mirror of
https://github.com/ROCm/composable_kernel.git
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embedding fuse layernorm (#405)
* add gridwise/device sparse embedding
* update code
* update code
* remove useless makefile
* code fix
* workable
* work properly
* emb add
* add more instance
* format
* remove useless code
* fix format
* fix clang-tidy
* clean
* fix a compile error
Co-authored-by: Chao Liu <chao.liu2@amd.com>
Co-authored-by: Chao Liu <lc.roy86@gmail.com>
[ROCm/composable_kernel commit: efd1d25733]
This commit is contained in:
carlushuang
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// SPDX-License-Identifier: MIT
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// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
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#pragma once
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#include <iostream>
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#include <sstream>
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#include "ck/host_utility/device_prop.hpp"
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#include "ck/host_utility/kernel_launch.hpp"
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#include "ck/tensor_operation/gpu/device/device_base.hpp"
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#include "ck/utility/common_header.hpp"
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#include "ck/tensor_description/tensor_descriptor.hpp"
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#include "ck/tensor_description/tensor_descriptor_helper.hpp"
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#include "ck/tensor_operation/gpu/grid/gridwise_sparse_embedding3_forward_layernorm.hpp"
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namespace ck {
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namespace tensor_operation {
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namespace device {
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template <typename EmbType,
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typename IndexType,
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typename GammaDataType,
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typename BetaDataType,
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typename AccDataType,
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typename OutType,
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ck::index_t BlockSize,
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ck::index_t DimClusterSize,
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ck::index_t RowClusterSize,
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ck::index_t DimPerBlock,
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ck::index_t RowPerBlock,
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ck::index_t DimThreadSize,
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ck::index_t RowVectorSize>
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struct DeviceSparseEmbedding3ForwardLayernorm : public BaseOperator
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{
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static auto MakeOutputDescriptor(const index_t index_length, const index_t rows)
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{
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return make_naive_tensor_descriptor_packed(make_tuple(index_length, rows));
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}
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struct Argument : public BaseArgument
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{
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Argument(OutType* p_out,
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const EmbType* p_emb_a,
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const EmbType* p_emb_b,
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const EmbType* p_emb_c,
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const IndexType* p_index_a,
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const IndexType* p_index_b,
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const IndexType* p_index_c,
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const GammaDataType* p_gamma,
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const BetaDataType* p_beta,
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const ck::index_t NumRows,
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const ck::index_t EmbeddingDim,
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const ck::index_t IndexLength,
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const AccDataType epsilon)
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: p_out_(p_out),
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p_emb_a_(p_emb_a),
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p_emb_b_(p_emb_b),
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p_emb_c_(p_emb_c),
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p_index_a_(p_index_a),
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p_index_b_(p_index_b),
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p_index_c_(p_index_c),
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p_gamma_(p_gamma),
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p_beta_(p_beta),
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NumRows_(NumRows),
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EmbeddingDim_(EmbeddingDim),
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IndexLength_(IndexLength),
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epsilon_(epsilon)
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{
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grid_size_ = (IndexLength + DimClusterSize - 1) / DimClusterSize;
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}
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OutType* p_out_;
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const EmbType* p_emb_a_;
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const EmbType* p_emb_b_;
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const EmbType* p_emb_c_;
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const IndexType* p_index_a_;
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const IndexType* p_index_b_;
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const IndexType* p_index_c_;
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const GammaDataType* p_gamma_;
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const BetaDataType* p_beta_;
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ck::index_t NumRows_;
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ck::index_t EmbeddingDim_;
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ck::index_t IndexLength_;
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AccDataType epsilon_;
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size_t grid_size_;
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};
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virtual std::unique_ptr<BaseArgument> MakeArgumentPointer(void* p_out,
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const void* p_emb_a,
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const void* p_emb_b,
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const void* p_emb_c,
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const void* p_index_a,
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const void* p_index_b,
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const void* p_index_c,
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const void* p_gamma,
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const void* p_beta,
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ck::index_t NumRows,
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ck::index_t EmbeddingDim,
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ck::index_t IndexLength,
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const AccDataType epsilon)
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{
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return std::make_unique<Argument>(reinterpret_cast<OutType*>(p_out),
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reinterpret_cast<const EmbType*>(p_emb_a),
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reinterpret_cast<const EmbType*>(p_emb_b),
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reinterpret_cast<const EmbType*>(p_emb_c),
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reinterpret_cast<const IndexType*>(p_index_a),
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reinterpret_cast<const IndexType*>(p_index_b),
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reinterpret_cast<const IndexType*>(p_index_c),
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reinterpret_cast<const GammaDataType*>(p_gamma),
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reinterpret_cast<const BetaDataType*>(p_beta),
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NumRows,
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EmbeddingDim,
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IndexLength,
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epsilon);
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}
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using GridwiseSparseEmbedding =
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GridwiseSparseEmbedding3ForwardLayernorm<EmbType,
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IndexType,
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GammaDataType,
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BetaDataType,
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AccDataType,
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OutType,
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decltype(MakeOutputDescriptor(1, 1)),
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BlockSize,
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DimClusterSize,
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RowClusterSize,
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DimPerBlock,
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RowPerBlock,
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DimThreadSize,
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RowVectorSize>;
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struct Invoker : public BaseInvoker
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{
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float Run(const Argument& arg, const StreamConfig& stream_config = StreamConfig{})
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{
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auto out_desc = MakeOutputDescriptor(arg.IndexLength_, arg.EmbeddingDim_);
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const auto kernel_main =
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kernel_sparse_embedding3_forward_layernorm<GridwiseSparseEmbedding,
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EmbType,
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IndexType,
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GammaDataType,
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BetaDataType,
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AccDataType,
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OutType,
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decltype(out_desc)>;
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float avg_time = 0;
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avg_time += launch_and_time_kernel(stream_config,
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kernel_main,
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dim3(arg.grid_size_),
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dim3(BlockSize),
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0,
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arg.p_out_,
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arg.p_emb_a_,
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arg.p_emb_b_,
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arg.p_emb_c_,
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arg.p_index_a_,
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arg.p_index_b_,
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arg.p_index_c_,
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arg.p_gamma_,
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arg.p_beta_,
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out_desc,
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arg.epsilon_);
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return (avg_time);
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}
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float Run(const BaseArgument* p_arg,
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const StreamConfig& stream_config = StreamConfig{}) override
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{
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return Run(*dynamic_cast<const Argument*>(p_arg), stream_config);
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};
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};
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static bool IsSupportedArgument(const Argument* p_arg)
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{
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return (RowPerBlock == p_arg->EmbeddingDim_) && (p_arg->NumRows_ % DimPerBlock == 0);
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}
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bool IsSupportedArgument(const BaseArgument* p_arg) override
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{
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return IsSupportedArgument(dynamic_cast<const Argument*>(p_arg));
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}
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virtual std::unique_ptr<BaseInvoker> MakeInvokerPointer()
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{
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return std::make_unique<Invoker>();
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}
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std::string GetTypeString() const override
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{
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auto str = std::stringstream();
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// clang-format off
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str << "DeviceSparseEmbedding3ForwardLayernorm_"<< BlockSize << "_" <<
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DimClusterSize << "x" << RowClusterSize << "_" <<
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DimPerBlock << "x" << RowPerBlock << "_" <<
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DimThreadSize << "x" << RowVectorSize;
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// clang-format on
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return str.str();
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}
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};
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} // namespace device
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} // namespace tensor_operation
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} // namespace ck
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@@ -0,0 +1,344 @@
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// SPDX-License-Identifier: MIT
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// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
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#pragma once
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#include "ck/utility/common_header.hpp"
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#include "ck/tensor_operation/gpu/thread/threadwise_tensor_slice_transfer.hpp"
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#include "ck/tensor_operation/gpu/thread/threadwise_welford.hpp"
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#include "ck/tensor_operation/gpu/block/blockwise_welford.hpp"
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namespace ck {
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template <typename GridwiseSparseEmbedding,
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typename EmbType,
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typename IndexType,
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typename GammaDataType,
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typename BetaDataType,
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typename AccDataType,
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typename OutType,
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typename OutGridDesc>
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#if CK_USE_LAUNCH_BOUNDS
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__launch_bounds__(CK_MAX_THREAD_PER_BLOCK, CK_MIN_BLOCK_PER_CU)
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#endif
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__global__ void kernel_sparse_embedding3_forward_layernorm(OutType* p_out,
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const EmbType* p_emb_a,
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const EmbType* p_emb_b,
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const EmbType* p_emb_c,
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const IndexType* p_index_a,
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const IndexType* p_index_b,
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const IndexType* p_index_c,
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const GammaDataType* p_gamma,
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const BetaDataType* p_beta,
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const OutGridDesc out_grid_desc,
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const AccDataType epsilon)
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{
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GridwiseSparseEmbedding::Run(p_out,
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p_emb_a,
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p_emb_b,
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p_emb_c,
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p_index_a,
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p_index_b,
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p_index_c,
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p_gamma,
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p_beta,
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out_grid_desc,
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epsilon);
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}
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template <typename EmbType,
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typename IndexType,
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typename GammaDataType,
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typename BetaDataType,
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typename AccDataType,
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typename OutType,
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typename OutGridDesc,
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ck::index_t BlockSize,
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ck::index_t DimClusterSize,
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ck::index_t RowClusterSize,
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ck::index_t DimPerBlock, // Row x Dim, along Dim
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ck::index_t RowPerBlock, // Row x Dim, along Row
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ck::index_t DimThreadSize, // this is actually not vector, but number of registers
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ck::index_t RowVectorSize>
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struct GridwiseSparseEmbedding3ForwardLayernorm
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{
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static constexpr auto I0 = Number<0>{};
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static constexpr auto I1 = Number<1>{};
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static constexpr auto I2 = Number<2>{};
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static constexpr auto I3 = Number<3>{};
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static constexpr index_t WaveSize = 64;
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static_assert(BlockSize == RowClusterSize * DimClusterSize,
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"Invalid cluster distribution within block");
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static_assert(RowClusterSize % WaveSize == 0, "need to be wavewise");
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static_assert(DimPerBlock % (DimClusterSize * DimThreadSize) == 0, "");
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static_assert(RowPerBlock % (RowClusterSize * RowVectorSize) == 0, "");
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static constexpr auto DimSubBlocks = DimPerBlock / (DimClusterSize * DimThreadSize);
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static constexpr auto RowSubBlocks = RowPerBlock / (RowClusterSize * RowVectorSize);
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static_assert((DimPerBlock % DimSubBlocks == 0) && (RowPerBlock % RowSubBlocks == 0), "");
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static constexpr auto DimPerSubBlock = DimPerBlock / DimSubBlocks;
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static constexpr auto RowPerSubBlock = RowPerBlock / RowSubBlocks;
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using ThreadwiseWolfordDesc2D = decltype(make_naive_tensor_descriptor_packed(make_tuple(
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Number<DimSubBlocks * DimThreadSize>{}, Number<RowSubBlocks * RowVectorSize>{})));
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using ThreadwiseWolfordDescReduce = decltype(
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make_naive_tensor_descriptor_packed(make_tuple(Number<DimSubBlocks * DimThreadSize>{})));
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using ThreadwiseWelford =
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ThreadwiseWelford<AccDataType, ThreadwiseWolfordDesc2D, ThreadwiseWolfordDescReduce>;
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using ThreadClusterLength = Sequence<DimClusterSize, RowClusterSize>;
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using BlockwiseWelford =
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BlockwiseWelford<AccDataType, BlockSize, ThreadClusterLength, Sequence<0, 1>>;
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__device__ static void Run(OutType* p_out,
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const EmbType* p_emb_a,
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const EmbType* p_emb_b,
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const EmbType* p_emb_c,
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const IndexType* p_index_a,
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const IndexType* p_index_b,
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const IndexType* p_index_c,
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const GammaDataType* p_gamma,
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const BetaDataType* p_beta,
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const OutGridDesc,
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const AccDataType epsilon)
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{
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const index_t thread_local_id = get_thread_local_1d_id();
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const index_t block_global_id = get_block_1d_id();
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// const auto index_length = out_grid_desc.GetLength(I0);
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// const auto emb_dim = out_grid_desc.GetLength(I1);
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constexpr auto thread_cluster_desc =
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make_cluster_descriptor(Sequence<DimClusterSize, RowClusterSize>{}, Sequence<0, 1>{});
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const auto thread_cluster_idx =
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thread_cluster_desc.CalculateBottomIndex(make_multi_index(thread_local_id));
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const auto thread_dim_cluster_id = thread_cluster_idx[I0];
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const auto thread_row_cluster_id = thread_cluster_idx[I1];
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const auto wave_dim_id = __builtin_amdgcn_readfirstlane(thread_dim_cluster_id / WaveSize);
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const auto index_start = block_global_id * DimPerBlock + wave_dim_id * DimThreadSize;
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auto threadwise_welford = ThreadwiseWelford();
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threadwise_welford.max_count_ = RowSubBlocks * RowVectorSize;
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constexpr auto thread_buf_size =
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DimSubBlocks * DimThreadSize * RowSubBlocks * RowVectorSize;
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constexpr auto thread_buf_desc = make_naive_tensor_descriptor_packed(
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make_tuple(DimSubBlocks, DimThreadSize, RowSubBlocks, RowVectorSize));
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constexpr auto mean_var_buf_size = DimSubBlocks * DimThreadSize;
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constexpr auto mean_var_buf_desc =
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make_naive_tensor_descriptor_packed(make_tuple(DimSubBlocks, DimThreadSize));
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constexpr auto gamma_beta_buf_size = RowSubBlocks * RowVectorSize;
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constexpr auto gamma_beta_buf_desc =
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make_naive_tensor_descriptor_packed(make_tuple(RowSubBlocks, RowVectorSize));
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StaticBuffer<AddressSpaceEnum::Vgpr, EmbType, thread_buf_size, true> in_thread_buf_a;
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StaticBuffer<AddressSpaceEnum::Vgpr, EmbType, thread_buf_size, true> in_thread_buf_b;
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StaticBuffer<AddressSpaceEnum::Vgpr, EmbType, thread_buf_size, true> in_thread_buf_c;
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StaticBuffer<AddressSpaceEnum::Sgpr, IndexType, DimPerBlock, true> index_buf_a;
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StaticBuffer<AddressSpaceEnum::Sgpr, IndexType, DimPerBlock, true> index_buf_b;
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StaticBuffer<AddressSpaceEnum::Sgpr, IndexType, DimPerBlock, true> index_buf_c;
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StaticBuffer<AddressSpaceEnum::Vgpr, AccDataType, thread_buf_size, true> acc_thread_buf;
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StaticBuffer<AddressSpaceEnum::Vgpr, AccDataType, gamma_beta_buf_size, true>
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gamma_thread_buf;
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StaticBuffer<AddressSpaceEnum::Vgpr, AccDataType, gamma_beta_buf_size, true>
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beta_thread_buf;
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StaticBuffer<AddressSpaceEnum::Vgpr, AccDataType, mean_var_buf_size, true> mean_thread_buf;
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StaticBuffer<AddressSpaceEnum::Vgpr, AccDataType, mean_var_buf_size, true> var_thread_buf;
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auto load_current_sub_row = [&](auto i_dim_sub_, auto i_row_sub_) {
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vector_type_maker_t<EmbType, RowVectorSize> emb_vector_a;
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vector_type_maker_t<EmbType, RowVectorSize> emb_vector_b;
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vector_type_maker_t<EmbType, RowVectorSize> emb_vector_c;
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using src_vector_t = typename decltype(emb_vector_a)::type;
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static_for<0, DimThreadSize, 1>{}([&](auto i_dim_vec_) {
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constexpr auto current_dim = i_dim_sub_ * DimPerSubBlock + i_dim_vec_;
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IndexType index_a = index_buf_a[Number<current_dim>{}];
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IndexType index_b = index_buf_b[Number<current_dim>{}];
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IndexType index_c = index_buf_c[Number<current_dim>{}];
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auto thread_offset = (thread_row_cluster_id + i_row_sub_ * RowClusterSize) *
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sizeof(EmbType) * RowVectorSize;
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int32x4_t emb_res_a =
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make_wave_buffer_resource_with_default_range(p_emb_a + index_a * RowPerBlock);
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int32x4_t emb_res_b =
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make_wave_buffer_resource_with_default_range(p_emb_b + index_b * RowPerBlock);
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int32x4_t emb_res_c =
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make_wave_buffer_resource_with_default_range(p_emb_c + index_c * RowPerBlock);
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emb_vector_a.template AsType<src_vector_t>()(I0) =
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amd_buffer_load_impl<EmbType, RowVectorSize>(emb_res_a, thread_offset, 0);
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emb_vector_b.template AsType<src_vector_t>()(I0) =
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amd_buffer_load_impl<EmbType, RowVectorSize>(emb_res_b, thread_offset, 0);
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emb_vector_c.template AsType<src_vector_t>()(I0) =
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amd_buffer_load_impl<EmbType, RowVectorSize>(emb_res_c, thread_offset, 0);
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static_for<0, RowVectorSize, 1>{}([&](auto i_row_vec_) {
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constexpr auto register_offset = thread_buf_desc.CalculateOffset(
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make_tuple(i_dim_sub_, i_dim_vec_, i_row_sub_, i_row_vec_));
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in_thread_buf_a(Number<register_offset>{}) =
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emb_vector_a.template AsType<EmbType>()[i_row_vec_];
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in_thread_buf_b(Number<register_offset>{}) =
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emb_vector_b.template AsType<EmbType>()[i_row_vec_];
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in_thread_buf_c(Number<register_offset>{}) =
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emb_vector_c.template AsType<EmbType>()[i_row_vec_];
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});
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});
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};
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auto accumulate_current_sub_row = [&](auto i_dim_sub_, auto i_row_sub_) {
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static_for<0, DimThreadSize, 1>{}([&](auto i_dim_vec_) {
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static_for<0, RowVectorSize, 1>{}([&](auto i_row_vec_) {
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constexpr auto register_offset = thread_buf_desc.CalculateOffset(
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make_tuple(i_dim_sub_, i_dim_vec_, i_row_sub_, i_row_vec_));
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AccDataType va =
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ck::type_convert<AccDataType>(in_thread_buf_a(Number<register_offset>{}));
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AccDataType vb =
|
||||
ck::type_convert<AccDataType>(in_thread_buf_b(Number<register_offset>{}));
|
||||
AccDataType vc =
|
||||
ck::type_convert<AccDataType>(in_thread_buf_c(Number<register_offset>{}));
|
||||
|
||||
acc_thread_buf(Number<register_offset>{}) += va + vb + vc;
|
||||
});
|
||||
});
|
||||
};
|
||||
|
||||
auto threadwise_welford_sub_row = [&](auto i_dim_sub_, auto i_row_sub_) {
|
||||
static_for<0, DimThreadSize, 1>{}([&](auto i_dim_vec_) {
|
||||
static_for<0, RowVectorSize, 1>{}([&](auto i_row_vec_) {
|
||||
constexpr auto register_offset = thread_buf_desc.CalculateOffset(
|
||||
make_tuple(i_dim_sub_, i_dim_vec_, i_row_sub_, i_row_vec_));
|
||||
constexpr auto mean_var_offset =
|
||||
mean_var_buf_desc.CalculateOffset(make_tuple(i_dim_sub_, i_dim_vec_));
|
||||
|
||||
threadwise_welford.cur_count_++;
|
||||
threadwise_welford.Update(mean_thread_buf(Number<mean_var_offset>{}),
|
||||
var_thread_buf(Number<mean_var_offset>{}),
|
||||
acc_thread_buf(Number<register_offset>{}));
|
||||
});
|
||||
});
|
||||
};
|
||||
|
||||
auto threadwise_normalize_store_out = [&](auto i_dim_sub_, auto i_row_sub_) {
|
||||
int32x4_t out_res =
|
||||
make_wave_buffer_resource_with_default_range(p_out + index_start * RowPerBlock);
|
||||
static_for<0, DimThreadSize, 1>{}([&](auto i_dim_vec_) {
|
||||
vector_type_maker_t<OutType, RowVectorSize> out_vector;
|
||||
using dst_vector_t = typename decltype(out_vector)::type;
|
||||
|
||||
constexpr auto mean_var_offset =
|
||||
mean_var_buf_desc.CalculateOffset(make_tuple(i_dim_sub_, i_dim_vec_));
|
||||
|
||||
static_for<0, RowVectorSize, 1>{}([&](auto i_row_vec_) {
|
||||
constexpr auto register_offset = thread_buf_desc.CalculateOffset(
|
||||
make_tuple(i_dim_sub_, i_dim_vec_, i_row_sub_, i_row_vec_));
|
||||
constexpr auto gamma_beta_offset =
|
||||
gamma_beta_buf_desc.CalculateOffset(make_tuple(i_row_sub_, i_row_vec_));
|
||||
|
||||
auto acc_val = acc_thread_buf[Number<register_offset>{}];
|
||||
acc_val = (acc_val - mean_thread_buf(Number<mean_var_offset>{})) /
|
||||
sqrt(var_thread_buf(Number<mean_var_offset>{}) + epsilon);
|
||||
acc_val = acc_val * gamma_thread_buf[Number<gamma_beta_offset>{}] +
|
||||
beta_thread_buf[Number<gamma_beta_offset>{}];
|
||||
|
||||
out_vector.template AsType<OutType>()(Number<i_row_vec_>{}) =
|
||||
type_convert<OutType>(acc_val);
|
||||
});
|
||||
|
||||
index_t thread_offset = (thread_row_cluster_id + i_row_sub_ * RowClusterSize) *
|
||||
sizeof(OutType) * RowVectorSize;
|
||||
|
||||
amd_buffer_store_impl<OutType, RowVectorSize>(
|
||||
out_vector.template AsType<dst_vector_t>()[Number<0>{}],
|
||||
out_res,
|
||||
thread_offset,
|
||||
0);
|
||||
});
|
||||
};
|
||||
|
||||
// first load index
|
||||
ck::static_for<0, DimPerBlock, 1>{}([&](auto i_idx_) {
|
||||
// prefer use s_load
|
||||
index_buf_a(i_idx_) = p_index_a[index_start + i_idx_.value];
|
||||
index_buf_b(i_idx_) = p_index_b[index_start + i_idx_.value];
|
||||
index_buf_c(i_idx_) = p_index_c[index_start + i_idx_.value];
|
||||
});
|
||||
|
||||
// load gamma/beta
|
||||
static_for<0, RowSubBlocks, 1>{}([&](auto i_row_sub_) {
|
||||
vector_type_maker_t<GammaDataType, RowVectorSize> gamma_vector;
|
||||
vector_type_maker_t<BetaDataType, RowVectorSize> beta_vector;
|
||||
|
||||
index_t thread_offset_gamma = (thread_row_cluster_id + i_row_sub_ * RowClusterSize) *
|
||||
sizeof(GammaDataType) * RowVectorSize;
|
||||
index_t thread_offset_beta = (thread_row_cluster_id + i_row_sub_ * RowClusterSize) *
|
||||
sizeof(BetaDataType) * RowVectorSize;
|
||||
|
||||
int32x4_t gamma_res = make_wave_buffer_resource_with_default_range(p_gamma);
|
||||
int32x4_t beta_res = make_wave_buffer_resource_with_default_range(p_beta);
|
||||
|
||||
gamma_vector.template AsType<typename decltype(gamma_vector)::type>()(I0) =
|
||||
amd_buffer_load_impl<GammaDataType, RowVectorSize>(
|
||||
gamma_res, thread_offset_gamma, 0);
|
||||
beta_vector.template AsType<typename decltype(beta_vector)::type>()(I0) =
|
||||
amd_buffer_load_impl<BetaDataType, RowVectorSize>(beta_res, thread_offset_beta, 0);
|
||||
|
||||
static_for<0, RowVectorSize, 1>{}([&](auto i_row_vec_) {
|
||||
constexpr auto offset =
|
||||
gamma_beta_buf_desc.CalculateOffset(make_tuple(i_row_sub_, i_row_vec_));
|
||||
gamma_thread_buf(Number<offset>{}) = type_convert<AccDataType>(
|
||||
gamma_vector.template AsType<GammaDataType>()[Number<i_row_vec_>{}]);
|
||||
beta_thread_buf(Number<offset>{}) = type_convert<AccDataType>(
|
||||
beta_vector.template AsType<BetaDataType>()[Number<i_row_vec_>{}]);
|
||||
});
|
||||
});
|
||||
|
||||
static_for<0, thread_buf_size, 1>{}(
|
||||
[&](auto I) { acc_thread_buf(I) = type_convert<AccDataType>(0.0f); });
|
||||
|
||||
static_for<0, mean_var_buf_size, 1>{}([&](auto I) {
|
||||
mean_thread_buf(I) = type_convert<AccDataType>(0.0f);
|
||||
var_thread_buf(I) = type_convert<AccDataType>(0.0f);
|
||||
});
|
||||
|
||||
static_for<0, DimSubBlocks, 1>{}([&](auto i_dim_sub) {
|
||||
load_current_sub_row(i_dim_sub, Number<0>{});
|
||||
static_for<0, RowSubBlocks - 1, 1>{}([&](auto i_row) {
|
||||
load_current_sub_row(i_dim_sub, Number<1>{} + i_row);
|
||||
accumulate_current_sub_row(i_dim_sub, i_row);
|
||||
threadwise_welford_sub_row(i_dim_sub, i_row);
|
||||
});
|
||||
accumulate_current_sub_row(i_dim_sub, Number<RowSubBlocks - 1>{});
|
||||
threadwise_welford_sub_row(i_dim_sub, Number<RowSubBlocks - 1>{});
|
||||
|
||||
// blockwise welford
|
||||
static_for<0, mean_var_buf_size, 1>{}([&](auto I) {
|
||||
if constexpr(I > 0)
|
||||
block_sync_lds();
|
||||
|
||||
BlockwiseWelford::Run(
|
||||
mean_thread_buf(I), var_thread_buf(I), threadwise_welford.cur_count_);
|
||||
});
|
||||
|
||||
// store
|
||||
static_for<0, RowSubBlocks, 1>{}(
|
||||
[&](auto i_row) { threadwise_normalize_store_out(i_dim_sub, i_row); });
|
||||
});
|
||||
}
|
||||
};
|
||||
|
||||
} // namespace ck
|
||||
@@ -34,6 +34,21 @@ __device__ int32x4_t make_wave_buffer_resource(T* p_wave, index_t element_space_
|
||||
return wave_buffer_resource.content;
|
||||
}
|
||||
|
||||
template <typename T>
|
||||
__device__ int32x4_t make_wave_buffer_resource_with_default_range(T* p_wave)
|
||||
{
|
||||
BufferResource<T> wave_buffer_resource;
|
||||
|
||||
// wavewise base address (64 bit)
|
||||
wave_buffer_resource.address(Number<0>{}) = const_cast<remove_cv_t<T>*>(p_wave);
|
||||
// wavewise range (32 bit)
|
||||
wave_buffer_resource.range(Number<2>{}) = 0xffffffff; // max possible range
|
||||
// wavewise setting (32 bit)
|
||||
wave_buffer_resource.config(Number<3>{}) = CK_BUFFER_RESOURCE_3RD_DWORD;
|
||||
|
||||
return wave_buffer_resource.content;
|
||||
}
|
||||
|
||||
// buffer load i8
|
||||
__device__ int8_t
|
||||
llvm_amdgcn_raw_buffer_load_i8(int32x4_t srsrc,
|
||||
|
||||
Reference in New Issue
Block a user