Commit 33d1e0e2 authored by Chao Liu's avatar Chao Liu
Browse files

refactoring for miopen

parent b1cb48a0
......@@ -264,7 +264,7 @@ struct GridwiseConvolutionImplicitGemm_v1r1_chwn_cyxk_khwn
#if 1
blockwise_batch_gemm.Run
#else
blockwise_batch_gemm.Run_asm
blockwise_batch_gemm.Run_amd_asm
#endif
(p_wei_block + wei_c_y_x_k_block_desc.GetOffsetFromMultiIndex(0, y, x, 0),
p_in_block + in_c_h_w_n_block_desc.GetOffsetFromMultiIndex(0, y, x, 0),
......
......@@ -191,7 +191,7 @@ struct GridwiseConvolutionImplicitGemm_v1r3_chwn_cyxk_khwn
#if 0
return blockwise_batch_gemm.Run(Xs...);
#elif 0
return blockwise_batch_gemm.Run_asm(Xs...);
return blockwise_batch_gemm.Run_amd_asm(Xs...);
#else
return blockwise_batch_gemm.Run_asm_v2(Xs...);
#endif
......
......@@ -206,7 +206,7 @@ struct GridwiseConvolutionImplicitGemm_v1r3_chwn_cyxk_khwn_lds_double_buffer
#if 1
return blockwise_batch_gemm.Run(Xs...);
#elif 0
return blockwise_batch_gemm.Run_asm(Xs...);
return blockwise_batch_gemm.Run_amd_asm(Xs...);
#else
return blockwise_batch_gemm.Run_asm_v2(Xs...);
#endif
......
......@@ -201,7 +201,7 @@ struct GridwiseConvolutionImplicitGemm_v1r3_nchw_cyxk_nkhw
#if 1
return blockwise_batch_gemm.Run(Xs...);
#elif 0
return blockwise_batch_gemm.Run_asm(Xs...);
return blockwise_batch_gemm.Run_amd_asm(Xs...);
#else
return blockwise_batch_gemm.Run_asm_v2(Xs...);
#endif
......
......@@ -203,7 +203,7 @@ struct GridwiseConvolutionImplicitGemm_v1r3_nchw_cyxk_nkhw_lds_double_buffer
#if 1
return blockwise_batch_gemm.Run(Xs...);
#elif 0
return blockwise_batch_gemm.Run_asm(Xs...);
return blockwise_batch_gemm.Run_amd_asm(Xs...);
#else
return blockwise_batch_gemm.Run_asm_v2(Xs...);
#endif
......
......@@ -238,7 +238,7 @@ struct GridwiseConvolutionImplicitGemm_v2_chwn_cyxk_khwn
#elif 0
blockwise_gemm.Run_RegisterDoubleBuffer
#elif 1
blockwise_gemm.Run_asm
blockwise_gemm.Run_amd_asm
#endif
(p_wei_block + wei_cyxk_block_desc.GetOffsetFromMultiIndex(0, y, x, 0),
p_in_block + y * Wi + x,
......
......@@ -271,7 +271,7 @@ struct GridwiseConvolutionImplicitGemm_v2_chwn_cyxk_khwn_lds_double_buffer
#elif 0
blockwise_gemm.Run_RegisterDoubleBuffer
#elif 0
blockwise_gemm.Run_asm
blockwise_gemm.Run_amd_asm
#endif
(p_wei_block_now +
wei_cyxk_block_desc.GetOffsetFromMultiIndex(0, y, x, 0),
......@@ -313,7 +313,7 @@ struct GridwiseConvolutionImplicitGemm_v2_chwn_cyxk_khwn_lds_double_buffer
#elif 0
blockwise_gemm.Run_RegisterDoubleBuffer
#elif 0
blockwise_gemm.Run_asm
blockwise_gemm.Run_amd_asm
#endif
(p_wei_block_double +
wei_cyxk_block_desc.GetOffsetFromMultiIndex(0, y, x, 0),
......@@ -339,7 +339,7 @@ struct GridwiseConvolutionImplicitGemm_v2_chwn_cyxk_khwn_lds_double_buffer
#elif 0
blockwise_gemm.Run_RegisterDoubleBuffer
#elif 0
blockwise_gemm.Run_asm
blockwise_gemm.Run_amd_asm
#endif
(p_wei_block_double + wei_block_space +
wei_cyxk_block_desc.GetOffsetFromMultiIndex(0, y, x, 0),
......
......@@ -217,7 +217,7 @@ struct GridwiseConvolutionImplicitGemm_v3_nchw_cyxk_nkhw
#if 1
return blockwise_gemm.Run(Xs...);
#else
return blockwise_gemm.Run_asm(Xs...);
return blockwise_gemm.Run_amd_asm(Xs...);
#endif
};
......
......@@ -214,7 +214,7 @@ struct GridwiseConvolutionImplicitGemm_v3_nchw_cyxk_nkhw_lds_double_buffer
#if 1
return blockwise_gemm.Run(Xs...);
#else
return blockwise_gemm.Run_asm(Xs...);
return blockwise_gemm.Run_amd_asm(Xs...);
#endif
};
......
......@@ -247,7 +247,7 @@ struct GridwiseConvolutionImplicitGemm_v4_nchw_kcyx_nkhw
#if 1
return blockwise_gemm.Run(Xs...);
#else
return blockwise_gemm.Run_asm(Xs...);
return blockwise_gemm.Run_amd_asm(Xs...);
#endif
};
......
......@@ -9,10 +9,6 @@
#include "blockwise_gemm.hpp"
#include "threadwise_generic_tensor_slice_copy.hpp"
#ifndef CK_BLOCKWISE_GEMM_USE_AMD_INLINE_ASM
#define CK_BLOCKWISE_GEMM_USE_AMD_INLINE_ASM 1
#endif
namespace ck {
// define B = merge(N0, Ho, Wo)
......@@ -239,15 +235,6 @@ struct GridwiseConvolutionImplicitGemm_v4_nchw_kcyx_nkhw_lds_double_buffer
GemmDataPerReadA,
GemmDataPerReadB>{};
// choose GEMM implementation here
const auto run_blockwise_gemm = [&](auto... Xs) {
#if CK_USE_AMD_INLINE_ASM && CK_BLOCKWISE_GEMM_USE_AMD_INLINE_ASM
return blockwise_gemm.Run_asm(Xs...);
#else
return blockwise_gemm.Run(Xs...);
#endif
};
// LDS allocation for input and weight: be careful of alignment
constexpr index_t max_align = math::lcm(InBlockCopyDstDataPerWrite_N2,
WeiBlockCopyDstDataPerWrite_K,
......@@ -255,9 +242,11 @@ struct GridwiseConvolutionImplicitGemm_v4_nchw_kcyx_nkhw_lds_double_buffer
GemmDataPerReadB);
constexpr index_t in_block_space =
in_e_n1_b_n2_block_desc.GetElementSpace(Number<max_align>{});
math::integer_divide_ceil(in_e_n1_b_n2_block_desc.GetElementSpace(), max_align) *
max_align;
constexpr index_t wei_block_space = wei_e_k_block_desc.GetElementSpace(Number<max_align>{});
constexpr index_t wei_block_space =
math::integer_divide_ceil(wei_e_k_block_desc.GetElementSpace(), max_align) * max_align;
__shared__ Float p_in_block_double[2 * in_block_space];
__shared__ Float p_wei_block_double[2 * wei_block_space];
......@@ -309,7 +298,7 @@ struct GridwiseConvolutionImplicitGemm_v4_nchw_kcyx_nkhw_lds_double_buffer
p_wei_register_clipboard);
// LDS double buffer: GEMM on current data
run_blockwise_gemm(p_wei_block_now, p_in_block_now, p_out_thread);
blockwise_gemm.Run(p_wei_block_now, p_in_block_now, p_out_thread);
// LDS double buffer: store next data to LDS
blockwise_in_copy.RunStoreRegisterClipboard(p_in_register_clipboard,
......@@ -336,7 +325,7 @@ struct GridwiseConvolutionImplicitGemm_v4_nchw_kcyx_nkhw_lds_double_buffer
p_wei_register_clipboard);
// LDS double buffer: GEMM on current data
run_blockwise_gemm(p_wei_block_double, p_in_block_double, p_out_thread);
blockwise_gemm.Run(p_wei_block_double, p_in_block_double, p_out_thread);
// LDS double buffer: store next data to LDS
blockwise_in_copy.RunStoreRegisterClipboard(p_in_register_clipboard,
......@@ -348,7 +337,7 @@ struct GridwiseConvolutionImplicitGemm_v4_nchw_kcyx_nkhw_lds_double_buffer
__syncthreads();
// LDS double buffer: GEMM on current data
run_blockwise_gemm(p_wei_block_double + wei_block_space,
blockwise_gemm.Run(p_wei_block_double + wei_block_space,
p_in_block_double + in_block_space,
p_out_thread);
}
......
......@@ -107,15 +107,12 @@ struct ConstantTensorDescriptor
return accumulate_on_sequence(Lengths{}, math::multiplies<index_t>{}, Number<1>{});
}
template <class Align = Number<1>>
__host__ __device__ static constexpr index_t GetElementSpace(Align align = Align{})
__host__ __device__ static constexpr index_t GetElementSpace()
{
// This is WRONG! align shouldbe applied to the last memory rank, not the last tensor
// dimension
constexpr index_t element_space_unaligned = accumulate_on_sequence(
(GetLengths() - Number<1>{}) * GetStrides(), math::plus<index_t>{}, Number<1>{});
return align.Get() * ((element_space_unaligned + align.Get() - 1) / align.Get());
return element_space_unaligned;
}
// emulate constexpr lambda
......@@ -234,7 +231,7 @@ struct ConstantTensorDescriptor
// do carry check in reversed order, starting from lowest dimension
// don't check the highest dimension
static_for<0, nDim, 1>{}([&](auto IDimReverse) {
constexpr index_t idim = nDim - 1 - IDimReverse.Get();
constexpr index_t idim = nDim - 1 - IDimReverse;
constexpr auto IDim = Number<idim>{};
if(carry)
......@@ -260,7 +257,7 @@ struct ConstantTensorDescriptor
// do borrow check in reversed order, starting from lowest dimension
// don't check the highest dimension
static_for<0, nDim, 1>{}([&](auto IDimReverse) {
constexpr index_t idim = nDim - 1 - IDimReverse.Get();
constexpr index_t idim = nDim - 1 - IDimReverse;
constexpr auto IDim = Number<idim>{};
if(borrow)
......
......@@ -286,7 +286,7 @@ struct Blockwise2dTensorCopy2
__device__ void Run(const Float* __restrict__ p_src, Float* __restrict__ p_dst) const
{
static_assert(is_same<Float, float>::value, "wrong! only support float!\n");
static_assert(is_same<Float, float>{}, "wrong! only support float!\n");
using Float4 = float4;
using Float2 = float2;
......@@ -565,7 +565,7 @@ struct Blockwise2dTensorCopy3
__device__ constexpr index_t GetRegisterClipboardSize() const
{
static_assert(is_same<Float, float>::value, "wrong! only support float!\n");
static_assert(is_same<Float, float>{}, "wrong! only support float!\n");
constexpr auto I0 = Number<0>{};
constexpr auto I1 = Number<1>{};
......@@ -714,7 +714,7 @@ struct Blockwise2dTensorCopy3
*(reinterpret_cast<const vector_t*>(&p_src[mSrcMyThreadOffset +
iloop * src_loop_stride]));
#else
static_assert(is_same<float, Float>::value && DataPerRead == 4,
static_assert(is_same<float, Float>{} && DataPerRead == 4,
"global_load is only for float4");
global_load(reinterpret_cast<vector_t&>(p_clipboard[iloop * DataPerRead]),
......@@ -773,7 +773,7 @@ struct Blockwise2dTensorCopy3
*(reinterpret_cast<vector_t*>(&p_dst[mDstMyThreadOffset + iloop * dst_loop_stride]) =
*(reinterpret_cast<const vector_t*>(&p_clipboard[iloop * DataPerRead]);
#else
static_assert(is_same<float, Float>::value && DataPerRead == 4,
static_assert(is_same<float, Float>{} && DataPerRead == 4,
"ds_write_b128 is only for float4");
ds_write_b128(reinterpret_cast<const vector_t&>(p_clipboard[iloop * DataPerRead]),
......
......@@ -239,7 +239,7 @@ struct Blockwise3dTensorCopy3
__device__ static constexpr index_t GetRegisterClipboardSize()
{
static_assert(is_same<Float, float>::value, "wrong! only support float!\n");
static_assert(is_same<Float, float>{}, "wrong! only support float!\n");
constexpr auto I0 = Number<0>{};
constexpr auto I1 = Number<1>{};
......
......@@ -598,7 +598,7 @@ struct Blockwise4dTensorCopy3
__device__ constexpr index_t GetRegisterClipboardSize() const
{
static_assert(is_same<Float, float>::value, "wrong! only support float!\n");
static_assert(is_same<Float, float>{}, "wrong! only support float!\n");
constexpr auto I0 = Number<0>{};
constexpr auto I1 = Number<1>{};
......
......@@ -295,7 +295,7 @@ struct BlockwiseBatchGemmBlockABlockBThreadCTransANormalBNormalC_V2
#if CK_USE_AMD_INLINE_ASM
template <class FloatA, class FloatB, class FloatC>
__device__ void Run_asm(const FloatA* __restrict__ p_a_block,
__device__ void Run_amd_asm(const FloatA* __restrict__ p_a_block,
const FloatB* __restrict__ p_b_block,
FloatC* __restrict__ p_c_thread) const
{
......@@ -330,19 +330,19 @@ struct BlockwiseBatchGemmBlockABlockBThreadCTransANormalBNormalC_V2
constexpr index_t NPerLevel1Cluster = NPerThreadSubC * NLevel0Cluster * NLevel1Cluster;
// assertion for inline asm
static_assert(is_same<FloatA, float>::value && is_same<FloatB, float>::value &&
is_same<FloatC, float>::value,
"Run_asm only deal with float\n");
static_assert(is_same<FloatA, float>{} && is_same<FloatB, float>{} &&
is_same<FloatC, float>{},
"Run_amd_asm only deal with float\n");
static_assert(MPerThreadSubC == 4 && NPerThreadSubC == 4 && KPerThreadLoop == 1 &&
MPerThread == 8 && NPerThread == 8,
"Run_asm cannot deal with this GEMM shape yet\n");
"Run_amd_asm cannot deal with this GEMM shape yet\n");
static_assert(DataPerReadA == 4 && DataPerReadB == 4, "Run_asm only do float4 read\n");
static_assert(DataPerReadA == 4 && DataPerReadB == 4, "Run_amd_asm only do float4 read\n");
static_assert(
BlockMatrixStrideA == 0 && BatchPerThread == 1,
"Run_asm can only deal with BlockMatrixStrideA == 0 && BatchPerThread == 1 for now\n");
static_assert(BlockMatrixStrideA == 0 && BatchPerThread == 1,
"Run_amd_asm can only deal with BlockMatrixStrideA == 0 && BatchPerThread == "
"1 for now\n");
using Float4 = vector_type<float, 4>::MemoryType;
......@@ -421,19 +421,19 @@ struct BlockwiseBatchGemmBlockABlockBThreadCTransANormalBNormalC_V2
constexpr index_t NPerLevel1Cluster = NPerThreadSubC * NLevel0Cluster * NLevel1Cluster;
// assertion for inline asm
static_assert(is_same<FloatA, float>::value && is_same<FloatB, float>::value &&
is_same<FloatC, float>::value,
"Run_asm only deal with float\n");
static_assert(is_same<FloatA, float>{} && is_same<FloatB, float>{} &&
is_same<FloatC, float>{},
"Run_amd_asm only deal with float\n");
static_assert(MPerThreadSubC == 4 && NPerThreadSubC == 4 && KPerThreadLoop == 1 &&
MPerThread == 8 && NPerThread == 8,
"Run_asm cannot deal with this GEMM shape yet\n");
"Run_amd_asm cannot deal with this GEMM shape yet\n");
static_assert(DataPerReadA == 4 && DataPerReadB == 4, "Run_asm only do float4 read\n");
static_assert(DataPerReadA == 4 && DataPerReadB == 4, "Run_amd_asm only do float4 read\n");
static_assert(
BlockMatrixStrideA == 0 && BatchPerThread == 1,
"Run_asm can only deal with BlockMatrixStrideA == 0 && BatchPerThread == 1 for now\n");
static_assert(BlockMatrixStrideA == 0 && BatchPerThread == 1,
"Run_amd_asm can only deal with BlockMatrixStrideA == 0 && BatchPerThread == "
"1 for now\n");
using Float4 = vector_type<float, 4>::MemoryType;
......
......@@ -5,6 +5,10 @@
#include "ConstantMatrixDescriptor.hpp"
#include "threadwise_gemm.hpp"
#ifndef CK_BLOCKWISE_GEMM_USE_AMD_INLINE_ASM
#define CK_BLOCKWISE_GEMM_USE_AMD_INLINE_ASM 1
#endif
namespace ck {
// if following number are power of 2, index calculation shall be greatly reduced:
......@@ -51,7 +55,8 @@ struct BlockwiseGemmBlockABlockBThreadCTransANormalBNormalC_v2
N % (NPerThreadSubC * NLevel0Cluster * NLevel1Cluster) == 0,
"wrong! Cannot evenly divide work among\n");
static_assert(is_same_type(ThreadMatrixC::GetLengths(), GetThreadMatrixCLengths()),
static_assert(std::is_same<decltype(ThreadMatrixC::GetLengths()),
decltype(GetThreadMatrixCLengths())>{},
"wrong! ThreadMatrixC lengths is wrong");
auto c_thread_mtx_index = GetBeginOfThreadMatrixC(get_thread_local_1d_id());
......@@ -115,9 +120,8 @@ struct BlockwiseGemmBlockABlockBThreadCTransANormalBNormalC_v2
}
#if CK_USE_AMD_INLINE_ASM
// TODO: this is not working correctly
template <class FloatA, class FloatB, class FloatC>
__device__ void Run_asm(const FloatA* __restrict__ p_a_block,
__device__ void Run_amd_asm(const FloatA* __restrict__ p_a_block,
const FloatB* __restrict__ p_b_block,
FloatC* __restrict__ p_c_thread) const
{
......@@ -156,15 +160,15 @@ struct BlockwiseGemmBlockABlockBThreadCTransANormalBNormalC_v2
constexpr index_t NPerLevel1Cluster = NPerThreadSubC * NLevel0Cluster * NLevel1Cluster;
// assertion for inline asm
static_assert(is_same<FloatA, float>::value && is_same<FloatB, float>::value &&
is_same<FloatC, float>::value,
"Run_asm only deal with float\n");
static_assert(is_same<FloatA, float>{} && is_same<FloatB, float>{} &&
is_same<FloatC, float>{},
"Run_amd_asm only deal with float");
static_assert(MPerThreadSubC == 4 && NPerThreadSubC == 4 && KPerThreadLoop == 1 &&
MPerThread == 8 && NPerThread == 8,
"Run_asm cannot deal with this GEMM shape yet\n");
"Run_amd_asm cannot deal with this GEMM shape yet");
static_assert(DataPerReadA == 4 && DataPerReadB == 4, "Run_asm only do float4 read\n");
static_assert(DataPerReadA == 4 && DataPerReadB == 4, "Run_amd_asm only do float4 read");
using Float4 = vector_type<float, 4>::MemoryType;
......@@ -200,7 +204,7 @@ struct BlockwiseGemmBlockABlockBThreadCTransANormalBNormalC_v2
#endif
template <class FloatA, class FloatB, class FloatC>
__device__ void Run(const FloatA* const __restrict__ p_a_block,
__device__ void Run_source(const FloatA* const __restrict__ p_a_block,
const FloatB* const __restrict__ p_b_block,
FloatC* const __restrict__ p_c_thread) const
{
......@@ -291,7 +295,7 @@ struct BlockwiseGemmBlockABlockBThreadCTransANormalBNormalC_v2
}
template <class FloatA, class FloatB, class FloatC>
__device__ void Run_RegisterDoubleBuffer(FloatA* const p_a_block,
__device__ void RunRegisterDoubleBuffer_source(FloatA* const p_a_block,
FloatB* const p_b_block,
FloatC* p_c_thread) const
{
......@@ -427,6 +431,18 @@ struct BlockwiseGemmBlockABlockBThreadCTransANormalBNormalC_v2
p_c_thread);
}
}
template <class FloatA, class FloatB, class FloatC>
__device__ void Run(const FloatA* __restrict__ p_a_block,
const FloatB* __restrict__ p_b_block,
FloatC* __restrict__ p_c_thread) const
{
#if CK_USE_AMD_INLINE_ASM && CK_BLOCKWISE_GEMM_USE_AMD_INLINE_ASM
Run_amd_asm(p_a_block, p_b_block, p_c_thread);
#else
Run_source(p_a_block, p_b_block, p_c_thread);
#endif
}
};
} // namespace ck
......
......@@ -6,6 +6,10 @@
#include "ConstantMergedTensorDescriptor.hpp"
#include "threadwise_generic_tensor_slice_copy.hpp"
#ifndef CK_EXPERIMENTAL_USE_MORE_COMPILE_STATIC_BLOCKWISE_GENERIC_SLICE_COPY_V1
#define CK_EXPERIMENTAL_USE_MORE_COMPILE_STATIC_BLOCKWISE_GENERIC_SLICE_COPY_V1 1
#endif
namespace ck {
// slice a (normal or merged) tensor, and copy it into another (normal or merged) tensor
......@@ -91,7 +95,7 @@ struct BlockwiseGenericTensorSliceCopy_v1
constexpr auto repeat_lengths = SliceLengths{} / data_per_cluster_per_dims;
// for now, only support SubLengths.Get() == 1 on a merged dimension that constains
// for now, only support SubLengths == 1 on a merged dimension that constains
// multiple original dimensions
static_for<0, nDim, 1>{}([&](auto IDim_) {
constexpr auto IDim = decltype(IDim_){};
......@@ -121,7 +125,7 @@ struct BlockwiseGenericTensorSliceCopy_v1
// partial offset on each dimension
static_for<0, nDim, 1>{}([&](auto IDim_) {
constexpr auto IDim = decltype(IDim_){};
constexpr index_t idim = IDim.Get();
constexpr index_t idim = IDim;
constexpr auto src_partial_original_dims =
SrcDesc::GetContainedOriginalDimensions(IDim);
......@@ -135,7 +139,7 @@ struct BlockwiseGenericTensorSliceCopy_v1
static_for<0, nDim, 1>{}([&](auto IDim_) {
constexpr auto IDim = decltype(IDim_){};
constexpr index_t idim = IDim.Get();
constexpr index_t idim = IDim;
constexpr auto dst_partial_original_dims =
DstDesc::GetContainedOriginalDimensions(IDim);
......@@ -153,38 +157,6 @@ struct BlockwiseGenericTensorSliceCopy_v1
mThreadDstOffset = accumulate_on_array(
mThreadDstPartialOffsets, math::plus<index_t>{}, static_cast<index_t>(0));
#if 0
if(get_block_1d_id() == 0)
{
printf("id %5u %5u: "
"src_block_data_multi_id_begin: %u %u %u %u, "
"thread_cluster_multi_id: %u %u %u %u, "
"data_cluster_multi_id: %u %u %u %u, "
"thread_data_multi_id_begin: %u %u %u %u, "
"mThreadSrcOffset %u, mThreadDstOffset %u \n",
get_block_1d_id(),
get_thread_local_1d_id(),
src_block_data_multi_id_begin[0],
src_block_data_multi_id_begin[1],
src_block_data_multi_id_begin[2],
src_block_data_multi_id_begin[3],
thread_cluster_multi_id[0],
thread_cluster_multi_id[1],
thread_cluster_multi_id[2],
thread_cluster_multi_id[3],
data_cluster_multi_id[0],
data_cluster_multi_id[1],
data_cluster_multi_id[2],
data_cluster_multi_id[3],
thread_data_multi_id_begin[0],
thread_data_multi_id_begin[1],
thread_data_multi_id_begin[2],
thread_data_multi_id_begin[3],
mThreadSrcOffset,
mThreadDstOffset);
}
#endif
}
__device__ static constexpr index_t GetRegisterClipboardSize()
......@@ -210,19 +182,7 @@ struct BlockwiseGenericTensorSliceCopy_v1
make_ConstantTensorDescriptor_packed(thread_sub_tensor_lengths * repeat_lengths);
static_ford<decltype(repeat_lengths)>{}([&](auto repeat_multi_id_) {
#if 0
constexpr auto repeat_multi_id = sequence2array(decltype(repeat_multi_id_){});
const auto src_thread_data_multi_id_begin = repeat_multi_id * data_per_cluster_per_dims;
const auto clipboard_data_multi_id_begin = repeat_multi_id * thread_sub_tensor_lengths;
const index_t src_offset =
SrcDesc{}.GetOffsetFromMultiIndex(src_thread_data_multi_id_begin);
const index_t clipboard_offset =
thread_tensor_desc.GetOffsetFromMultiIndex(clipboard_data_multi_id_begin);
#else // HIP compiler performs better with these codes
#if CK_EXPERIMENTAL_USE_MORE_COMPILE_STATIC_BLOCKWISE_GENERIC_SLICE_COPY_V1
constexpr auto repeat_multi_id = decltype(repeat_multi_id_){};
constexpr auto src_thread_data_multi_id_begin =
......@@ -236,6 +196,18 @@ struct BlockwiseGenericTensorSliceCopy_v1
constexpr index_t clipboard_offset =
thread_tensor_desc.GetOffsetFromMultiIndex(clipboard_data_multi_id_begin);
#else
constexpr auto repeat_multi_id = sequence2array(decltype(repeat_multi_id_){});
const auto src_thread_data_multi_id_begin = repeat_multi_id * data_per_cluster_per_dims;
const auto clipboard_data_multi_id_begin = repeat_multi_id * thread_sub_tensor_lengths;
const index_t src_offset =
SrcDesc{}.GetOffsetFromMultiIndex(src_thread_data_multi_id_begin);
const index_t clipboard_offset =
thread_tensor_desc.GetOffsetFromMultiIndex(clipboard_data_multi_id_begin);
#endif
threadwise_generic_tensor_slice_copy_v1(SrcDesc{},
......@@ -263,18 +235,7 @@ struct BlockwiseGenericTensorSliceCopy_v1
make_ConstantTensorDescriptor_packed(thread_sub_tensor_lengths * repeat_lengths);
static_ford<decltype(repeat_lengths)>{}([&](auto repeat_multi_id_) {
#if 0
constexpr auto repeat_multi_id = sequence2array(decltype(repeat_multi_id_){});
const auto clipboard_data_multi_id_begin = repeat_multi_id * thread_sub_tensor_lengths;
const auto dst_data_multi_id_begin = repeat_multi_id * data_per_cluster_per_dims;
const index_t clipboard_offset =
thread_tensor_desc.GetOffsetFromMultiIndex(clipboard_data_multi_id_begin);
const index_t dst_offset = DstDesc{}.GetOffsetFromMultiIndex(dst_data_multi_id_begin);
#else // HIP compiler performs better with these codes
#if CK_EXPERIMENTAL_USE_MORE_COMPILE_STATIC_BLOCKWISE_GENERIC_SLICE_COPY_V1
constexpr auto repeat_multi_id = decltype(repeat_multi_id_){};
constexpr auto clipboard_data_multi_id_begin =
......@@ -287,6 +248,17 @@ struct BlockwiseGenericTensorSliceCopy_v1
constexpr index_t dst_offset =
DstDesc{}.GetOffsetFromMultiIndex(dst_data_multi_id_begin);
#else
constexpr auto repeat_multi_id = sequence2array(decltype(repeat_multi_id_){});
const auto clipboard_data_multi_id_begin = repeat_multi_id * thread_sub_tensor_lengths;
const auto dst_data_multi_id_begin = repeat_multi_id * data_per_cluster_per_dims;
const index_t clipboard_offset =
thread_tensor_desc.GetOffsetFromMultiIndex(clipboard_data_multi_id_begin);
const index_t dst_offset = DstDesc{}.GetOffsetFromMultiIndex(dst_data_multi_id_begin);
#endif
threadwise_generic_tensor_slice_copy_v1(thread_tensor_desc,
......@@ -310,7 +282,7 @@ struct BlockwiseGenericTensorSliceCopy_v1
}
// When moving the slicing windows along a merged dimension, if the strides of the
// contained (by the merged dimension) original dimensions are in descending order,
// contained (by the merged dimension) original dimensions are not in descending order,
// then there is no guarantee that the new offset will be larger than the old offset
// for movement in positive direction (vice versue for movement in negative direction).
// As a result, there is the possiblity that the offset calculation may result in
......@@ -323,7 +295,7 @@ struct BlockwiseGenericTensorSliceCopy_v1
Number<IDim_>, Number<StepSize>, integral_constant<bool, PositiveDirection> direction)
{
constexpr auto IDim = Number<IDim_>{};
constexpr index_t idim = IDim.Get();
constexpr index_t idim = IDim;
static_if<SrcDesc::ContainMultipleOriginalDimensions(IDim)>{}([&](auto fwd) {
// logic for a merged dimension, also works for non-merged dimension, but its logic may
......@@ -350,8 +322,7 @@ struct BlockwiseGenericTensorSliceCopy_v1
constexpr auto I = decltype(I_){};
constexpr index_t idim_original = src_partial_original_dims.Get(I);
mThreadSrcOriginalMultiId(idim_original) =
new_src_partial_original_multi_id[I.Get()];
mThreadSrcOriginalMultiId(idim_original) = new_src_partial_original_multi_id[I];
});
// calculate new partial offset on this merged dimension
......
......@@ -49,7 +49,7 @@ struct BlockwiseTensorSliceReorderCopy_v3
make_ConstantTensorDescriptor_packed(thread_cluster_lengths);
// sanity check: data type
static_assert(is_same<Float, float>::value, "wrong! only support float for now!\n");
static_assert(is_same<Float, float>{}, "wrong! only support float for now!\n");
// sanity check: nDim
static_assert(SrcDesc::GetNumOfDimension() == nDim &&
......@@ -121,12 +121,11 @@ struct BlockwiseTensorSliceReorderCopy_v3
reorder_array_given_old2new(thread_multi_id, map_thread_cluster_2_src_cluster);
static_for<0, nDim, 1>{}([&](auto IDim) {
constexpr auto I = decltype(IDim){};
constexpr index_t i = I.Get();
constexpr index_t idim = IDim;
// compiler: will it really compute index here, or be merged with
// GetOffsetFromMultiIndex and
// optimized away???
src_data_multi_id(i) *= src_sub_lengths.Get(I);
src_data_multi_id(idim) *= src_sub_lengths.Get(IDim);
});
// compiler: will it really compute index here, or be merged with GetOffsetFromMultiIndex
......
......@@ -26,16 +26,16 @@ __device__ void threadwise_4d_tensor_shift_down(Desc, Float* __restrict__ p, IDi
constexpr index_t nshift = NShift::mValue;
constexpr index_t did0_end =
is_same<decltype(I0), IDim>::value ? desc.GetLength(I0) - nshift : desc.GetLength(I0);
is_same<decltype(I0), IDim>{} ? desc.GetLength(I0) - nshift : desc.GetLength(I0);
constexpr index_t did1_end =
is_same<decltype(I1), IDim>::value ? desc.GetLength(I1) - nshift : desc.GetLength(I1);
is_same<decltype(I1), IDim>{} ? desc.GetLength(I1) - nshift : desc.GetLength(I1);
constexpr index_t did2_end =
is_same<decltype(I2), IDim>::value ? desc.GetLength(I2) - nshift : desc.GetLength(I2);
is_same<decltype(I2), IDim>{} ? desc.GetLength(I2) - nshift : desc.GetLength(I2);
constexpr index_t did3_end =
is_same<decltype(I3), IDim>::value ? desc.GetLength(I3) - nshift : desc.GetLength(I3);
is_same<decltype(I3), IDim>{} ? desc.GetLength(I3) - nshift : desc.GetLength(I3);
for(index_t did0 = 0; did0 < did0_end; ++did0)
{
......
Markdown is supported
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment