}
};
src/include/gridwise_convolution_implicit_gemm_v1r3_lds_double_buffer_nchw_cyxk_khwn.hip.hpp 0 → 100644
View file @ 569ad66e
#pragma once
#include "common.hip.hpp"
#include "ConstantTensorDescriptor.hip.hpp"
#include "ConstantMatrixDescriptor.hip.hpp"
#include "blockwise_2d_tensor_op.hip.hpp"
#include "blockwise_4d_tensor_op.hip.hpp"
#include "threadwise_nd_tensor_op.hip.hpp"
#include "threadwise_4d_tensor_op.hip.hpp"
#include "blockwise_batched_gemm.hip.hpp"
template <index_t GridSize,
index_t BlockSize,
class Float,
class InGlobalDesc,
class WeiGlobalDesc,
class OutGlobalDesc,
index_t NPerBlock,
index_t KPerBlock,
index_t CPerBlock,
index_t HoPerBlock,
index_t WoPerBlock,
index_t NPerThread,
index_t KPerThread,
index_t HoPerThread,
index_t WoPerThread,
index_t GemmMPerThreadSubC,
index_t GemmNPerThreadSubC,
index_t GemmMLevel0Cluster,
index_t GemmNLevel0Cluster,
index_t GemmMLevel1Cluster,
index_t GemmNLevel1Cluster,
index_t GemmKPerThreadLoop,
index_t GemmDataPerReadA,
index_t GemmDataPerReadB,
class InBlockReorderSrcSubLengths_NCHW,
class InBlockReorderSrcClusterLengths_NCHW,
class InBlockReorderMapThreadCluster2SrcCluster_CHNW2NCHW,
index_t InBlockReorderDataPerRead_W,
index_t InBlockReorderDataPerWrite_N,
class WeiBlockCopyClusterLengths_CK, // not used
index_t WeiBlockCopyDataPerRead_K,
index_t OutThreadCopyDataPerWrite_N>
struct GridwiseConvolutionImplicitGemm_v1r3_lds_double_buffer_nchw_cyxk_khwn
{
__device__ void Run(const Float* const __restrict__ p_in_global,
const Float* const __restrict__ p_wei_global,
Float* const __restrict__ p_out_global) const
{
// be careful of this assertion
static_assert(NPerBlock % NPerThread == 0 && (GemmNPerThreadSubC <= NPerBlock &&
NPerBlock % GemmNPerThreadSubC == 0) ||
(GemmNPerThreadSubC >= NPerBlock && NPerThread == NPerBlock &&
GemmNPerThreadSubC % NPerThread == 0),
"wrong!");
constexpr auto I0 = Number<0>{};
constexpr auto I1 = Number<1>{};
constexpr auto I2 = Number<2>{};
constexpr auto I3 = Number<3>{};
constexpr auto in_n_c_h_w_global_desc = InGlobalDesc{};
constexpr auto wei_c_y_x_k_global_desc = WeiGlobalDesc{};
constexpr auto out_k_h_w_n_global_desc = OutGlobalDesc{};
constexpr index_t C = in_n_c_h_w_global_desc.GetLength(I1);
constexpr index_t K = out_k_h_w_n_global_desc.GetLength(I0);
constexpr index_t Ho = out_k_h_w_n_global_desc.GetLength(I1);
constexpr index_t Wo = out_k_h_w_n_global_desc.GetLength(I2);
constexpr index_t N = out_k_h_w_n_global_desc.GetLength(I3);
constexpr index_t Y = wei_c_y_x_k_global_desc.GetLength(I1);
constexpr index_t X = wei_c_y_x_k_global_desc.GetLength(I2);
// assert for LDS double buffer
static_assert(C % (2 * CPerBlock) == 0, "C cannot be evenly divided");
// divide block work: [K, Ho, Wo, N]
static_assert(N % NPerBlock == 0 && K % KPerBlock == 0 && C % CPerBlock == 0 &&
Ho % HoPerBlock == 0 && Wo % WoPerBlock == 0,
"wrong! cannot evenly divide work for workgroup ");
constexpr index_t KBlockWork = (K + KPerBlock - 1) / KPerBlock;
constexpr index_t HBlockWork = (Ho + HoPerBlock - 1) / HoPerBlock;
constexpr index_t WBlockWork = (Wo + WoPerBlock - 1) / WoPerBlock;
constexpr index_t NBlockWork = (N + NPerBlock - 1) / NPerBlock;
const index_t k_block_work_id = get_block_1d_id() / (HBlockWork * WBlockWork * NBlockWork);
index_t itmp = get_block_1d_id() - k_block_work_id * (HBlockWork * WBlockWork * NBlockWork);
const index_t h_block_work_id = itmp / (WBlockWork * NBlockWork);
itmp -= h_block_work_id * (WBlockWork * NBlockWork);
const index_t w_block_work_id = itmp / NBlockWork;
const index_t n_block_work_id = itmp - w_block_work_id * NBlockWork;
const index_t k_block_data_begin = k_block_work_id * KPerBlock;
const index_t ho_block_data_begin = h_block_work_id * HoPerBlock;
const index_t wo_block_data_begin = w_block_work_id * WoPerBlock;
const index_t n_block_data_begin = n_block_work_id * NPerBlock;
const index_t hi_block_data_begin = ho_block_data_begin;
const index_t wi_block_data_begin = wo_block_data_begin;
// global tensor view
constexpr auto wei_c_k_global_desc =
make_ConstantTensorDescriptor(Sequence<C, K>{}, Sequence<Y * X * K, 1>{});
// LDS tensor view
// be careful of alignment
constexpr index_t max_align = mod_conv::max(InBlockReorderDataPerWrite_N,
WeiBlockCopyDataPerRead_K,
GemmDataPerReadA,
GemmDataPerReadB);
constexpr auto in_c_h_w_n_block_desc = make_ConstantTensorDescriptor_aligned(
Sequence<CPerBlock, HoPerBlock, WoPerBlock, NPerBlock>{},
Number<InBlockReorderDataPerWrite_N>{});
// this check is ad-hoc
// TODO: need to properly implement tensor descriptor with alignment
static_assert(in_c_h_w_n_block_desc.GetStride(I1) % GemmDataPerReadB == 0,
"GemmDataPerReadB alignment requirement is not meet");
constexpr auto wei_c_k_block_desc = make_ConstantTensorDescriptor_aligned(
Sequence<CPerBlock, KPerBlock>{},
Number<mod_conv::max(WeiBlockCopyDataPerRead_K, GemmDataPerReadA)>{});
// tensor view of threadwise output in register
constexpr auto out_k_h_w_n_thread_desc = make_ConstantTensorDescriptor(
Sequence<KPerThread, HoPerThread, WoPerThread, NPerThread>{});
// blockwise copy
// input: format is [N, C, Hi, Wi] to [C, Hi, Wi, N]
constexpr auto map_chwn2nchw = Sequence<1, 2, 3, 0>{};
const auto blockwise_in_copy_reorder =
Blockwise4dTensorCopyReorder3<BlockSize,
Float,
decltype(in_n_c_h_w_global_desc),
decltype(in_c_h_w_n_block_desc),
Sequence<NPerBlock, CPerBlock, HoPerBlock, WoPerBlock>,
InBlockReorderSrcSubLengths_NCHW,
InBlockReorderSrcClusterLengths_NCHW,
decltype(map_chwn2nchw),
InBlockReorderMapThreadCluster2SrcCluster_CHNW2NCHW,
InBlockReorderDataPerRead_W,
InBlockReorderDataPerWrite_N>{};
// blockwise wei copy
// format is [CPerBlock, KPerBlock]
const auto blockwise_wei_copy =
Blockwise2dTensorCopy3<BlockSize,
Float,
decltype(wei_c_k_global_desc),
decltype(wei_c_k_block_desc),
decltype(wei_c_k_block_desc.GetLengths()),
WeiBlockCopyDataPerRead_K>{};
// a series of blockwise batched GEMM
// C_matrix += transpose(A_matrix) * B_matrix
// A_matrix and B_matrix saved in LDS, C_matrix saved in register
// A_matrix[C,K] is a sub-matrix of wei_block[C,K]
// B_matrix[C,Wo*N] is a sub-matrix of in_block[C,Hi,Wi,N]
// C_matrix[K,Wo*N] is a sub-matrix of out_block[K,Ho,Wo,N]
constexpr auto a_c_k_block_mtx_desc = make_ConstantMatrixDescriptor(
Number<CPerBlock>{}, Number<KPerBlock>{}, Number<wei_c_k_block_desc.GetStride(I0)>{});
constexpr auto b_c_wn_block_mtx_desc =
make_ConstantMatrixDescriptor(Number<CPerBlock>{},
Number<WoPerBlock * NPerBlock>{},
Number<in_c_h_w_n_block_desc.GetStride(I0)>{});
constexpr auto c_k_wn_thread_mtx_desc =
make_ConstantMatrixDescriptor(Number<KPerThread>{},
Number<WoPerThread * NPerThread>{},
Number<out_k_h_w_n_thread_desc.GetStride(I0)>{});
const auto blockwise_batch_gemm =
BlockwiseBatchGemmBlockABlockBThreadCTransANormalBNormalC_V2<
BlockSize,
decltype(a_c_k_block_mtx_desc),
decltype(b_c_wn_block_mtx_desc),
decltype(c_k_wn_thread_mtx_desc),
0,
in_c_h_w_n_block_desc.GetStride(I1),
out_k_h_w_n_thread_desc.GetStride(I1),
HoPerBlock,
GemmMPerThreadSubC,
GemmNPerThreadSubC,
GemmMLevel0Cluster,
GemmNLevel0Cluster,
GemmMLevel1Cluster,
GemmNLevel1Cluster,
GemmKPerThreadLoop,
HoPerThread,
GemmDataPerReadA,
GemmDataPerReadB>{};
// LDS: be careful of alignment
constexpr index_t in_block_space =
in_c_h_w_n_block_desc.GetElementSpace(Number<max_align>{});
constexpr index_t wei_block_space = wei_c_k_block_desc.GetElementSpace(Number<max_align>{});
// LDS double buffer
__shared__ Float p_in_block_double[2 * in_block_space];
__shared__ Float p_wei_block_double[2 * wei_block_space];
// register
// C++ lambda doesn't capture array, use pointer instead
Float p_out_thread_data[out_k_h_w_n_thread_desc.GetElementSpace()];
Float* const p_out_thread = p_out_thread_data;
#if 0
if(get_thread_local_1d_id() == 0 && get_block_1d_id() == 0)
{
print_ConstantTensorDescriptor(in_c_h_w_n_global_desc, "in_c_h_w_n_global_desc");
print_ConstantTensorDescriptor(wei_c_y_x_k_global_desc, "wei_c_y_x_k_global_desc");
print_ConstantTensorDescriptor(in_c_h_w_n_block_desc, "in_c_h_w_n_block_desc");
print_ConstantTensorDescriptor(wei_c_k_block_desc, "wei_c_k_block_desc");
printf("in_block_space %u, wei_block_space %u\n", in_block_space, wei_block_space);
}
#endif
// set threadwise output tensor to 0
threadwise_4d_tensor_set_zero(out_k_h_w_n_thread_desc, p_out_thread);
for(index_t y = 0; y < Y; ++y)
{
for(index_t x = 0; x < X; ++x)
{
const Float* p_in_global_block_offset =
p_in_global +
in_n_c_h_w_global_desc.Get1dIndex(
n_block_data_begin, 0, hi_block_data_begin + y, wi_block_data_begin + x);
const Float* p_wei_global_block_offset =
p_wei_global + wei_c_y_x_k_global_desc.Get1dIndex(0, y, x, k_block_data_begin);
// LDS double buffer: preload data into LDS
{
Float p_in_register_clipboard[blockwise_in_copy_reorder
.GetRegisterClipboardSize()];
Float p_wei_register_clipboard[blockwise_wei_copy.GetRegisterClipboardSize()];
blockwise_in_copy_reorder.RunLoadRegisterClipboard(p_in_global_block_offset,
p_in_register_clipboard);
blockwise_wei_copy.RunLoadRegisterClipboard(p_wei_global_block_offset,
p_wei_register_clipboard);
blockwise_in_copy_reorder.RunStoreRegisterClipboard(p_in_register_clipboard,
p_in_block_double);
blockwise_wei_copy.RunStoreRegisterClipboard(p_wei_register_clipboard,
p_wei_block_double);
}
// LDS double buffer: main body
for(index_t c_block_data_begin = 0; c_block_data_begin + 2 * CPerBlock < C;
c_block_data_begin += 2 * CPerBlock)
{
#pragma unroll
for(index_t iloop = 0; iloop < 2; ++iloop)
{
const bool even_loop = (iloop % 2 == 0);
Float* p_in_block_now =
even_loop ? p_in_block_double : p_in_block_double + in_block_space;
Float* p_wei_block_now =
even_loop ? p_wei_block_double : p_wei_block_double + wei_block_space;
Float* p_in_block_next =
even_loop ? p_in_block_double + in_block_space : p_in_block_double;
Float* p_wei_block_next =
even_loop ? p_wei_block_double + wei_block_space : p_wei_block_double;
Float p_in_register_clipboard[blockwise_in_copy_reorder
.GetRegisterClipboardSize()];
Float
p_wei_register_clipboard[blockwise_wei_copy.GetRegisterClipboardSize()];
p_in_global_block_offset +=
CPerBlock * in_n_c_h_w_global_desc.GetStride(I1);
p_wei_global_block_offset +=
CPerBlock * wei_c_y_x_k_global_desc.GetStride(I0);
__syncthreads();
// LDS doubel buffer: load next data from device mem
blockwise_in_copy_reorder.RunLoadRegisterClipboard(p_in_global_block_offset,
p_in_register_clipboard);
blockwise_wei_copy.RunLoadRegisterClipboard(p_wei_global_block_offset,
p_wei_register_clipboard);
// LDS double buffer: GEMM on current data
blockwise_batch_gemm.Run(p_wei_block_now, p_in_block_now, p_out_thread);
// LDS double buffer: store next data to LDS
blockwise_in_copy_reorder.RunStoreRegisterClipboard(p_in_register_clipboard,
p_in_block_next);
blockwise_wei_copy.RunStoreRegisterClipboard(p_wei_register_clipboard,
p_wei_block_next);
}
}
// LDS double buffer: tail
{
Float p_in_register_clipboard[blockwise_in_copy_reorder
.GetRegisterClipboardSize()];
Float p_wei_register_clipboard[blockwise_wei_copy.GetRegisterClipboardSize()];
// even iteration
p_in_global_block_offset += CPerBlock * in_n_c_h_w_global_desc.GetStride(I1);
p_wei_global_block_offset += CPerBlock * wei_c_y_x_k_global_desc.GetStride(I0);
__syncthreads();
// LDS doubel buffer: load next data from device mem
blockwise_in_copy_reorder.RunLoadRegisterClipboard(p_in_global_block_offset,
p_in_register_clipboard);
blockwise_wei_copy.RunLoadRegisterClipboard(p_wei_global_block_offset,
p_wei_register_clipboard);
// LDS double buffer: GEMM on current data
blockwise_batch_gemm.Run(p_wei_block_double, p_in_block_double, p_out_thread);
// LDS double buffer: store next data to LDS
blockwise_in_copy_reorder.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
blockwise_batch_gemm.Run(p_wei_block_double + wei_block_space,
p_in_block_double + in_block_space,
p_out_thread);
}
}
}
// output: register to global mem,
const auto c_thread_mtx_begin =
blockwise_batch_gemm.GetBeginOfThreadMatrixC(get_thread_local_1d_id());
const index_t k_thread_data_begin = c_thread_mtx_begin.row;
const index_t ho_thread_data_begin = c_thread_mtx_begin.batch;
const index_t wo_thread_data_begin = c_thread_mtx_begin.col / NPerBlock;
const index_t n_thread_data_begin = c_thread_mtx_begin.col % NPerBlock;
static_if<GemmNPerThreadSubC <= NPerBlock>{}(
[&](auto f_dummy) { // f_dummy do nothing but perfect forwarding. Using this trick to
// make this lambda a generic lambda, so it won't be compiled until
// instantiated
static_assert((f_dummy(GemmNPerThreadSubC) <= NPerBlock &&
NPerBlock % GemmNPerThreadSubC == 0),
"wrong!");
// output is a 10d tensor
constexpr index_t N2 = GemmNPerThreadSubC;
constexpr index_t N1 = NPerBlock / N2;
constexpr index_t W2 = (GemmNLevel0Cluster * GemmNLevel1Cluster) /
f_dummy(NPerBlock / GemmNPerThreadSubC);
constexpr index_t W1 = WoPerBlock / W2;
constexpr index_t K2 = GemmMPerThreadSubC;
constexpr index_t K1 = KPerBlock / KPerThread;
constexpr auto out_10d_global_desc =
make_ConstantTensorDescriptor(Sequence<K / (K1 * K2),
K1,
K2,
Ho,
Wo / (W1 * W2),
W1,
W2,
N / f_dummy(N1 * N2),
N1,
N2>{});
constexpr auto out_10d_thread_desc = make_ConstantTensorDescriptor(
Sequence<KPerThread / K2, 1, K2, HoPerThread, 1, W1, 1, 1, 1, N2>{});
#if 0
if(get_thread_local_1d_id() == 0 && get_block_1d_id() == 0)
{
print_ConstantTensorDescriptor(out_k_h_w_n_thread_desc,
"out_k_h_w_n_thread_desc");
print_ConstantTensorDescriptor(out_10d_thread_desc, "out_10d_thread_desc");
print_ConstantTensorDescriptor(out_k_h_w_n_global_desc,
"out_k_h_w_n_global_desc");
print_ConstantTensorDescriptor(out_10d_global_desc, "out_10d_global_desc");
}
#endif
threadwise_nd_tensor_copy(out_10d_thread_desc,
p_out_thread,
out_10d_global_desc,
p_out_global +
out_k_h_w_n_global_desc.Get1dIndex(
k_block_data_begin + k_thread_data_begin,
ho_block_data_begin + ho_thread_data_begin,
wo_block_data_begin + wo_thread_data_begin,
n_block_data_begin + n_thread_data_begin),
out_10d_thread_desc.GetLengths(),
Number<OutThreadCopyDataPerWrite_N>{});
})
.else_([&](auto f_dummy) {
static_assert(f_dummy(GemmNPerThreadSubC) >= NPerBlock && NPerThread == NPerBlock &&
GemmNPerThreadSubC % NPerThread == 0,
"wrong!");
// output is a 10d tensor
constexpr index_t N1 = NPerBlock;
constexpr index_t W3 = GemmNPerThreadSubC / NPerBlock;
constexpr index_t W2 = GemmNLevel0Cluster * GemmNLevel1Cluster;
constexpr index_t W1 = WoPerBlock / f_dummy(W2 * W3);
constexpr index_t K2 = GemmMPerThreadSubC;
constexpr index_t K1 = KPerBlock / KPerThread;
constexpr auto out_10d_global_desc =
make_ConstantTensorDescriptor(Sequence<K / (K1 * K2),
K1,
K2,
Ho,
Wo / (W1 * W2 * W3),
W1,
W2,
W3,
N / N1,
N1>{});
constexpr auto out_10d_thread_desc = make_ConstantTensorDescriptor(
Sequence<KPerThread / K2, 1, K2, HoPerThread, 1, W1, 1, W3, 1, N1>{});
#if 0
if(get_thread_local_1d_id() == 0 && get_block_1d_id() == 0)
{
print_ConstantTensorDescriptor(out_k_h_w_n_thread_desc,
"out_k_h_w_n_thread_desc");
print_ConstantTensorDescriptor(out_10d_thread_desc, "out_10d_thread_desc");
print_ConstantTensorDescriptor(out_k_h_w_n_global_desc,
"out_k_h_w_n_global_desc");
print_ConstantTensorDescriptor(out_10d_global_desc, "out_10d_global_desc");
for(index_t i = 0; i < 64; ++i)
{
printf("out %f, ", p_out_thread[i]);
}
}
#endif
threadwise_nd_tensor_copy(out_10d_thread_desc,
p_out_thread,
out_10d_global_desc,
p_out_global +
out_k_h_w_n_global_desc.Get1dIndex(
k_block_data_begin + k_thread_data_begin,
ho_block_data_begin + ho_thread_data_begin,
wo_block_data_begin + wo_thread_data_begin,
n_block_data_begin + n_thread_data_begin),
out_10d_thread_desc.GetLengths(),
Number<OutThreadCopyDataPerWrite_N>{});
});
}
};
src/include/gridwise_convolution_implicit_gemm_v1r3_nchw_cyxk_khwn.hip.hpp 0 → 100644
View file @ 569ad66e
#pragma once
#include "common.hip.hpp"
#include "ConstantTensorDescriptor.hip.hpp"
#include "ConstantMatrixDescriptor.hip.hpp"
#include "blockwise_2d_tensor_op.hip.hpp"
#include "blockwise_4d_tensor_op.hip.hpp"
#include "threadwise_nd_tensor_op.hip.hpp"
#include "threadwise_4d_tensor_op.hip.hpp"
#include "blockwise_batched_gemm.hip.hpp"
template <index_t GridSize,
index_t BlockSize,
class Float,
class InGlobalDesc,
class WeiGlobalDesc,
class OutGlobalDesc,
index_t NPerBlock,
index_t KPerBlock,
index_t CPerBlock,
index_t HoPerBlock,
index_t WoPerBlock,
index_t NPerThread,
index_t KPerThread,
index_t HoPerThread,
index_t WoPerThread,
index_t GemmMPerThreadSubC,
index_t GemmNPerThreadSubC,
index_t GemmMLevel0Cluster,
index_t GemmNLevel0Cluster,
index_t GemmMLevel1Cluster,
index_t GemmNLevel1Cluster,
index_t GemmKPerThreadLoop,
index_t GemmDataPerReadA,
index_t GemmDataPerReadB,
class InBlockReorderSrcSubLengths_NCHW,
class InBlockReorderSrcClusterLengths_NCHW,
class InBlockReorderMapThreadCluster2SrcCluster_CHNW2NCHW,
index_t InBlockReorderDataPerRead_W,
index_t InBlockReorderDataPerWrite_N,
class WeiBlockCopyClusterLengths_CK, // not used
index_t WeiBlockCopyDataPerRead_K,
index_t OutThreadCopyDataPerWrite_N>
struct GridwiseConvolutionImplicitGemm_v1r3_nchw_cyxk_khwn
{
__device__ void Run(const Float* const __restrict__ p_in_global,
const Float* const __restrict__ p_wei_global,
Float* const __restrict__ p_out_global) const
{
// be careful of this assertion
static_assert(NPerBlock % NPerThread == 0 && (GemmNPerThreadSubC <= NPerBlock &&
NPerBlock % GemmNPerThreadSubC == 0) ||
(GemmNPerThreadSubC >= NPerBlock && NPerThread == NPerBlock &&
GemmNPerThreadSubC % NPerThread == 0),
"wrong!");
constexpr auto I0 = Number<0>{};
constexpr auto I1 = Number<1>{};
constexpr auto I2 = Number<2>{};
constexpr auto I3 = Number<3>{};
constexpr auto in_n_c_h_w_global_desc = InGlobalDesc{};
constexpr auto wei_c_y_x_k_global_desc = WeiGlobalDesc{};
constexpr auto out_k_h_w_n_global_desc = OutGlobalDesc{};
constexpr index_t C = in_n_c_h_w_global_desc.GetLength(I1);
constexpr index_t K = out_k_h_w_n_global_desc.GetLength(I0);
constexpr index_t Ho = out_k_h_w_n_global_desc.GetLength(I1);
constexpr index_t Wo = out_k_h_w_n_global_desc.GetLength(I2);
constexpr index_t N = out_k_h_w_n_global_desc.GetLength(I3);
constexpr index_t Y = wei_c_y_x_k_global_desc.GetLength(I1);
constexpr index_t X = wei_c_y_x_k_global_desc.GetLength(I2);
// divide block work: [K, Ho, Wo, N]
static_assert(N % NPerBlock == 0 && K % KPerBlock == 0 && C % CPerBlock == 0 &&
Ho % HoPerBlock == 0 && Wo % WoPerBlock == 0,
"wrong! cannot evenly divide work for workgroup ");
constexpr index_t KBlockWork = (K + KPerBlock - 1) / KPerBlock;
constexpr index_t HBlockWork = (Ho + HoPerBlock - 1) / HoPerBlock;
constexpr index_t WBlockWork = (Wo + WoPerBlock - 1) / WoPerBlock;
constexpr index_t NBlockWork = (N + NPerBlock - 1) / NPerBlock;
const index_t k_block_work_id = get_block_1d_id() / (HBlockWork * WBlockWork * NBlockWork);
index_t itmp = get_block_1d_id() - k_block_work_id * (HBlockWork * WBlockWork * NBlockWork);
const index_t h_block_work_id = itmp / (WBlockWork * NBlockWork);
itmp -= h_block_work_id * (WBlockWork * NBlockWork);
const index_t w_block_work_id = itmp / NBlockWork;
const index_t n_block_work_id = itmp - w_block_work_id * NBlockWork;
const index_t k_block_data_begin = k_block_work_id * KPerBlock;
const index_t ho_block_data_begin = h_block_work_id * HoPerBlock;
const index_t wo_block_data_begin = w_block_work_id * WoPerBlock;
const index_t n_block_data_begin = n_block_work_id * NPerBlock;
const index_t hi_block_data_begin = ho_block_data_begin;
const index_t wi_block_data_begin = wo_block_data_begin;
// global tensor view
constexpr auto wei_c_k_global_desc =
make_ConstantTensorDescriptor(Sequence<C, K>{}, Sequence<Y * X * K, 1>{});
// LDS tensor view
// be careful of alignment
constexpr index_t max_align = mod_conv::max(InBlockReorderDataPerWrite_N,
WeiBlockCopyDataPerRead_K,
GemmDataPerReadA,
GemmDataPerReadB);
constexpr auto in_c_h_w_n_block_desc = make_ConstantTensorDescriptor_aligned(
Sequence<CPerBlock, HoPerBlock, WoPerBlock, NPerBlock>{},
Number<InBlockReorderDataPerWrite_N>{});
// this check is ad-hoc
// TODO: need to properly implement tensor descriptor with alignment
static_assert(in_c_h_w_n_block_desc.GetStride(I1) % GemmDataPerReadB == 0,
"GemmDataPerReadB alignment requirement is not meet");
constexpr auto wei_c_k_block_desc = make_ConstantTensorDescriptor_aligned(
Sequence<CPerBlock, KPerBlock>{},
Number<mod_conv::max(WeiBlockCopyDataPerRead_K, GemmDataPerReadA)>{});
// tensor view of threadwise output in register
constexpr auto out_k_h_w_n_thread_desc = make_ConstantTensorDescriptor(
Sequence<KPerThread, HoPerThread, WoPerThread, NPerThread>{});
// blockwise copy
// input: format is [N, C, Hi, Wi] to [C, Hi, Wi, N]
constexpr auto map_chwn2nchw = Sequence<1, 2, 3, 0>{};
const auto blockwise_in_copy_reorder =
Blockwise4dTensorCopyReorder3<BlockSize,
Float,
decltype(in_n_c_h_w_global_desc),
decltype(in_c_h_w_n_block_desc),
Sequence<NPerBlock, CPerBlock, HoPerBlock, WoPerBlock>,
InBlockReorderSrcSubLengths_NCHW,
InBlockReorderSrcClusterLengths_NCHW,
decltype(map_chwn2nchw),
InBlockReorderMapThreadCluster2SrcCluster_CHNW2NCHW,
InBlockReorderDataPerRead_W,
InBlockReorderDataPerWrite_N>{};
// blockwise wei copy
// format is [CPerBlock, KPerBlock]
const auto blockwise_wei_copy =
Blockwise2dTensorCopy3<BlockSize,
Float,
decltype(wei_c_k_global_desc),
decltype(wei_c_k_block_desc),
decltype(wei_c_k_block_desc.GetLengths()),
WeiBlockCopyDataPerRead_K>{};
// a series of blockwise batched GEMM
// C_matrix += transpose(A_matrix) * B_matrix
// A_matrix and B_matrix saved in LDS, C_matrix saved in register
// A_matrix[C,K] is a sub-matrix of wei_block[C,K]
// B_matrix[C,Wo*N] is a sub-matrix of in_block[C,Hi,Wi,N]
// C_matrix[K,Wo*N] is a sub-matrix of out_block[K,Ho,Wo,N]
constexpr auto a_c_k_block_mtx_desc = make_ConstantMatrixDescriptor(
Number<CPerBlock>{}, Number<KPerBlock>{}, Number<wei_c_k_block_desc.GetStride(I0)>{});
constexpr auto b_c_wn_block_mtx_desc =
make_ConstantMatrixDescriptor(Number<CPerBlock>{},
Number<WoPerBlock * NPerBlock>{},
Number<in_c_h_w_n_block_desc.GetStride(I0)>{});
constexpr auto c_k_wn_thread_mtx_desc =
make_ConstantMatrixDescriptor(Number<KPerThread>{},
Number<WoPerThread * NPerThread>{},
Number<out_k_h_w_n_thread_desc.GetStride(I0)>{});
const auto blockwise_batch_gemm =
BlockwiseBatchGemmBlockABlockBThreadCTransANormalBNormalC_V2<
BlockSize,
decltype(a_c_k_block_mtx_desc),
decltype(b_c_wn_block_mtx_desc),
decltype(c_k_wn_thread_mtx_desc),
0,
in_c_h_w_n_block_desc.GetStride(I1),
out_k_h_w_n_thread_desc.GetStride(I1),
HoPerBlock,
GemmMPerThreadSubC,
GemmNPerThreadSubC,
GemmMLevel0Cluster,
GemmNLevel0Cluster,
GemmMLevel1Cluster,
GemmNLevel1Cluster,
GemmKPerThreadLoop,
HoPerThread,
GemmDataPerReadA,
GemmDataPerReadB>{};
// LDS: be careful of alignment
constexpr index_t in_block_space =
in_c_h_w_n_block_desc.GetElementSpace(Number<max_align>{});
constexpr index_t wei_block_space = wei_c_k_block_desc.GetElementSpace(Number<max_align>{});
__shared__ Float p_in_block[in_block_space];
__shared__ Float p_wei_block[wei_block_space];
// register
// C++ lambda doesn't capture array, use pointer instead
Float p_out_thread_data[out_k_h_w_n_thread_desc.GetElementSpace()];
Float* const p_out_thread = p_out_thread_data;
#if 0
if(get_thread_local_1d_id() == 0 && get_block_1d_id() == 0)
{
print_ConstantTensorDescriptor(in_c_h_w_n_global_desc, "in_c_h_w_n_global_desc");
print_ConstantTensorDescriptor(wei_c_y_x_k_global_desc, "wei_c_y_x_k_global_desc");
print_ConstantTensorDescriptor(in_c_h_w_n_block_desc, "in_c_h_w_n_block_desc");
print_ConstantTensorDescriptor(wei_c_k_block_desc, "wei_c_k_block_desc");
printf("in_block_space %u, wei_block_space %u\n", in_block_space, wei_block_space);
}
#endif
// set threadwise output tensor to 0
threadwise_4d_tensor_set_zero(out_k_h_w_n_thread_desc, p_out_thread);
#if 1
const Float* p_in_global_block_offset =
p_in_global + in_n_c_h_w_global_desc.Get1dIndex(
n_block_data_begin, 0, hi_block_data_begin, wi_block_data_begin);
const Float* p_wei_global_block_offset =
p_wei_global + wei_c_y_x_k_global_desc.Get1dIndex(0, 0, 0, k_block_data_begin);
for(index_t c_block_data_begin = 0; c_block_data_begin < C; c_block_data_begin += CPerBlock,
p_in_global_block_offset += CPerBlock * in_n_c_h_w_global_desc.GetStride(I1),
p_wei_global_block_offset += CPerBlock * wei_c_y_x_k_global_desc.GetStride(I0))
{
for(index_t y = 0; y < Y; ++y)
{
for(index_t x = 0; x < X; ++x)
{
#if 1
blockwise_in_copy_reorder.Run(p_in_global_block_offset +
in_n_c_h_w_global_desc.Get1dIndex(0, 0, y, x),
p_in_block);
blockwise_wei_copy.Run(p_wei_global_block_offset +
wei_c_y_x_k_global_desc.Get1dIndex(0, y, x, 0),
p_wei_block);
#else
Float p_in_clipboard[blockwise_in_copy_reorder.GetRegisterClipboardSize()];
Float p_wei_clipboard[blockwise_wei_copy.GetRegisterClipboardSize()];
blockwise_in_copy_reorder.RunLoadRegisterClipboard(
p_in_global_block_offset + in_n_c_h_w_global_desc.Get1dIndex(0, 0, y, x),
p_in_clipboard);
blockwise_wei_copy.RunLoadRegisterClipboard(
p_wei_global_block_offset + wei_c_y_x_k_global_desc.Get1dIndex(0, y, x, 0),
p_wei_clipboard);
blockwise_wei_copy.RunStoreRegisterClipboard(p_wei_clipboard, p_wei_block);
blockwise_in_copy_reorder.RunStoreRegisterClipboard(p_in_clipboard, p_in_block);
#endif
__syncthreads();
blockwise_batch_gemm.Run(p_wei_block, p_in_block, p_out_thread);
__syncthreads();
}
}
}
#else
for(index_t y = 0; y < Y; ++y)
{
for(index_t x = 0; x < X; ++x)
{
const Float* p_in_global_block_offset =
p_in_global +
in_n_c_h_w_global_desc.Get1dIndex(
n_block_data_begin, 0, hi_block_data_begin + y, wi_block_data_begin + x);
const Float* p_wei_global_block_offset =
p_wei_global + wei_c_y_x_k_global_desc.Get1dIndex(0, y, x, k_block_data_begin);
for(index_t c_block_data_begin = 0; c_block_data_begin < C;
c_block_data_begin += CPerBlock,
p_in_global_block_offset +=
CPerBlock * in_n_c_h_w_global_desc.GetStride(I1),
p_wei_global_block_offset +=
CPerBlock * wei_c_y_x_k_global_desc.GetStride(I0))
{
#if 0
blockwise_in_copy_reorder.Run(p_in_global_block_offset,
p_in_block);
blockwise_wei_copy.Run(p_wei_global_block_offset,
p_wei_block);
#else
Float p_in_clipboard[blockwise_in_copy_reorder.GetRegisterClipboardSize()];
Float p_wei_clipboard[blockwise_wei_copy.GetRegisterClipboardSize()];
blockwise_in_copy_reorder.RunLoadRegisterClipboard(p_in_global_block_offset,
p_in_clipboard);
blockwise_wei_copy.RunLoadRegisterClipboard(p_wei_global_block_offset,
p_wei_clipboard);
blockwise_wei_copy.RunStoreRegisterClipboard(p_wei_clipboard, p_wei_block);
blockwise_in_copy_reorder.RunStoreRegisterClipboard(p_in_clipboard, p_in_block);
#endif
__syncthreads();
blockwise_batch_gemm.Run(p_wei_block, p_in_block, p_out_thread);
__syncthreads();
}
}
}
#endif
// output: register to global mem,
const auto c_thread_mtx_begin =
blockwise_batch_gemm.GetBeginOfThreadMatrixC(get_thread_local_1d_id());
const index_t k_thread_data_begin = c_thread_mtx_begin.row;
const index_t ho_thread_data_begin = c_thread_mtx_begin.batch;
const index_t wo_thread_data_begin = c_thread_mtx_begin.col / NPerBlock;
const index_t n_thread_data_begin = c_thread_mtx_begin.col % NPerBlock;
static_if<GemmNPerThreadSubC <= NPerBlock>{}(
[&](auto f_dummy) { // f_dummy do nothing but perfect forwarding. Using this trick to
// make this lambda a generic lambda, so it won't be compiled until
// instantiated
static_assert((f_dummy(GemmNPerThreadSubC) <= NPerBlock &&
NPerBlock % GemmNPerThreadSubC == 0),
"wrong!");
// output is a 10d tensor
constexpr index_t N2 = GemmNPerThreadSubC;
constexpr index_t N1 = NPerBlock / N2;
constexpr index_t W2 = (GemmNLevel0Cluster * GemmNLevel1Cluster) /
f_dummy(NPerBlock / GemmNPerThreadSubC);
constexpr index_t W1 = WoPerBlock / W2;
constexpr index_t K2 = GemmMPerThreadSubC;
constexpr index_t K1 = KPerBlock / KPerThread;
constexpr auto out_10d_global_desc =
make_ConstantTensorDescriptor(Sequence<K / (K1 * K2),
K1,
K2,
Ho,
Wo / (W1 * W2),
W1,
W2,
N / f_dummy(N1 * N2),
N1,
N2>{});
constexpr auto out_10d_thread_desc = make_ConstantTensorDescriptor(
Sequence<KPerThread / K2, 1, K2, HoPerThread, 1, W1, 1, 1, 1, N2>{});
#if 0
if(get_thread_local_1d_id() == 0 && get_block_1d_id() == 0)
{
print_ConstantTensorDescriptor(out_k_h_w_n_thread_desc,
"out_k_h_w_n_thread_desc");
print_ConstantTensorDescriptor(out_10d_thread_desc, "out_10d_thread_desc");
print_ConstantTensorDescriptor(out_k_h_w_n_global_desc,
"out_k_h_w_n_global_desc");
print_ConstantTensorDescriptor(out_10d_global_desc, "out_10d_global_desc");
}
#endif
threadwise_nd_tensor_copy(out_10d_thread_desc,
p_out_thread,
out_10d_global_desc,
p_out_global +
out_k_h_w_n_global_desc.Get1dIndex(
k_block_data_begin + k_thread_data_begin,
ho_block_data_begin + ho_thread_data_begin,
wo_block_data_begin + wo_thread_data_begin,
n_block_data_begin + n_thread_data_begin),
out_10d_thread_desc.GetLengths(),
Number<OutThreadCopyDataPerWrite_N>{});
})
.else_([&](auto f_dummy) {
static_assert(f_dummy(GemmNPerThreadSubC) >= NPerBlock && NPerThread == NPerBlock &&
GemmNPerThreadSubC % NPerThread == 0,
"wrong!");
// output is a 10d tensor
constexpr index_t N1 = NPerBlock;
constexpr index_t W3 = GemmNPerThreadSubC / NPerBlock;
constexpr index_t W2 = GemmNLevel0Cluster * GemmNLevel1Cluster;
constexpr index_t W1 = WoPerBlock / f_dummy(W2 * W3);
constexpr index_t K2 = GemmMPerThreadSubC;
constexpr index_t K1 = KPerBlock / KPerThread;
constexpr auto out_10d_global_desc =
make_ConstantTensorDescriptor(Sequence<K / (K1 * K2),
K1,
K2,
Ho,
Wo / (W1 * W2 * W3),
W1,
W2,
W3,
N / N1,
N1>{});
constexpr auto out_10d_thread_desc = make_ConstantTensorDescriptor(
Sequence<KPerThread / K2, 1, K2, HoPerThread, 1, W1, 1, W3, 1, N1>{});
#if 0
if(get_thread_local_1d_id() == 0 && get_block_1d_id() == 0)
{
print_ConstantTensorDescriptor(out_k_h_w_n_thread_desc,
"out_k_h_w_n_thread_desc");
print_ConstantTensorDescriptor(out_10d_thread_desc, "out_10d_thread_desc");
print_ConstantTensorDescriptor(out_k_h_w_n_global_desc,
"out_k_h_w_n_global_desc");
print_ConstantTensorDescriptor(out_10d_global_desc, "out_10d_global_desc");
for(index_t i = 0; i < 64; ++i)
{
printf("out %f, ", p_out_thread[i]);
}
}
#endif
threadwise_nd_tensor_copy(out_10d_thread_desc,
p_out_thread,
out_10d_global_desc,
p_out_global +
out_k_h_w_n_global_desc.Get1dIndex(
k_block_data_begin + k_thread_data_begin,
ho_block_data_begin + ho_thread_data_begin,
wo_block_data_begin + wo_thread_data_begin,
n_block_data_begin + n_thread_data_begin),
out_10d_thread_desc.GetLengths(),
Number<OutThreadCopyDataPerWrite_N>{});
});
}
};
src/include/threadwise_2d_tensor_op.hip.hpp
View file @ 569ad66e
......@@ -88,6 +88,7 @@ threadwise_2d_tensor_copy_reorder_by_get_dst_from_src(SrcDesc,
SrcDesc{}, p_src, DstDesc{}, p_dst, SrcOpLengths{}, MapDst2Src{}, f_copy);
}
#if 0 // replaced threadwise_nd_tensor_copy
template <class Float, class SrcDesc, class DstDesc, class SrcOpLengths>
__device__ void threadwise_2d_tensor_copy(
SrcDesc, Float* const __restrict__ p_src, DstDesc, Float* __restrict__ p_dst, SrcOpLengths)
......@@ -97,6 +98,7 @@ __device__ void threadwise_2d_tensor_copy(
threadwise_2d_tensor_copy_reorder_by_get_dst_from_src(
SrcDesc{}, p_src, DstDesc{}, p_dst, SrcOpLengths{}, dst_from_src_reorder);
}
#endif
template <class Float, class Desc, class IDim, class NShift>
__device__ void threadwise_2d_tensor_shift_down(Desc, Float* __restrict__ p, IDim, NShift)
......
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