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Commit 56532f77 authored by rocking's avatar rocking
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Add second kernel of normalization splitK

parent 28ebcfe7
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Showing with 595 additions and 45 deletions
include/ck/tensor_operation/gpu/device/impl/device_normalization_splitk_impl.hpp
View file @ 56532f77
...@@ -12,12 +12,13 @@ ...@@ -12,12 +12,13 @@
#include "ck/tensor_operation/gpu/device/device_reduce.hpp" #include "ck/tensor_operation/gpu/device/device_reduce.hpp"
#include "ck/tensor_operation/gpu/device/impl/device_reduce_common.hpp" #include "ck/tensor_operation/gpu/device/impl/device_reduce_common.hpp"
#include "ck/tensor_operation/gpu/grid/normalization/gridwise_normalization_splitk_1st.hpp" #include "ck/tensor_operation/gpu/grid/normalization/gridwise_normalization_splitk_1st.hpp"
#include "ck/tensor_operation/gpu/grid/normalization/gridwise_normalization_splitk_2nd.hpp"
#include "ck/tensor_operation/gpu/grid/gridwise_set_buffer_value.hpp" #include "ck/tensor_operation/gpu/grid/gridwise_set_buffer_value.hpp"
#include "ck/host_utility/device_prop.hpp" #include "ck/host_utility/device_prop.hpp"
#include "ck/host_utility/kernel_launch.hpp" #include "ck/host_utility/kernel_launch.hpp"
namespace ck { namespace ck {
template <typename GridwiseWelford1, template <typename GridwiseWelford,
typename XDataType, typename XDataType,
typename MeanVarDataType, typename MeanVarDataType,
typename ComputeDataType, typename ComputeDataType,
...@@ -32,13 +33,64 @@ kernel_normalizationSplitK1st(const XGridDesc_M_K x_grid_desc_m_k, ...@@ -32,13 +33,64 @@ kernel_normalizationSplitK1st(const XGridDesc_M_K x_grid_desc_m_k,
MeanVarDataType* const __restrict__ p_welford_variance, MeanVarDataType* const __restrict__ p_welford_variance,
int32_t* const __restrict__ p_welford_count) int32_t* const __restrict__ p_welford_count)
{ {
GridwiseWelford1::Run(x_grid_desc_m_k, GridwiseWelford::Run(x_grid_desc_m_k,
mean_var_grid_desc_m_kblock, mean_var_grid_desc_m_kblock,
num_k_block_tile_iteration, num_k_block_tile_iteration,
p_x_global, p_x_global,
p_welford_mean, p_welford_mean,
p_welford_variance, p_welford_variance,
p_welford_count); p_welford_count);
};
template <typename GridwiseWelfordNormalization,
typename MeanVarDataType,
typename XDataType,
typename GammaDataType,
typename BetaDataType,
typename YDataType,
typename ComputeDataType,
typename YElementwiseOperation,
typename MeanVarGridDesc_M_KBlock,
typename CountVarGridDesc_M_KBlock,
typename XYGammaBetaGridDesc_M_K>
__global__ void
kernel_normalizationSplitK2nd(const MeanVarGridDesc_M_KBlock mean_var_grid_desc_m_kblock,
const CountVarGridDesc_M_KBlock count_grid_desc_m_kblock,
const XYGammaBetaGridDesc_M_K x_grid_desc_m_k,
const XYGammaBetaGridDesc_M_K gamma_grid_desc_m_k,
const XYGammaBetaGridDesc_M_K beta_grid_desc_m_k,
const XYGammaBetaGridDesc_M_K y_grid_desc_m_k,
index_t num_k_mean_var_count_iteration,
index_t num_k_block_tile_iteration,
index_t k_grid_size,
ComputeDataType epsilon,
const MeanVarDataType* const p_mean_global,
const MeanVarDataType* const p_variance_global,
const int32_t* const p_welford_count_global,
const XDataType* const __restrict__ p_x_global,
const GammaDataType* const __restrict__ p_gamma_global,
const BetaDataType* const __restrict__ p_beta_global,
YDataType* const __restrict__ p_y_global,
const YElementwiseOperation y_elementwise_op)
{
GridwiseWelfordNormalization::Run(mean_var_grid_desc_m_kblock,
count_grid_desc_m_kblock,
x_grid_desc_m_k,
gamma_grid_desc_m_k,
beta_grid_desc_m_k,
y_grid_desc_m_k,
num_k_mean_var_count_iteration,
num_k_block_tile_iteration,
k_grid_size,
epsilon,
p_mean_global,
p_variance_global,
p_welford_count_global,
p_x_global,
p_gamma_global,
p_beta_global,
p_y_global,
y_elementwise_op);
}; };
} // namespace ck } // namespace ck
...@@ -64,7 +116,7 @@ template <typename XDataType, ...@@ -64,7 +116,7 @@ template <typename XDataType,
index_t KThreadClusterSize, index_t KThreadClusterSize,
index_t MThreadSliceSize, index_t MThreadSliceSize,
index_t KThreadSliceSize, index_t KThreadSliceSize,
index_t XYSrcVectorDim, index_t XYVectorDim,
index_t XSrcVectorSize, index_t XSrcVectorSize,
index_t GammaSrcVectorDim, index_t GammaSrcVectorDim,
index_t GammaSrcVectorSize, index_t GammaSrcVectorSize,
...@@ -184,21 +236,52 @@ struct DeviceNormalizationSplitKImpl : public DeviceNormalization<XDataType, ...@@ -184,21 +236,52 @@ struct DeviceNormalizationSplitKImpl : public DeviceNormalization<XDataType,
} }
using SrcGridDesc_M_K = decltype(MakeSrc2dDescriptor({1}, {1}, 1, 1)); using SrcGridDesc_M_K = decltype(MakeSrc2dDescriptor({1}, {1}, 1, 1));
using Welford1MeanVarGridDesc_M_KBlock = using Kernel1MeanVarGridDesc_M_KBlock =
decltype(MakeMeanVarDescriptor_M_K<Sequence<true, false>, 1, 1>(1, 1)); decltype(MakeMeanVarDescriptor_M_K<Sequence<true, false>, 1, 1>(1, 1));
using GridwiseWelford1 = GridwiseNormalizationSplitK1st<XDataType, using Kernel2MeanVarGridDesc_M_KBlock =
ComputeDataType, decltype(MakeMeanVarDescriptor_M_K<Sequence<true, true>, 1, 1>(1, 1));
MeanVarDataType,
SrcGridDesc_M_K, using Kernel2CountGridDesc_M_KBlock =
Welford1MeanVarGridDesc_M_KBlock, decltype(MakeCountDescriptor_M_K<Sequence<true, true>, 1, 1>(1, 1));
BlockSize,
MThreadClusterSize, using GridwiseWelford = GridwiseNormalizationSplitK1st<XDataType,
KThreadClusterSize, ComputeDataType,
MThreadSliceSize, MeanVarDataType,
KThreadSliceSize, SrcGridDesc_M_K,
XYSrcVectorDim, Kernel1MeanVarGridDesc_M_KBlock,
XSrcVectorSize>; BlockSize,
MThreadClusterSize,
KThreadClusterSize,
MThreadSliceSize,
KThreadSliceSize,
XYVectorDim,
XSrcVectorSize>;
using GridwiseWelfordNormalization =
GridwiseNormalizationSplitK2nd<MeanVarDataType,
XDataType,
GammaDataType,
BetaDataType,
YDataType,
ComputeDataType,
YElementwiseOperation,
Kernel2MeanVarGridDesc_M_KBlock,
Kernel2CountGridDesc_M_KBlock,
SrcGridDesc_M_K,
BlockSize,
MThreadClusterSize,
KThreadClusterSize,
MThreadSliceSize,
KThreadSliceSize,
XYVectorDim,
XSrcVectorSize,
GammaSrcVectorDim,
GammaSrcVectorSize,
BetaSrcVectorDim,
BetaSrcVectorSize,
XYVectorDim,
YDstVectorSize>;
struct Argument : public BaseArgument struct Argument : public BaseArgument
{ {
...@@ -236,19 +319,19 @@ struct DeviceNormalizationSplitKImpl : public DeviceNormalization<XDataType, ...@@ -236,19 +319,19 @@ struct DeviceNormalizationSplitKImpl : public DeviceNormalization<XDataType,
numBlockTileIteration_ = 1; numBlockTileIteration_ = 1;
while(true) while(true)
{ {
int testKGridSize_ = int testKGridSize =
math::integer_divide_ceil(KRaw_, K_BlockTileSize * numBlockTileIteration_); math::integer_divide_ceil(KRaw_, K_BlockTileSize * numBlockTileIteration_);
// we want the testKGridSize_ be not more than 128 // we want the kGridSize_ be not more than 128
if(testKGridSize_ <= 128) if(testKGridSize <= 128)
break; break;
++numBlockTileIteration_; ++numBlockTileIteration_;
}; };
kGridSize_ = math::integer_divide_ceil(KRaw_, K_BlockTileSize * numBlockTileIteration_); kGridSize_ = math::integer_divide_ceil(KRaw_, K_BlockTileSize * numBlockTileIteration_);
gridSize_ = math::integer_divide_ceil(MRaw_, M_BlockTileSize) * kGridSize_;
gridSize_ = math::integer_divide_ceil(MRaw_, M_BlockTileSize) * kGridSize_; numMeanVarCountIteration_ = math::integer_divide_ceil(kGridSize_, KThreadClusterSize);
x_grid_desc_m_k_ = x_grid_desc_m_k_ =
MakeSrc2dDescriptor(Lengths_, xStrides_, kGridSize_, numBlockTileIteration_); MakeSrc2dDescriptor(Lengths_, xStrides_, kGridSize_, numBlockTileIteration_);
...@@ -260,9 +343,17 @@ struct DeviceNormalizationSplitKImpl : public DeviceNormalization<XDataType, ...@@ -260,9 +343,17 @@ struct DeviceNormalizationSplitKImpl : public DeviceNormalization<XDataType,
MakeSrc2dDescriptor(Lengths_, yStrides_, kGridSize_, numBlockTileIteration_); MakeSrc2dDescriptor(Lengths_, yStrides_, kGridSize_, numBlockTileIteration_);
// We don't need to pad in K dimension for Welford1. Set KPerTile 1. // We don't need to pad in K dimension for Welford1. Set KPerTile 1.
mean_var_grid_desc_m_kblock_ = kernel1_mean_var_grid_desc_m_kblock_ =
MakeMeanVarDescriptor_M_K<Sequence<true, false>, M_BlockTileSize, 1>(MRaw_, MakeMeanVarDescriptor_M_K<Sequence<true, false>, M_BlockTileSize, 1>(MRaw_,
kGridSize_); kGridSize_);
kernel2_mean_var_grid_desc_m_kblock_ =
MakeMeanVarDescriptor_M_K<Sequence<true, true>, M_BlockTileSize, K_BlockTileSize>(
MRaw_, kGridSize_);
kernel2_count_grid_desc_m_kblock_ =
MakeCountDescriptor_M_K<Sequence<true, true>, M_BlockTileSize, K_BlockTileSize>(
MRaw_, kGridSize_);
} }
ComputeDataType epsilon_; ComputeDataType epsilon_;
...@@ -284,6 +375,7 @@ struct DeviceNormalizationSplitKImpl : public DeviceNormalization<XDataType, ...@@ -284,6 +375,7 @@ struct DeviceNormalizationSplitKImpl : public DeviceNormalization<XDataType,
YElementwiseOperation y_elementwise_op_; YElementwiseOperation y_elementwise_op_;
int kGridSize_; int kGridSize_;
int numMeanVarCountIteration_;
int numBlockTileIteration_; int numBlockTileIteration_;
size_t gridSize_; size_t gridSize_;
...@@ -292,7 +384,9 @@ struct DeviceNormalizationSplitKImpl : public DeviceNormalization<XDataType, ...@@ -292,7 +384,9 @@ struct DeviceNormalizationSplitKImpl : public DeviceNormalization<XDataType,
SrcGridDesc_M_K beta_grid_desc_m_k_; SrcGridDesc_M_K beta_grid_desc_m_k_;
SrcGridDesc_M_K y_grid_desc_m_k_; SrcGridDesc_M_K y_grid_desc_m_k_;
Welford1MeanVarGridDesc_M_KBlock mean_var_grid_desc_m_kblock_; Kernel1MeanVarGridDesc_M_KBlock kernel1_mean_var_grid_desc_m_kblock_;
Kernel2MeanVarGridDesc_M_KBlock kernel2_mean_var_grid_desc_m_kblock_;
Kernel2CountGridDesc_M_KBlock kernel2_count_grid_desc_m_kblock_;
index_t MRaw_; // invarient length index_t MRaw_; // invarient length
index_t KRaw_; // reduce length index_t KRaw_; // reduce length
...@@ -306,12 +400,24 @@ struct DeviceNormalizationSplitKImpl : public DeviceNormalization<XDataType, ...@@ -306,12 +400,24 @@ struct DeviceNormalizationSplitKImpl : public DeviceNormalization<XDataType,
arg.p_workspace_count_ == nullptr) arg.p_workspace_count_ == nullptr)
throw std::runtime_error("wrong! WorkSpace pointer has not been set"); throw std::runtime_error("wrong! WorkSpace pointer has not been set");
auto kernel1 = kernel_normalizationSplitK1st<GridwiseWelford1, auto kernel1 = kernel_normalizationSplitK1st<GridwiseWelford,
XDataType, XDataType,
MeanVarDataType, MeanVarDataType,
ComputeDataType, ComputeDataType,
SrcGridDesc_M_K, SrcGridDesc_M_K,
Welford1MeanVarGridDesc_M_KBlock>; Kernel1MeanVarGridDesc_M_KBlock>;
auto kernel2 = kernel_normalizationSplitK2nd<GridwiseWelfordNormalization,
MeanVarDataType,
XDataType,
GammaDataType,
BetaDataType,
YDataType,
ComputeDataType,
YElementwiseOperation,
Kernel2MeanVarGridDesc_M_KBlock,
Kernel2CountGridDesc_M_KBlock,
SrcGridDesc_M_K>;
float avg_time = 0; float avg_time = 0;
avg_time += launch_and_time_kernel(stream_config, avg_time += launch_and_time_kernel(stream_config,
...@@ -320,16 +426,38 @@ struct DeviceNormalizationSplitKImpl : public DeviceNormalization<XDataType, ...@@ -320,16 +426,38 @@ struct DeviceNormalizationSplitKImpl : public DeviceNormalization<XDataType,
dim3(BlockSize), dim3(BlockSize),
0, 0,
arg.x_grid_desc_m_k_, arg.x_grid_desc_m_k_,
arg.mean_var_grid_desc_m_kblock_, arg.kernel1_mean_var_grid_desc_m_kblock_,
arg.numBlockTileIteration_, arg.numBlockTileIteration_,
arg.p_x_, arg.p_x_,
static_cast<MeanVarDataType*>(arg.p_workspace_mean_), static_cast<MeanVarDataType*>(arg.p_workspace_mean_),
static_cast<MeanVarDataType*>(arg.p_workspace_var_), static_cast<MeanVarDataType*>(arg.p_workspace_var_),
static_cast<int32_t*>(arg.p_workspace_count_)); static_cast<int32_t*>(arg.p_workspace_count_));
// TODO - welford2 + elementwise avg_time += launch_and_time_kernel(stream_config,
kernel2,
dim3(arg.gridSize_),
dim3(BlockSize),
0,
arg.kernel2_mean_var_grid_desc_m_kblock_,
arg.kernel2_count_grid_desc_m_kblock_,
arg.x_grid_desc_m_k_,
arg.gamma_grid_desc_m_k_,
arg.beta_grid_desc_m_k_,
arg.y_grid_desc_m_k_,
arg.numMeanVarCountIteration_,
arg.numBlockTileIteration_,
arg.kGridSize_,
arg.epsilon_,
static_cast<MeanVarDataType*>(arg.p_workspace_mean_),
static_cast<MeanVarDataType*>(arg.p_workspace_var_),
static_cast<int32_t*>(arg.p_workspace_count_),
arg.p_x_,
arg.p_gamma_,
arg.p_beta_,
arg.p_y_,
arg.y_elementwise_op_);
return (avg_time); return avg_time;
}; };
float Run(const BaseArgument* p_arg, float Run(const BaseArgument* p_arg,
...@@ -390,7 +518,7 @@ struct DeviceNormalizationSplitKImpl : public DeviceNormalization<XDataType, ...@@ -390,7 +518,7 @@ struct DeviceNormalizationSplitKImpl : public DeviceNormalization<XDataType,
constexpr index_t NumInvariantDim = Rank - NumReduceDim; constexpr index_t NumInvariantDim = Rank - NumReduceDim;
if constexpr(XYSrcVectorDim == 0) if constexpr(XYVectorDim == 0)
{ {
if constexpr(NumInvariantDim == 0) if constexpr(NumInvariantDim == 0)
{ {
...@@ -423,38 +551,41 @@ struct DeviceNormalizationSplitKImpl : public DeviceNormalization<XDataType, ...@@ -423,38 +551,41 @@ struct DeviceNormalizationSplitKImpl : public DeviceNormalization<XDataType,
if constexpr(GammaSrcVectorDim == 0) if constexpr(GammaSrcVectorDim == 0)
{ {
if(p_arg_->gammaStrides_[NumInvariantDim - 1] != 1) if(p_arg_->gammaStrides_[NumInvariantDim - 1] != 1)
return (false); return false;
if(p_arg_->Lengths_[Rank - 1] % GammaSrcVectorSize != 0) if(p_arg_->Lengths_[Rank - 1] % GammaSrcVectorSize != 0)
return (false); return false;
} }
else // if fastest dim is reduced else // if fastest dim is reduced
{ {
if(p_arg_->gammaStrides_[Rank - 1] != 1) if(p_arg_->gammaStrides_[Rank - 1] != 1)
return (false); return false;
if(p_arg_->Lengths_[Rank - 1] % GammaSrcVectorSize != 0) if(p_arg_->Lengths_[Rank - 1] % GammaSrcVectorSize != 0)
return (false); return false;
} }
// if fastest dim is not reduced // if fastest dim is not reduced
if constexpr(BetaSrcVectorDim == 0) if constexpr(BetaSrcVectorDim == 0)
{ {
if(p_arg_->betaStrides_[NumInvariantDim - 1] != 1) if(p_arg_->betaStrides_[NumInvariantDim - 1] != 1)
return (false); return false;
if(p_arg_->invariant_lowest_length % BetaSrcVectorSize != 0) if(p_arg_->invariant_lowest_length % BetaSrcVectorSize != 0)
return (false); return false;
} }
else // if fastest dim is reduced else // if fastest dim is reduced
{ {
if(p_arg_->betaStrides_[Rank - 1] != 1) if(p_arg_->betaStrides_[Rank - 1] != 1)
return (false); return false;
if(p_arg_->Lengths_[Rank - 1] % BetaSrcVectorSize != 0) if(p_arg_->Lengths_[Rank - 1] % BetaSrcVectorSize != 0)
return (false); return false;
} }
if(p_arg_->kGridSize_ <= 1)
return false;
return true; return true;
}; };
...@@ -507,7 +638,7 @@ struct DeviceNormalizationSplitKImpl : public DeviceNormalization<XDataType, ...@@ -507,7 +638,7 @@ struct DeviceNormalizationSplitKImpl : public DeviceNormalization<XDataType,
str << "DeviceNormalizationImpl<" << BlockSize << ","; str << "DeviceNormalizationImpl<" << BlockSize << ",";
str << "Cluster_MK_" << MThreadClusterSize << "_" << KThreadClusterSize << ","; str << "Cluster_MK_" << MThreadClusterSize << "_" << KThreadClusterSize << ",";
str << "Slice_MK_" << MThreadSliceSize << "_" << KThreadSliceSize << ","; str << "Slice_MK_" << MThreadSliceSize << "_" << KThreadSliceSize << ",";
str << "XYSrcVectorDim_" << XYSrcVectorDim << ","; str << "XYSrcVectorDim_" << XYVectorDim << ",";
str << "VectorSize_X" << XSrcVectorSize << "_Gamma" << GammaSrcVectorSize << "_Beta" << BetaSrcVectorSize << "_Y" << YDstVectorSize << ">"; str << "VectorSize_X" << XSrcVectorSize << "_Gamma" << GammaSrcVectorSize << "_Beta" << BetaSrcVectorSize << "_Y" << YDstVectorSize << ">";
// clang-format on // clang-format on
......
include/ck/tensor_operation/gpu/grid/normalization/gridwise_normalization_splitk_1st.hpp
View file @ 56532f77
...@@ -203,7 +203,7 @@ struct GridwiseNormalizationSplitK1st ...@@ -203,7 +203,7 @@ struct GridwiseNormalizationSplitK1st
var_thread_buf(I) = type_convert<ComputeDataType>(0.0f); var_thread_buf(I) = type_convert<ComputeDataType>(0.0f);
}); });
for(index_t reducedTiles = 0; reducedTiles < num_k_block_tile_iteration; ++reducedTiles) for(index_t k = 0; k < num_k_block_tile_iteration; ++k)
{ {
static_for<0, ThreadBufferNumber, 1>{}([&](auto i) { static_for<0, ThreadBufferNumber, 1>{}([&](auto i) {
threadwise_x_load.Run(x_grid_desc_m_k, threadwise_x_load.Run(x_grid_desc_m_k,
......
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