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Commit 18d5297b authored by aska-0096's avatar aska-0096
Browse files

Todo: fix gemm_bilinear_wmma instances compilation bug

parent 4fe49693
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Showing with 220 additions and 468 deletions
example/32_batched_gemm_scale_softmax_gemm/CMakeLists.txt
View file @ 18d5297b
add_example_executable(example_batched_gemm_scale_softmax_gemm_xdl_fp16 batched_gemm_scale_softmax_gemm_xdl_fp16.cpp)
add_example_executable(example_batched_gemm_scale_softmax_gemm_xdl_bf16 batched_gemm_scale_softmax_gemm_xdl_bf16.cpp)
add_example_executable(example_batched_gemm_scale_softmax_gemm_permute_xdl_fp16 batched_gemm_scale_softmax_gemm_permute_xdl_fp16.cpp)
add_example_executable(example_batched_gemm_scale_softmax_gemm_permute_xdl_bf16 batched_gemm_scale_softmax_gemm_permute_xdl_bf16.cpp)
add_example_executable(example_grouped_gemm_scale_softmax_gemm_permute_xdl_fp16 grouped_gemm_scale_softmax_gemm_permute_xdl_fp16.cpp)
add_example_executable(example_batched_gemm_lower_triangle_scale_softmax_gemm_permute_xdl_fp16 batched_gemm_lower_triangle_scale_softmax_gemm_permute_xdl_fp16.cpp)
add_example_executable(example_grouped_gemm_lower_triangle_scale_softmax_gemm_permute_xdl_fp16 grouped_gemm_lower_triangle_scale_softmax_gemm_permute_xdl_fp16.cpp)
if(GPU_TARGETS MATCHES "gfx1100" OR GPU_TARGETS MATCHES "gfx1101" OR GPU_TARGETS MATCHES "gfx1102") if(GPU_TARGETS MATCHES "gfx1100" OR GPU_TARGETS MATCHES "gfx1101" OR GPU_TARGETS MATCHES "gfx1102")
add_example_executable(example_batched_gemm_lower_triangle_scale_softmax_gemm_permute_wmma_fp16 batched_gemm_lower_triangle_scale_softmax_gemm_permute_wmma_fp16.cpp) add_example_executable(example_batched_gemm_lower_triangle_scale_softmax_gemm_permute_wmma_fp16 batched_gemm_lower_triangle_scale_softmax_gemm_permute_wmma_fp16.cpp)
add_example_executable(example_batched_gemm_scale_softmax_gemm_permute_wmma_fp16 batched_gemm_scale_softmax_gemm_permute_wmma_fp16.cpp) add_example_executable(example_batched_gemm_scale_softmax_gemm_permute_wmma_fp16 batched_gemm_scale_softmax_gemm_permute_wmma_fp16.cpp)
......
example/49_fpAintB_gemm/run_gemm_example.inc → example/64_fpAintB_gemm/run_gemm_example.inc
View file @ 18d5297b
...@@ -34,30 +34,15 @@ bool run_gemm(const ProblemSize& problem_size, const ExecutionConfig& config) ...@@ -34,30 +34,15 @@ bool run_gemm(const ProblemSize& problem_size, const ExecutionConfig& config)
{ {
case 0: break; case 0: break;
case 1: case 1:
ck::utils::FillUniformDistributionIntegerValue<ADataType>{-5.f, 5.f}(a_m_k); ck::utils::FillUniformDistributionIntegerValue<ADataType>{-1.f, 1.f}(a_m_k);
ck::utils::FillUniformDistributionIntegerValue<QuantDataType>{-5.f, 5.f}(quant_b_k_n); ck::utils::FillUniformDistributionIntegerValue<QuantDataType>{-1.f, 1.f}(quant_b_k_n);
ck::utils::FillUniformDistributionIntegerValue<ScaleDataType>{-5.f, 5.f}(scale_k_n); ck::utils::FillUniformDistributionIntegerValue<ScaleDataType>{-1.f, 1.f}(scale_k_n);
break; break;
case 2: case 2:
ck::utils::FillUniformDistribution<ADataType>{-1.f, 1.f}(a_m_k); ck::utils::FillUniformDistribution<ADataType>{-1.f, 1.f}(a_m_k);
ck::utils::FillUniformDistribution<QuantDataType>{-1.f, 1.f}(quant_b_k_n); ck::utils::FillUniformDistribution<QuantDataType>{-1.f, 1.f}(quant_b_k_n);
ck::utils::FillUniformDistribution<ScaleDataType>{-1.f, 1.f}(scale_k_n); ck::utils::FillUniformDistribution<ScaleDataType>{-1.f, 1.f}(scale_k_n);
break; break;
case 3:
ck::utils::FillUniformDistributionIntegerValue<ADataType>{1.f, 1.f}(a_m_k);
ck::utils::FillUniformDistributionIntegerValue<QuantDataType>{-5.f, 5.f}(quant_b_k_n);
ck::utils::FillUniformDistributionIntegerValue<ScaleDataType>{-5.f, 5.f}(scale_k_n);
break;
case 4:
ck::utils::FillUniformDistributionIntegerValue<ADataType>{1.f, 1.f}(a_m_k);
ck::utils::FillUniformDistributionIntegerValue<QuantDataType>{1.f, 1.f}(quant_b_k_n);
ck::utils::FillUniformDistributionIntegerValue<ScaleDataType>{2.f, 2.f}(scale_k_n);
break;
case 5:
ck::utils::FillUniformDistributionIntegerValue<ADataType>{-2.f, 2.f}(a_m_k);
ck::utils::FillUniformDistributionIntegerValue<QuantDataType>{-2.f, 2.f}(quant_b_k_n);
ck::utils::FillUniformDistributionIntegerValue<ScaleDataType>{-2.f, 2.f}(scale_k_n);
break;
default: default:
ck::utils::FillUniformDistribution<ADataType>{-1.f, 1.f}(a_m_k); ck::utils::FillUniformDistribution<ADataType>{-1.f, 1.f}(a_m_k);
ck::utils::FillUniformDistribution<QuantDataType>{-1.f, 1.f}(quant_b_k_n); ck::utils::FillUniformDistribution<QuantDataType>{-1.f, 1.f}(quant_b_k_n);
......
include/ck/tensor_operation/gpu/device/impl/device_grouped_conv_bwd_data_multiple_d_wmma_cshuffle.hpp
View file @ 18d5297b
...@@ -217,7 +217,7 @@ struct DeviceGroupedConvBwdDataMultipleD_Wmma_CShuffle ...@@ -217,7 +217,7 @@ struct DeviceGroupedConvBwdDataMultipleD_Wmma_CShuffle
// Tiling Family // Tiling Family
MPerBlock, MPerBlock,
NPerBlock, NPerBlock,
K0PerBlock, KPerBlock,
MPerWMMA, MPerWMMA,
NPerWMMA, NPerWMMA,
K1, K1,
...@@ -231,8 +231,8 @@ struct DeviceGroupedConvBwdDataMultipleD_Wmma_CShuffle ...@@ -231,8 +231,8 @@ struct DeviceGroupedConvBwdDataMultipleD_Wmma_CShuffle
ABlockTransferSrcVectorDim, ABlockTransferSrcVectorDim,
ABlockTransferSrcScalarPerVector, ABlockTransferSrcScalarPerVector,
ABlockTransferDstScalarPerVector_AK1, ABlockTransferDstScalarPerVector_AK1,
true,
false, false,
true,
ABlockLdsExtraM, ABlockLdsExtraM,
BBlockTransferThreadClusterLengths_BK0_N_BK1, BBlockTransferThreadClusterLengths_BK0_N_BK1,
BBlockTransferThreadClusterArrangeOrder, BBlockTransferThreadClusterArrangeOrder,
...@@ -240,8 +240,8 @@ struct DeviceGroupedConvBwdDataMultipleD_Wmma_CShuffle ...@@ -240,8 +240,8 @@ struct DeviceGroupedConvBwdDataMultipleD_Wmma_CShuffle
BBlockTransferSrcVectorDim, BBlockTransferSrcVectorDim,
BBlockTransferSrcScalarPerVector, BBlockTransferSrcScalarPerVector,
BBlockTransferDstScalarPerVector_BK1, BBlockTransferDstScalarPerVector_BK1,
true,
false, false,
true,
BBlockLdsExtraN, BBlockLdsExtraN,
CShuffleMRepeatPerShuffle, CShuffleMRepeatPerShuffle,
CShuffleNRepeatPerShuffle, CShuffleNRepeatPerShuffle,
......
include/ck/tensor_operation/gpu/device/impl/device_grouped_conv_bwd_weight_wmma_cshuffle.hpp
View file @ 18d5297b
...@@ -416,7 +416,7 @@ struct DeviceGroupedConvBwdWeight_Wmma_CShuffle ...@@ -416,7 +416,7 @@ struct DeviceGroupedConvBwdWeight_Wmma_CShuffle
// Tiling Family // Tiling Family
MPerBlock, MPerBlock,
NPerBlock, NPerBlock,
K0PerBlock, KPerBlock,
MPerWMMA, MPerWMMA,
NPerWMMA, NPerWMMA,
K1, K1,
...@@ -430,8 +430,8 @@ struct DeviceGroupedConvBwdWeight_Wmma_CShuffle ...@@ -430,8 +430,8 @@ struct DeviceGroupedConvBwdWeight_Wmma_CShuffle
ABlockTransferSrcVectorDim, ABlockTransferSrcVectorDim,
ABlockTransferSrcScalarPerVector, ABlockTransferSrcScalarPerVector,
ABlockTransferDstScalarPerVector_K1, ABlockTransferDstScalarPerVector_K1,
true,
false, false,
true,
ABlockLdsAddExtraM, ABlockLdsAddExtraM,
BBlockTransferThreadClusterLengths_K0_N_K1, BBlockTransferThreadClusterLengths_K0_N_K1,
BBlockTransferThreadClusterArrangeOrder, BBlockTransferThreadClusterArrangeOrder,
...@@ -439,8 +439,8 @@ struct DeviceGroupedConvBwdWeight_Wmma_CShuffle ...@@ -439,8 +439,8 @@ struct DeviceGroupedConvBwdWeight_Wmma_CShuffle
BBlockTransferSrcVectorDim, BBlockTransferSrcVectorDim,
BBlockTransferSrcScalarPerVector, BBlockTransferSrcScalarPerVector,
BBlockTransferDstScalarPerVector_K1, BBlockTransferDstScalarPerVector_K1,
true,
false, false,
true,
BBlockLdsAddExtraN, BBlockLdsAddExtraN,
CShuffleMRepeatPerShuffle, CShuffleMRepeatPerShuffle,
CShuffleNRepeatPerShuffle, CShuffleNRepeatPerShuffle,
......
include/ck/tensor_operation/gpu/device/impl/device_grouped_conv_fwd_multiple_d_wmma_cshuffle.hpp
View file @ 18d5297b
...@@ -279,15 +279,11 @@ struct DeviceGroupedConvFwdMultipleD_Wmma_CShuffle ...@@ -279,15 +279,11 @@ struct DeviceGroupedConvFwdMultipleD_Wmma_CShuffle
} }
// desc for problem definition // desc for problem definition
using AGridDesc_M_K = remove_cvref_t<decltype(MakeAGridDescriptor_M_K<ALayout>(
{}, {}, {}, {}, {}, {}, {}, {}, {}, {}))>;
using BGridDesc_N_K = remove_cvref_t<decltype(MakeBGridDescriptor_N_K<BLayout>({}, {}))>;
using DsGridDesc_M_N = remove_cvref_t<decltype(MakeDsGridDescriptor_M_N({}, {}))>;
using EGridDesc_M_N = remove_cvref_t<decltype(MakeEGridDescriptor_M_N<ELayout>({}, {}))>;
using AGridDesc = using AGridDesc =
decltype(DeviceOp::MakeAGridDescriptor<ALayout>({}, {}, {}, {}, {}, {}, {}, {}, {}, {})); decltype(DeviceOp::MakeAGridDescriptor<ALayout>({}, {}, {}, {}, {}, {}, {}, {}, {}, {}));
using BGridDesc = decltype(DeviceOp::MakeBGridDescriptor<BLayout>({}, {})); using BGridDesc = decltype(DeviceOp::MakeBGridDescriptor<BLayout>({}, {}));
using DsGridDesc_M_N = remove_cvref_t<decltype(MakeDsGridDescriptor_M_N({}, {}))>;
using EGridDesc_M_N = remove_cvref_t<decltype(MakeEGridDescriptor_M_N<ELayout>({}, {}))>;
// GridwiseOp // GridwiseOp
using GridwiseOp = GridwiseGemmMultipleD_Wmma< using GridwiseOp = GridwiseGemmMultipleD_Wmma<
......
include/ck/tensor_operation/gpu/element/unary_element_wise_operation.hpp
View file @ 18d5297b
...@@ -121,6 +121,9 @@ struct PassThrough ...@@ -121,6 +121,9 @@ struct PassThrough
__host__ __device__ void operator()<bhalf_t, int8_t>(bhalf_t& y, const int8_t& x) const __host__ __device__ void operator()<bhalf_t, int8_t>(bhalf_t& y, const int8_t& x) const
{ {
y = type_convert<bhalf_t>(x); y = type_convert<bhalf_t>(x);
}
template <>
__host__ __device__ void operator()<uint8_t, uint8_t>(uint8_t& y, const uint8_t& x) const __host__ __device__ void operator()<uint8_t, uint8_t>(uint8_t& y, const uint8_t& x) const
{ {
y = x; y = x;
...@@ -738,5 +741,4 @@ struct FastNumericArrayConverter<uint8_t, ck::half_t, N> ...@@ -738,5 +741,4 @@ struct FastNumericArrayConverter<uint8_t, ck::half_t, N>
} // namespace element_wise } // namespace element_wise
} // namespace tensor_operation } // namespace tensor_operation
} } // namespace ck
}// namespace ck
include/ck/tensor_operation/gpu/grid/gridwise_batched_gemm_softmax_gemm_wmma_cshuffle.hpp
View file @ 18d5297b
...@@ -651,8 +651,9 @@ struct GridwiseBatchedGemmSoftmaxGemm_Wmma ...@@ -651,8 +651,9 @@ struct GridwiseBatchedGemmSoftmaxGemm_Wmma
c_grid_desc_m_n); c_grid_desc_m_n);
} }
using CGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock = remove_cvref_t<decltype( using CGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock =
MakeCGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock(CGridDesc_M_N{}))>; remove_cvref_t<decltype(MakeCGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock(
CGridDesc_M_N{}))>;
using DefaultBlock2CTileMap = using DefaultBlock2CTileMap =
remove_cvref_t<decltype(MakeDefaultBlock2CTileMap(CGridDesc_M_N{}, 1, 1))>; remove_cvref_t<decltype(MakeDefaultBlock2CTileMap(CGridDesc_M_N{}, 1, 1))>;
......
include/ck/tensor_operation/gpu/grid/gridwise_fpAintB_gemm_wmma.hpp
View file @ 18d5297b
...@@ -535,8 +535,9 @@ struct GridwiseFpAintBGemm_Wmma ...@@ -535,8 +535,9 @@ struct GridwiseFpAintBGemm_Wmma
c_grid_desc_m_n); c_grid_desc_m_n);
} }
using CGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock = remove_cvref_t<decltype( using CGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock =
MakeCGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock(CGridDesc_M_N{}))>; remove_cvref_t<decltype(MakeCGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock(
CGridDesc_M_N{}))>;
using DefaultBlock2CTileMap = using DefaultBlock2CTileMap =
remove_cvref_t<decltype(MakeDefaultBlock2CTileMap(CGridDesc_M_N{}, 1, 1))>; remove_cvref_t<decltype(MakeDefaultBlock2CTileMap(CGridDesc_M_N{}, 1, 1))>;
......
include/ck/tensor_operation/gpu/grid/gridwise_gemm_multiple_d_wmma_cshuffle.hpp
View file @ 18d5297b
...@@ -596,6 +596,93 @@ struct GridwiseGemmMultipleD_Wmma ...@@ -596,6 +596,93 @@ struct GridwiseGemmMultipleD_Wmma
Number<NumDTensor>{}); Number<NumDTensor>{});
} }
// CheckValidity for kernels without multi D
template <typename Block2CTileMap>
__host__ __device__ static constexpr bool CheckValidity(const AGridDesc& a_grid_desc,
const BGridDesc& b_grid_desc,
const EGridDesc_M_N& e_grid_desc_m_n,
const Block2CTileMap& block_2_ctile_map)
{
static_assert(is_known_at_compile_time<remove_cv_t<decltype(K1)>>::value,
"wrong! K1 need to be known at compile-time");
static_assert((MPerBlock % (MPerWmma * MRepeat) == 0) &&
(NPerBlock % (NRepeat * NPerWmma)) == 0,
"Invalid tuning param!");
const auto GetAProblemsizeMK = [&]() {
if constexpr(AEnableLds)
{
return make_tuple(a_grid_desc.GetLength(I1),
a_grid_desc.GetLength(I0) * a_grid_desc.GetLength(I2));
}
else
{
return make_tuple(a_grid_desc.GetLength(I1) * a_grid_desc.GetLength(I2) *
a_grid_desc.GetLength(I5),
a_grid_desc.GetLength(I0) * a_grid_desc.GetLength(I3) *
a_grid_desc.GetLength(I4) * a_grid_desc.GetLength(I6));
}
};
const auto GetBProblemsizeNK = [&]() {
if constexpr(BEnableLds)
{
return make_tuple(b_grid_desc.GetLength(I1),
b_grid_desc.GetLength(I0) * b_grid_desc.GetLength(I2));
}
else
{
return make_tuple(b_grid_desc.GetLength(I1) * b_grid_desc.GetLength(I2) *
b_grid_desc.GetLength(I5),
b_grid_desc.GetLength(I0) * b_grid_desc.GetLength(I3) *
b_grid_desc.GetLength(I4) * b_grid_desc.GetLength(I6));
}
};
const auto M = GetAProblemsizeMK()[I0];
const auto N = GetBProblemsizeNK()[I0];
const auto K = GetAProblemsizeMK()[I1];
if(!(M == e_grid_desc_m_n.GetLength(I0) && N == e_grid_desc_m_n.GetLength(I1) &&
K == GetBProblemsizeNK()[I1]))
{
printf("GridwiseOp: ABE descriptor dimension cross check failure\n");
return false;
}
if(!(M % MPerBlock == 0 && N % NPerBlock == 0 && K % KPerBlock == 0))
{
printf("GridwiseOp: Problemsize descriptor dimension check failure\n");
return false;
}
// check gridwise gemm pipeline
const auto num_k_loop = K / KPerBlock;
if(!GridwiseGemmPipe::IsSupported(num_k_loop))
{
return false;
}
if(!block_2_ctile_map.CheckValidity(e_grid_desc_m_n))
{
return false;
}
// TODO: also check validity of all components (blockwise-copy, threadwise-copy, etc)
constexpr long_index_t TwoGB = (long_index_t{1} << 31);
if(!(a_grid_desc.GetElementSpaceSize() * sizeof(ADataType) <= TwoGB &&
b_grid_desc.GetElementSpaceSize() * sizeof(BDataType) <= TwoGB &&
e_grid_desc_m_n.GetElementSpaceSize() * sizeof(EDataType) <= TwoGB))
{
return false;
}
return true;
}
// block_id to matrix tile idx (m0, n0) mapping are controlled by {M01, N01} // block_id to matrix tile idx (m0, n0) mapping are controlled by {M01, N01}
template <typename Block2CTileMap> template <typename Block2CTileMap>
__host__ __device__ static constexpr bool CheckValidity(const AGridDesc& a_grid_desc, __host__ __device__ static constexpr bool CheckValidity(const AGridDesc& a_grid_desc,
......
include/ck/tensor_operation/gpu/grid/gridwise_gemm_pipeline_selector.hpp
View file @ 18d5297b
...@@ -45,6 +45,7 @@ constexpr auto GridwiseGemmPipeline_Selector() ...@@ -45,6 +45,7 @@ constexpr auto GridwiseGemmPipeline_Selector()
else if constexpr(PipelineVer == PipelineVersion::v4) else if constexpr(PipelineVer == PipelineVersion::v4)
{ {
return GridwiseGemmPipeline_v4<NumPrefetch>{}; return GridwiseGemmPipeline_v4<NumPrefetch>{};
}
else if constexpr(PipelineVer == PipelineVersion::weight_only) else if constexpr(PipelineVer == PipelineVersion::weight_only)
{ {
return GridwiseGemmPipeline_v1_WeightOnly<NumPrefetch, AEnableLds, BEnableLds>{}; return GridwiseGemmPipeline_v1_WeightOnly<NumPrefetch, AEnableLds, BEnableLds>{};
......
include/ck/utility/amd_buffer_addressing.hpp
View file @ 18d5297b
...@@ -417,7 +417,8 @@ __device__ typename vector_type<T, N>::type amd_buffer_load_impl(int32x4_t src_w ...@@ -417,7 +417,8 @@ __device__ typename vector_type<T, N>::type amd_buffer_load_impl(int32x4_t src_w
(is_same<T, int32_t>::value && (N == 1 || N == 2 || N == 4 || N == 8 || N == 16)) || (is_same<T, int32_t>::value && (N == 1 || N == 2 || N == 4 || N == 8 || N == 16)) ||
(is_same<T, f8_t>::value && (N == 1 || N == 2 || N == 4 || N == 8 || N == 16)) || (is_same<T, f8_t>::value && (N == 1 || N == 2 || N == 4 || N == 8 || N == 16)) ||
(is_same<T, bf8_t>::value && (N == 1 || N == 2 || N == 4 || N == 8 || N == 16)) || (is_same<T, bf8_t>::value && (N == 1 || N == 2 || N == 4 || N == 8 || N == 16)) ||
(is_same<T, int8_t>::value && (N == 1 || N == 2 || N == 4 || N == 8 || N == 16)), (is_same<T, int8_t>::value && (N == 1 || N == 2 || N == 4 || N == 8 || N == 16)) ||
(is_same<T, uint8_t>::value && (N == 1 || N == 2 || N == 4 || N == 8 || N == 16)),
"wrong! not implemented"); "wrong! not implemented");
using r_t = typename vector_type<T, N>::type; using r_t = typename vector_type<T, N>::type;
...@@ -521,114 +522,6 @@ amd_buffer_store_impl_raw(const typename vector_type<int8_t, N>::type src_thread ...@@ -521,114 +522,6 @@ amd_buffer_store_impl_raw(const typename vector_type<int8_t, N>::type src_thread
dst_wave_addr_offset + sizeof(int32_t) * 12, dst_wave_addr_offset + sizeof(int32_t) * 12,
static_cast<index_t>(coherence)); static_cast<index_t>(coherence));
} }
else if constexpr(is_same<T, uint8_t>::value)
{
if constexpr(N == 1)
{
return llvm_amdgcn_raw_buffer_load_i8(src_wave_buffer_resource,
src_thread_addr_offset,
src_wave_addr_offset,
static_cast<index_t>(coherence));
}
else if constexpr(N == 2)
{
#if !CK_WORKAROUND_SWDEV_XXXXXX_INT8_BUFFER_LOAD_STORE_ISSUE
return llvm_amdgcn_raw_buffer_load_i8x2(src_wave_buffer_resource,
src_thread_addr_offset,
src_wave_addr_offset,
static_cast<index_t>(coherence));
#else
int16_t tmp = llvm_amdgcn_raw_buffer_load_i16(src_wave_buffer_resource,
src_thread_addr_offset,
src_wave_addr_offset,
static_cast<index_t>(coherence));
return bit_cast<uint8x2_t>(tmp);
#endif
}
else if constexpr(N == 4)
{
#if !CK_WORKAROUND_SWDEV_XXXXXX_INT8_BUFFER_LOAD_STORE_ISSUE
return llvm_amdgcn_raw_buffer_load_i8x4(src_wave_buffer_resource,
src_thread_addr_offset,
src_wave_addr_offset,
static_cast<index_t>(coherence));
#else
int32_t tmp = llvm_amdgcn_raw_buffer_load_i32(src_wave_buffer_resource,
src_thread_addr_offset,
src_wave_addr_offset,
static_cast<index_t>(coherence));
return bit_cast<uint8x4_t>(tmp);
#endif
}
else if constexpr(N == 8)
{
#if !CK_WORKAROUND_SWDEV_XXXXXX_INT8_BUFFER_LOAD_STORE_ISSUE
vector_type<uint8_t, 8> tmp;
tmp.AsType<uint8x4_t>()(Number<0>{}) =
llvm_amdgcn_raw_buffer_load_i8x4(src_wave_buffer_resource,
src_thread_addr_offset,
src_wave_addr_offset,
static_cast<index_t>(coherence));
tmp.AsType<uint8x4_t>()(Number<1>{}) =
llvm_amdgcn_raw_buffer_load_i8x4(src_wave_buffer_resource,
src_thread_addr_offset,
src_wave_addr_offset + 4 * sizeof(int8_t),
static_cast<index_t>(coherence));
return tmp.AsType<uint8x8_t>()(Number<0>{});
#else
int32x2_t tmp = llvm_amdgcn_raw_buffer_load_i32x2(src_wave_buffer_resource,
src_thread_addr_offset,
src_wave_addr_offset,
static_cast<index_t>(coherence));
return bit_cast<uint8x8_t>(tmp);
#endif
}
else if constexpr(N == 16)
{
#if !CK_WORKAROUND_SWDEV_XXXXXX_INT8_BUFFER_LOAD_STORE_ISSUE
vector_type<uint8_t, 16> tmp;
tmp.AsType<uint8x4_t>()(Number<0>{}) =
llvm_amdgcn_raw_buffer_load_i8x4(src_wave_buffer_resource,
src_thread_addr_offset,
src_wave_addr_offset,
static_cast<index_t>(coherence));
tmp.AsType<uint8x4_t>()(Number<1>{}) =
llvm_amdgcn_raw_buffer_load_i8x4(src_wave_buffer_resource,
src_thread_addr_offset,
src_wave_addr_offset + 4 * sizeof(int8_t),
static_cast<index_t>(coherence));
tmp.AsType<uint8x4_t>()(Number<2>{}) =
llvm_amdgcn_raw_buffer_load_i8x4(src_wave_buffer_resource,
src_thread_addr_offset,
src_wave_addr_offset + 8 * sizeof(int8_t),
static_cast<index_t>(coherence));
tmp.AsType<uint8x4_t>()(Number<3>{}) =
llvm_amdgcn_raw_buffer_load_i8x4(src_wave_buffer_resource,
src_thread_addr_offset,
src_wave_addr_offset + 12 * sizeof(int8_t),
static_cast<index_t>(coherence));
return tmp.AsType<uint8x16_t>()(Number<0>{});
#else
int32x4_t tmp = llvm_amdgcn_raw_buffer_load_i32x4(src_wave_buffer_resource,
src_thread_addr_offset,
src_wave_addr_offset,
static_cast<index_t>(coherence));
return bit_cast<uint8x16_t>(tmp);
#endif
}
}
} }
template <typename T, template <typename T,
......
include/ck/utility/data_type.hpp
View file @ 18d5297b
...@@ -1053,219 +1053,6 @@ using uint8x16_t = typename vector_type<uint8_t, 16>::type; ...@@ -1053,219 +1053,6 @@ using uint8x16_t = typename vector_type<uint8_t, 16>::type;
using uint8x32_t = typename vector_type<uint8_t, 32>::type; using uint8x32_t = typename vector_type<uint8_t, 32>::type;
using uint8x64_t = typename vector_type<uint8_t, 64>::type; using uint8x64_t = typename vector_type<uint8_t, 64>::type;
// Convert X to Y
template <typename Y, typename X>
__host__ __device__ constexpr Y type_convert(X x)
{
static_assert(!std::is_reference_v<Y> && !std::is_reference_v<X>);
return static_cast<Y>(x);
}
// convert bfp16 to fp32
template <>
inline __host__ __device__ constexpr float type_convert<float, bhalf_t>(bhalf_t x)
{
union
{
uint32_t int32;
float fp32;
} u = {uint32_t(x) << 16};
return u.fp32;
}
// Convert X to Y
template <typename Y, typename X>
__host__ __device__ constexpr Y type_convert_sp(X x)
{
static_assert(!std::is_reference_v<Y> && !std::is_reference_v<X>);
return static_cast<Y>(x);
}
template <>
inline __host__ __device__ constexpr int type_convert_sp<int, float>(float x)
{
union
{
float fp32;
int int32;
} u = {x};
return u.int32;
}
template <>
inline __host__ __device__ constexpr float type_convert_sp<float, int>(int x)
{
union
{
int int32;
float fp32;
} u = {x};
return u.fp32;
}
template <>
inline __host__ __device__ constexpr int type_convert_sp<int, half_t>(half_t x)
{
union
{
half_t fp16;
int int32;
} u = {x};
return u.int32;
}
template <>
inline __host__ __device__ constexpr half_t type_convert_sp<half_t, int>(int x)
{
union
{
int int32;
half_t fp16;
} u = {x};
return u.fp16;
}
// convert fp32 to bfp16
template <>
inline __host__ __device__ constexpr bhalf_t type_convert<bhalf_t, float>(float x)
{
union
{
float fp32;
uint32_t int32;
} u = {x};
return uint16_t(u.int32 >> 16);
}
// convert bfp16 to fp16 via fp32
template <>
inline __host__ __device__ constexpr half_t type_convert<half_t, bhalf_t>(bhalf_t x)
{
float x_fp32 = type_convert<float>(x);
return static_cast<half_t>(x_fp32);
}
// convert fp16 to bfp16 via fp32
template <>
inline __host__ __device__ constexpr bhalf_t type_convert<bhalf_t, half_t>(half_t x)
{
float x_fp32 = static_cast<float>(x);
return type_convert<bhalf_t>(x_fp32);
}
// convert bfp16 to int32 via fp32
template <>
inline __host__ __device__ constexpr int32_t type_convert<int32_t, bhalf_t>(bhalf_t x)
{
float x_fp32 = type_convert<float>(x);
return static_cast<int32_t>(x_fp32);
}
// convert int32 to bfp16 via fp32
template <>
inline __host__ __device__ constexpr bhalf_t type_convert<bhalf_t, int32_t>(int32_t x)
{
float x_fp32 = static_cast<float>(x);
return type_convert<bhalf_t>(x_fp32);
}
// convert bfp16 to int8 via fp32
template <>
inline __host__ __device__ constexpr int8_t type_convert<int8_t, bhalf_t>(bhalf_t x)
{
float x_fp32 = type_convert<float>(x);
return static_cast<int8_t>(x_fp32);
}
// convert int8 to bfp16 via fp32
template <>
inline __host__ __device__ constexpr bhalf_t type_convert<bhalf_t, int8_t>(int8_t x)
{
float x_fp32 = static_cast<float>(x);
return type_convert<bhalf_t>(x_fp32);
}
// convert int8 to fp16 via fp32
template <>
inline __host__ __device__ constexpr half_t type_convert<half_t, int8_t>(int8_t x)
{
// TODO: replace it with fast_converter
float x_fp32 = static_cast<float>(x);
return type_convert<half_t>(x_fp32);
}
// Declare a template function for bf16 conversion using RTN
template <typename Y, typename X>
__host__ __device__ constexpr Y bf16_convert_rtn(X x);
// Convert fp32 to bf16 with RTN if higher precision is needed
template <>
inline __host__ __device__ constexpr bhalf_t bf16_convert_rtn<bhalf_t, float>(float x)
{
union
{
float fp32;
uint32_t int32;
} u = {x};
// When the exponent bits are not all 1s, then the value is zero, normal,
// or subnormal. We round the bfloat16 mantissa up by adding 0x7FFF, plus
// 1 if the least significant bit of the bfloat16 mantissa is 1 (odd).
// This causes the bfloat16's mantissa to be incremented by 1 if the 16
// least significant bits of the float mantissa are greater than 0x8000,
// or if they are equal to 0x8000 and the least significant bit of the
// bfloat16 mantissa is 1 (odd). This causes it to be rounded to even when
// the lower 16 bits are exactly 0x8000. If the bfloat16 mantissa already
// has the value 0x7f, then incrementing it causes it to become 0x00 and
// the exponent is incremented by one, which is the next higher FP value
// to the unrounded bfloat16 value. When the bfloat16 value is subnormal
// with an exponent of 0x00 and a mantissa of 0x7f, it may be rounded up
// to a normal value with an exponent of 0x01 and a mantissa of 0x00.
// When the bfloat16 value has an exponent of 0xFE and a mantissa of 0x7F,
// incrementing it causes it to become an exponent of 0xFF and a mantissa
// of 0x00, which is Inf, the next higher value to the unrounded value.
bool flag0 = ~u.int32 & 0x7f800000;
// When all of the exponent bits are 1, the value is Inf or NaN.
// Inf is indicated by a zero mantissa. NaN is indicated by any nonzero
// mantissa bit. Quiet NaN is indicated by the most significant mantissa
// bit being 1. Signaling NaN is indicated by the most significant
// mantissa bit being 0 but some other bit(s) being 1. If any of the
// lower 16 bits of the mantissa are 1, we set the least significant bit
// of the bfloat16 mantissa, in order to preserve signaling NaN in case
// the bfloat16's mantissa bits are all 0.
bool flag1 = !flag0 && (u.int32 & 0xffff);
u.int32 += flag0 ? 0x7fff + ((u.int32 >> 16) & 1) : 0; // Round to nearest, round to even
u.int32 |= flag1 ? 0x10000 : 0x0; // Preserve signaling NaN
return uint16_t(u.int32 >> 16);
}
// convert fp16 to bfp16 via fp32 with RTN if higher precision is needed
template <>
inline __host__ __device__ constexpr bhalf_t bf16_convert_rtn<bhalf_t, half_t>(half_t x)
{
float x_fp32 = static_cast<float>(x);
return bf16_convert_rtn<bhalf_t>(x_fp32);
}
template <typename T> template <typename T>
struct NumericLimits struct NumericLimits
{ {
......
library/src/tensor_operation_instance/gpu/gemm/CMakeLists.txt
View file @ 18d5297b
...@@ -111,6 +111,12 @@ list(APPEND GEMM_INSTANCES ...@@ -111,6 +111,12 @@ list(APPEND GEMM_INSTANCES
device_gemm_xdl_c_shuffle_fp8_fp8_fp8_km_kn_mn_instance.cpp device_gemm_xdl_c_shuffle_fp8_fp8_fp8_km_kn_mn_instance.cpp
device_gemm_xdl_c_shuffle_fp8_fp8_fp8_km_nk_mn_instance.cpp) device_gemm_xdl_c_shuffle_fp8_fp8_fp8_km_nk_mn_instance.cpp)
list(APPEND GEMM_INSTANCES
device_gemm_wmma_f16_f16_f16_mk_kn_mn_instance.cpp
device_gemm_wmma_f16_f16_f16_mk_nk_mn_instance.cpp
device_gemm_wmma_f16_f16_f16_km_kn_mn_instance.cpp
device_gemm_wmma_f16_f16_f16_km_nk_mn_instance.cpp)
add_instance_library(device_gemm_instance ${GEMM_INSTANCES}) add_instance_library(device_gemm_instance ${GEMM_INSTANCES})
set(ENABLE_PIPELINE_V2_OPT) set(ENABLE_PIPELINE_V2_OPT)
......
library/src/tensor_operation_instance/gpu/gemm_bilinear/CMakeLists.txt
View file @ 18d5297b
...@@ -3,8 +3,8 @@ add_instance_library(device_gemm_bilinear_instance ...@@ -3,8 +3,8 @@ add_instance_library(device_gemm_bilinear_instance
device_gemm_bilinear_xdl_c_shuffle_f16_f16_f16_f16_km_nk_mn_mn_instance.cpp device_gemm_bilinear_xdl_c_shuffle_f16_f16_f16_f16_km_nk_mn_mn_instance.cpp
device_gemm_bilinear_xdl_c_shuffle_f16_f16_f16_f16_mk_kn_mn_mn_instance.cpp device_gemm_bilinear_xdl_c_shuffle_f16_f16_f16_f16_mk_kn_mn_mn_instance.cpp
device_gemm_bilinear_xdl_c_shuffle_f16_f16_f16_f16_mk_nk_mn_mn_instance.cpp device_gemm_bilinear_xdl_c_shuffle_f16_f16_f16_f16_mk_nk_mn_mn_instance.cpp
#device_gemm_bilinear_wmma_c_shuffle_i8_i8_i8_i8_km_kn_mn_mn_instance.cpp device_gemm_bilinear_wmma_c_shuffle_i8_i8_i8_i8_km_kn_mn_mn_instance.cpp
#device_gemm_bilinear_wmma_c_shuffle_i8_i8_i8_i8_km_nk_mn_mn_instance.cpp device_gemm_bilinear_wmma_c_shuffle_i8_i8_i8_i8_km_nk_mn_mn_instance.cpp
#device_gemm_bilinear_wmma_c_shuffle_i8_i8_i8_i8_mk_kn_mn_mn_instance.cpp device_gemm_bilinear_wmma_c_shuffle_i8_i8_i8_i8_mk_kn_mn_mn_instance.cpp
#device_gemm_bilinear_wmma_c_shuffle_i8_i8_i8_i8_mk_nk_mn_mn_instance.cpp device_gemm_bilinear_wmma_c_shuffle_i8_i8_i8_i8_mk_nk_mn_mn_instance.cpp
) )
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