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Commit 6e3cf8b0 authored by Jing Zhang's avatar Jing Zhang
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merge develop

parents 4ad62d7f ba58a93f
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Showing with 2018 additions and 617 deletions
include/ck/options.hpp 0 → 100644
View file @ 6e3cf8b0
#pragma once
#define CK_TIME_KERNEL 1
include/ck/stream_config.hpp 0 → 100644
View file @ 6e3cf8b0
#pragma once
#include <hip/hip_runtime.h>
#include <hip/hip_fp16.h>
struct StreamConfig
{
hipStream_t stream_id_ = nullptr;
bool time_kernel_ = false;
};
include/ck/tensor_operation/gpu/device/convolution_backward_weight_specialization.hpp 0 → 100644
View file @ 6e3cf8b0
#pragma once
namespace ck {
namespace tensor_operation {
namespace device {
enum struct ConvolutionBackwardWeightSpecialization
{
Default,
Filter1x1Stride1Pad0,
Filter1x1Pad0,
OddC,
};
} // namespace device
} // namespace tensor_operation
} // namespace ck
include/ck/tensor_operation/gpu/device/device_base.hpp
View file @ 6e3cf8b0
#ifndef DEVICE_BASE_HPP
#define DEVICE_BASE_HPP
#pragma once
#include <string>
#include "stream_config.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
......@@ -22,7 +23,10 @@ struct BaseInvoker
BaseInvoker(const BaseInvoker&) = default;
BaseInvoker& operator=(const BaseInvoker&) = default;
virtual float Run(const BaseArgument*, int = 1) = 0;
virtual float Run(const BaseArgument*, const StreamConfig& = StreamConfig{})
{
return float{0};
}
virtual ~BaseInvoker() {}
};
......@@ -33,8 +37,8 @@ struct BaseOperator
BaseOperator(const BaseOperator&) = default;
BaseOperator& operator=(const BaseOperator&) = default;
virtual bool IsSupportedArgument(const BaseArgument*) = 0;
virtual std::string GetTypeString() const = 0;
virtual bool IsSupportedArgument(const BaseArgument*) { return false; }
virtual std::string GetTypeString() const { return ""; }
virtual ~BaseOperator() {}
};
......@@ -42,4 +46,3 @@ struct BaseOperator
} // namespace device
} // namespace tensor_operation
} // namespace ck
#endif
include/ck/tensor_operation/gpu/device/device_batched_gemm_xdl.hpp
View file @ 6e3cf8b0
......@@ -243,44 +243,6 @@ struct DeviceBatchedGemmXdl
using BGridDesc_K0_N_K1 = decltype(MakeBGridDescriptor_K0_N_K1(1, 1, 1));
using CGridDesc_M_N = decltype(MakeCGridDescriptor_M_N(1, 1, 1));
static constexpr auto MakeBlock2CTileMap(index_t batch_count,
const CGridDesc_M_N& c_grid_desc_m_n,
index_t M01,
index_t N01)
{
const auto M = c_grid_desc_m_n.GetLength(I0);
const auto N = c_grid_desc_m_n.GetLength(I1);
constexpr auto M1 = Number<MPerBlock>{};
constexpr auto N1 = Number<NPerBlock>{};
const auto M0 = M / M1;
const auto N0 = N / N1;
const auto M00 = M0 / M01;
const auto N00 = N0 / N01;
const auto g_m00_m01_n00_n01_to_m0_n0_block_cluster_adaptor =
make_single_stage_tensor_adaptor(
make_tuple(make_insert_transform(batch_count),
make_unmerge_transform(make_tuple(M00, M01)),
make_unmerge_transform(make_tuple(N00, N01))),
make_tuple(Sequence<>{}, Sequence<0>{}, Sequence<1>{}),
make_tuple(Sequence<0>{}, Sequence<1, 3>{}, Sequence<2, 4>{}));
const auto globalblockid_to_m00_m01_n00_n01_block_cluster_adaptor =
make_single_stage_tensor_adaptor(
make_tuple(make_merge_transform(make_tuple(batch_count, M00, N00, M01, N01))),
make_tuple(Sequence<0, 1, 2, 3, 4>{}),
make_tuple(Sequence<0>{}));
const auto globalblockid_to_m0_n0_block_cluster_adaptor =
chain_tensor_adaptors(g_m00_m01_n00_n01_to_m0_n0_block_cluster_adaptor,
globalblockid_to_m00_m01_n00_n01_block_cluster_adaptor);
return globalblockid_to_m0_n0_block_cluster_adaptor;
}
struct ComputePtrOffsetOfStridedBatch
{
ComputePtrOffsetOfStridedBatch(index_t BatchStrideA,
......@@ -354,7 +316,7 @@ struct DeviceBatchedGemmXdl
using CGridDesc_M0_N0_M1_N1_M2_M3_M4_N2 =
decltype(GridwiseGemm::MakeCGridDescriptor_M0_N0_M1_N1_M2_M3_M4_N2(CGridDesc_M_N{}));
using Block2CTileMap = decltype(MakeBlock2CTileMap(1, CGridDesc_M_N{}, 1, 1));
using Block2CTileMap = typename GridwiseGemm::DefaultBlock2CTileMap;
// Argument
struct Argument : public BaseArgument
......@@ -388,20 +350,21 @@ struct DeviceBatchedGemmXdl
type_convert<index_t>(a_grid_desc_k0_m_k1_.GetElementSpaceSize()),
type_convert<index_t>(b_grid_desc_k0_n_k1_.GetElementSpaceSize()),
type_convert<index_t>(c_grid_desc_m_n_.GetElementSpaceSize())},
block_2_ctile_map_{},
block_2_ctile_map_{
GridwiseGemm::MakeDefaultBlock2CTileMap(c_grid_desc_m_n_, M01, N01)},
M01_{M01},
N01_{N01},
a_element_op_{a_element_op},
b_element_op_{b_element_op},
c_element_op_{c_element_op}
{
if(GridwiseGemm::CheckValidity(
a_grid_desc_k0_m_k1_, b_grid_desc_k0_n_k1_, c_grid_desc_m_n_, M01_, N01_))
if(GridwiseGemm::CheckValidity(a_grid_desc_k0_m_k1_,
b_grid_desc_k0_n_k1_,
c_grid_desc_m_n_,
block_2_ctile_map_))
{
c_grid_desc_m0_n0_m1_n1_m2_m3_m4_n2_ =
GridwiseGemm::MakeCGridDescriptor_M0_N0_M1_N1_M2_M3_M4_N2(c_grid_desc_m_n_);
block_2_ctile_map_ = MakeBlock2CTileMap(BatchCount, c_grid_desc_m_n_, M01, N01);
}
}
......@@ -428,7 +391,7 @@ struct DeviceBatchedGemmXdl
{
using Argument = DeviceBatchedGemmXdl::Argument;
float Run(const Argument& arg, int nrepeat = 1)
float Run(const Argument& arg, const StreamConfig& stream_config = StreamConfig{})
{
{
std::cout << "arg.a_grid_desc_k0_m_k1_{" << arg.a_grid_desc_k0_m_k1_.GetLength(I0)
......@@ -446,15 +409,14 @@ struct DeviceBatchedGemmXdl
if(!GridwiseGemm::CheckValidity(arg.a_grid_desc_k0_m_k1_,
arg.b_grid_desc_k0_n_k1_,
arg.c_grid_desc_m_n_,
arg.M01_,
arg.N01_))
arg.block_2_ctile_map_))
{
throw std::runtime_error(
"wrong! GridwiseBatchedGemm_km_kn_m0m1n0n1_xdlops_v2r3 has invalid setting");
}
const index_t grid_size =
GridwiseGemm::CalculateGridSize(arg.c_grid_desc_m_n_) * arg.BatchCount_;
arg.block_2_ctile_map_.CalculateGridSize(arg.c_grid_desc_m_n_) * arg.BatchCount_;
const auto K =
arg.a_grid_desc_k0_m_k1_.GetLength(I0) * arg.a_grid_desc_k0_m_k1_.GetLength(I2);
......@@ -477,8 +439,8 @@ struct DeviceBatchedGemmXdl
remove_reference_t<Block2CTileMap>,
true>;
ave_time = launch_and_time_kernel(kernel,
nrepeat,
ave_time = launch_and_time_kernel(stream_config,
kernel,
dim3(grid_size),
dim3(BlockSize),
0,
......@@ -511,8 +473,8 @@ struct DeviceBatchedGemmXdl
remove_reference_t<Block2CTileMap>,
false>;
ave_time = launch_and_time_kernel(kernel,
nrepeat,
ave_time = launch_and_time_kernel(stream_config,
kernel,
dim3(grid_size),
dim3(BlockSize),
0,
......@@ -534,9 +496,10 @@ struct DeviceBatchedGemmXdl
}
// polymorphic
float Run(const BaseArgument* p_arg, int nrepeat = 1) override
float Run(const BaseArgument* p_arg,
const StreamConfig& stream_config = StreamConfig{}) override
{
return Run(*dynamic_cast<const Argument*>(p_arg), nrepeat);
return Run(*dynamic_cast<const Argument*>(p_arg), stream_config);
}
};
......@@ -551,8 +514,7 @@ struct DeviceBatchedGemmXdl
return GridwiseGemm::CheckValidity(arg.a_grid_desc_k0_m_k1_,
arg.b_grid_desc_k0_n_k1_,
arg.c_grid_desc_m_n_,
arg.M01_,
arg.N01_);
arg.block_2_ctile_map_);
}
// polymorphic
......
include/ck/tensor_operation/gpu/device/device_binary_elementwise.hpp 0 → 100644
View file @ 6e3cf8b0
#pragma once
#include <iostream>
#include <vector>
#include "device.hpp"
#include "device_base.hpp"
#include "gridwise_binary_elementwise_1d.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
template <typename ADataType,
typename BDataType,
typename CDataType,
typename ComputeDataType,
typename ElementwiseFunctor,
index_t Dim,
index_t ScalarPerVector>
struct DeviceBinaryElementwise : public BaseOperator
{
static constexpr auto I0 = Number<0>{};
template <typename Desc_M0>
static auto PadDescriptor_M0_1d(Desc_M0 desc_m0, index_t gridSize, index_t blockSize)
{
const auto m0 = desc_m0.GetLength(I0);
const index_t loop_step = gridSize * blockSize * ScalarPerVector;
const auto pad = math::integer_least_multiple(m0, loop_step) - m0;
const auto desc_m0_pad =
transform_tensor_descriptor(desc_m0,
make_tuple(make_right_pad_transform(m0, pad)),
make_tuple(Sequence<0>{}),
make_tuple(Sequence<0>{}));
return desc_m0_pad;
}
static auto MakeDescriptor_M0(const std::vector<index_t>& shape,
const std::vector<index_t>& stride,
index_t gridSize,
index_t blockSize)
{
auto tupleOfShape = generate_tuple([&](auto I) { return shape[I]; }, Number<Dim>{});
auto tupleOfStride = generate_tuple([&](auto I) { return stride[I]; }, Number<Dim>{});
// nd desc - [s0, s1, s2, ...]
const auto desc = make_naive_tensor_descriptor(tupleOfShape, tupleOfStride);
// merge nd to 1d desc - [s0 * s1 * ...]
if constexpr(Dim > 1)
{
const auto desc_m0 = transform_tensor_descriptor(
desc,
make_tuple(make_merge_transform(tupleOfShape)),
make_tuple(generate_sequence_v2([&](auto I) { return I; }, Number<Dim>{})),
make_tuple(Sequence<0>{}));
return PadDescriptor_M0_1d(desc_m0, gridSize, blockSize);
}
else
return PadDescriptor_M0_1d(desc, gridSize, blockSize);
}
using GridDesc_M0 = decltype(MakeDescriptor_M0({1, 1}, {1, 1}, 1, 1));
using GridwiseBinEltwise = GridwiseBinaryElementwise_1D<ADataType,
BDataType,
CDataType,
ComputeDataType,
GridDesc_M0,
ElementwiseFunctor,
ScalarPerVector>;
struct Argument : public BaseArgument
{
Argument(const ADataType* p_a,
const BDataType* p_b,
CDataType* p_c,
const std::vector<index_t>& shape,
const std::vector<index_t>& stride_a,
const std::vector<index_t>& stride_b,
const std::vector<index_t>& stride_c,
ElementwiseFunctor functor)
: p_a_(p_a),
p_b_(p_b),
p_c_(p_c),
shape_(shape),
functor_(functor),
blockSize_(256),
gridSize_(120) // FIXME - Calculate the grid size by number of CU in the future
{
a_grid_desc_m0_ = MakeDescriptor_M0(shape, stride_a, gridSize_, blockSize_);
b_grid_desc_m0_ = MakeDescriptor_M0(shape, stride_b, gridSize_, blockSize_);
c_grid_desc_m0_ = MakeDescriptor_M0(shape, stride_c, gridSize_, blockSize_);
}
const ADataType* p_a_;
const BDataType* p_b_;
CDataType* p_c_;
std::vector<int> shape_;
GridDesc_M0 a_grid_desc_m0_;
GridDesc_M0 b_grid_desc_m0_;
GridDesc_M0 c_grid_desc_m0_;
ElementwiseFunctor functor_;
index_t blockSize_;
index_t gridSize_;
};
struct Invoker : public BaseInvoker
{
float Run(const Argument& arg, const StreamConfig& stream_config = StreamConfig{})
{
const auto kernel = kernel_binary_elementwise_1d<GridwiseBinEltwise,
ADataType,
BDataType,
CDataType,
GridDesc_M0,
ElementwiseFunctor>;
float elapsed_time = launch_and_time_kernel(stream_config,
kernel,
dim3(arg.gridSize_),
dim3(arg.blockSize_),
0,
arg.p_a_,
arg.p_b_,
arg.p_c_,
arg.a_grid_desc_m0_,
arg.b_grid_desc_m0_,
arg.c_grid_desc_m0_,
arg.functor_);
return elapsed_time;
}
// polymorphic
float Run(const BaseArgument* p_arg,
const StreamConfig& stream_config = StreamConfig{}) override
{
return Run(*dynamic_cast<const Argument*>(p_arg), stream_config);
}
};
bool IsSupportedArgument(const BaseArgument* p_arg) override
{
const Argument* pArg = dynamic_cast<const Argument*>(p_arg);
if(pArg == nullptr)
return false;
if(pArg->shape_.back() % ScalarPerVector != 0)
return false;
return true;
};
std::unique_ptr<BaseArgument> MakeArgumentPointer(const void* p_a,
const void* p_b,
void* p_c,
std::vector<index_t> shape,
std::vector<index_t> stride_a,
std::vector<index_t> stride_b,
std::vector<index_t> stride_c,
ElementwiseFunctor functor)
{
return std::make_unique<Argument>(static_cast<const ADataType*>(p_a),
static_cast<const BDataType*>(p_b),
static_cast<CDataType*>(p_c),
shape,
stride_a,
stride_b,
stride_c,
functor);
}
std::unique_ptr<BaseInvoker> MakeInvokerPointer() { return std::make_unique<Invoker>(); }
std::string GetTypeString() const override
{
auto str = std::stringstream();
// clang-format off
str << "DeviceBinaryElementwise"
<< "<"
<< "ScalarPerVector = " << ScalarPerVector
<< ">";
// clang-format on
return str.str();
}
};
} // namespace device
} // namespace tensor_operation
} // namespace ck
include/ck/tensor_operation/gpu/device/device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk.hpp
View file @ 6e3cf8b0
......@@ -486,13 +486,16 @@ struct DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K
b_grid_desc_k0_n_k1_container_.push_back(descs[I1]);
c_grid_desc_m_n_container_.push_back(descs[I2]);
if(GridwiseGemm::CheckValidity(descs[I0], descs[I1], descs[I2], M01_, N01_))
auto block_2_ctile_map =
GridwiseGemm::MakeDefaultBlock2CTileMap(descs[I2], M01, N01);
if(GridwiseGemm::CheckValidity(
descs[I0], descs[I1], descs[I2], block_2_ctile_map))
{
c_grid_desc_m0_n0_m1_n1_m2_m3_m4_n2_container_.push_back(
GridwiseGemm::MakeCGridDescriptor_M0_N0_M1_N1_M2_M3_M4_N2(descs[I2]));
block_2_ctile_map_container_.push_back(
GridwiseGemm::MakeDefaultBlock2CTileMap(descs[I2], M01, N01));
block_2_ctile_map_container_.push_back(block_2_ctile_map);
}
}
}
......@@ -531,7 +534,7 @@ struct DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K
{
using Argument = DeviceOp::Argument;
float Run(const Argument& arg, int nrepeat = 1)
float Run(const Argument& arg, const StreamConfig& stream_config = StreamConfig{})
{
float ave_time = 0;
for(size_t i = 0; i < arg.a_grid_desc_k0_m_k1_container_.size(); i++)
......@@ -572,15 +575,14 @@ struct DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K
if(!GridwiseGemm::CheckValidity(arg.a_grid_desc_k0_m_k1_container_[i],
arg.b_grid_desc_k0_n_k1_container_[i],
arg.c_grid_desc_m_n_container_[i],
arg.M01_,
arg.N01_))
arg.block_2_ctile_map_container_[i]))
{
throw std::runtime_error(
"wrong! GridwiseGemm_km_kn_m0m1n0n1_xdlops_v3r1 has invalid setting");
}
const index_t grid_size =
GridwiseGemm::CalculateGridSize(arg.c_grid_desc_m_n_container_[i]);
const index_t grid_size = arg.block_2_ctile_map_container_[i].CalculateGridSize(
arg.c_grid_desc_m_n_container_[i]);
const auto K = arg.a_grid_desc_k0_m_k1_container_[i].GetLength(I0) *
arg.a_grid_desc_k0_m_k1_container_[i].GetLength(I2);
......@@ -602,8 +604,8 @@ struct DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K
true>;
ave_time += launch_and_time_kernel(
stream_config,
kernel,
nrepeat,
dim3(grid_size),
dim3(BlockSize),
0,
......@@ -635,8 +637,8 @@ struct DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K
false>;
ave_time += launch_and_time_kernel(
stream_config,
kernel,
nrepeat,
dim3(grid_size),
dim3(BlockSize),
0,
......@@ -655,9 +657,10 @@ struct DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K
return ave_time;
}
float Run(const BaseArgument* p_arg, int nrepeat = 1) override
float Run(const BaseArgument* p_arg,
const StreamConfig& stream_config = StreamConfig{}) override
{
return Run(*dynamic_cast<const Argument*>(p_arg), nrepeat);
return Run(*dynamic_cast<const Argument*>(p_arg), stream_config);
}
};
......@@ -702,8 +705,7 @@ struct DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K
if(!GridwiseGemm::CheckValidity(arg.a_grid_desc_k0_m_k1_container_[i],
arg.b_grid_desc_k0_n_k1_container_[i],
arg.c_grid_desc_m_n_container_[i],
arg.M01_,
arg.N01_))
arg.block_2_ctile_map_container_[i]))
{
return false;
}
......
include/ck/tensor_operation/gpu/device/device_conv2d_fwd_xdl_c_shuffle_bias_activation_add_nhwc_kyxc_nhwk.hpp
View file @ 6e3cf8b0
......@@ -540,7 +540,8 @@ struct
c_grid_desc_mblock_mxdlperwave_mwavemperxdl_nblock_nxdlperwave_nwavenperxdl_{},
c0_grid_desc_mblock_mxdlperwave_mwavemperxdl_nblock_nxdlperwave_nwavenperxdl_{},
c1_grid_desc_mblock_mxdlperwave_mwavemperxdl_nblock_nxdlperwave_nwavenperxdl_{},
block_2_ctile_map_{},
block_2_ctile_map_{
GridwiseGemm::MakeDefaultBlock2CTileMap(c_grid_desc_m_n_, M01, N01)},
M01_{M01},
N01_{N01},
in_element_op_{in_element_op},
......@@ -575,8 +576,10 @@ struct
c0_grid_desc_m_n_ = descs[I3];
c1_grid_desc_m_n_ = descs[I4];
if(GridwiseGemm::CheckValidity(
a_grid_desc_k0_m_k1_, b_grid_desc_k0_n_k1_, c_grid_desc_m_n_, M01_, N01_))
if(GridwiseGemm::CheckValidity(a_grid_desc_k0_m_k1_,
b_grid_desc_k0_n_k1_,
c_grid_desc_m_n_,
block_2_ctile_map_))
{
c_grid_desc_mblock_mxdlperwave_mwavemperxdl_nblock_nxdlperwave_nwavenperxdl_ =
GridwiseGemm::
......@@ -592,9 +595,6 @@ struct
GridwiseGemm::
MakeCGridDescriptor_MBlock_MXdlPerWave_MWaveMPerXdl_NBlock_NXdlPerWave_NWaveNPerXdl(
c1_grid_desc_m_n_);
block_2_ctile_map_ =
GridwiseGemm::MakeDefaultBlock2CTileMap(c_grid_desc_m_n_, M01, N01);
}
}
......@@ -642,7 +642,7 @@ struct
{
using Argument = DeviceOp::Argument;
float Run(const Argument& arg, int nrepeat = 1)
float Run(const Argument& arg, const StreamConfig& stream_config = StreamConfig{})
{
#if 0
{
......@@ -689,14 +689,14 @@ struct
if(!GridwiseGemm::CheckValidity(arg.a_grid_desc_k0_m_k1_,
arg.b_grid_desc_k0_n_k1_,
arg.c_grid_desc_m_n_,
arg.M01_,
arg.N01_))
arg.block_2_ctile_map_))
{
throw std::runtime_error(
"wrong! GridwiseGemm_km_kn_m0m1n0n1_xdlops_v3r3 has invalid setting");
}
const index_t grid_size = GridwiseGemm::CalculateGridSize(arg.c_grid_desc_m_n_);
const index_t grid_size =
arg.block_2_ctile_map_.CalculateGridSize(arg.c_grid_desc_m_n_);
const auto K =
arg.a_grid_desc_k0_m_k1_.GetLength(I0) * arg.a_grid_desc_k0_m_k1_.GetLength(I2);
......@@ -727,8 +727,8 @@ struct
true>;
ave_time = launch_and_time_kernel(
stream_config,
kernel,
nrepeat,
dim3(grid_size),
dim3(BlockSize),
0,
......@@ -771,8 +771,8 @@ struct
false>;
ave_time = launch_and_time_kernel(
stream_config,
kernel,
nrepeat,
dim3(grid_size),
dim3(BlockSize),
0,
......@@ -795,9 +795,10 @@ struct
return ave_time;
}
float Run(const BaseArgument* p_arg, int nrepeat = 1) override
float Run(const BaseArgument* p_arg,
const StreamConfig& stream_config = StreamConfig{}) override
{
return Run(*dynamic_cast<const Argument*>(p_arg), nrepeat);
return Run(*dynamic_cast<const Argument*>(p_arg), stream_config);
}
};
......@@ -851,8 +852,7 @@ struct
return GridwiseGemm::CheckValidity(arg.a_grid_desc_k0_m_k1_,
arg.b_grid_desc_k0_n_k1_,
arg.c_grid_desc_m_n_,
arg.M01_,
arg.N01_);
arg.block_2_ctile_map_);
}
bool IsSupportedArgument(const BaseArgument* p_arg) override
......
include/ck/tensor_operation/gpu/device/device_conv2d_fwd_xdl_c_shuffle_bias_activation_nhwc_kyxc_nhwk.hpp
View file @ 6e3cf8b0
......@@ -548,9 +548,13 @@ struct DeviceConv2dFwdXdl_C_Shuffle_Bias_Activation_Input_N_Hi_Wi_C_Weight_K_Y_X
b_grid_desc_k0_n_k1_ = descs[I1];
c_grid_desc_m_n_ = descs[I2];
c0_grid_desc_m_n_ = descs[I3];
block_2_ctile_map_ =
GridwiseGemm::MakeDefaultBlock2CTileMap(c_grid_desc_m_n_, M01, N01);
if(GridwiseGemm::CheckValidity(
a_grid_desc_k0_m_k1_, b_grid_desc_k0_n_k1_, c_grid_desc_m_n_, M01_, N01_))
if(GridwiseGemm::CheckValidity(a_grid_desc_k0_m_k1_,
b_grid_desc_k0_n_k1_,
c_grid_desc_m_n_,
block_2_ctile_map_))
{
c_grid_desc_mblock_mxdlperwave_mwavemperxdl_nblock_nxdlperwave_nwavenperxdl_ =
GridwiseGemm::
......@@ -561,9 +565,6 @@ struct DeviceConv2dFwdXdl_C_Shuffle_Bias_Activation_Input_N_Hi_Wi_C_Weight_K_Y_X
GridwiseGemm::
MakeCGridDescriptor_MBlock_MXdlPerWave_MWaveMPerXdl_NBlock_NXdlPerWave_NWaveNPerXdl(
c0_grid_desc_m_n_);
block_2_ctile_map_ =
GridwiseGemm::MakeDefaultBlock2CTileMap(c_grid_desc_m_n_, M01, N01);
}
}
......@@ -605,7 +606,7 @@ struct DeviceConv2dFwdXdl_C_Shuffle_Bias_Activation_Input_N_Hi_Wi_C_Weight_K_Y_X
{
using Argument = DeviceOp::Argument;
float Run(const Argument& arg, int nrepeat = 1)
float Run(const Argument& arg, const StreamConfig& stream_config = StreamConfig{})
{
#if 0
{
......@@ -649,14 +650,14 @@ struct DeviceConv2dFwdXdl_C_Shuffle_Bias_Activation_Input_N_Hi_Wi_C_Weight_K_Y_X
if(!GridwiseGemm::CheckValidity(arg.a_grid_desc_k0_m_k1_,
arg.b_grid_desc_k0_n_k1_,
arg.c_grid_desc_m_n_,
arg.M01_,
arg.N01_))
arg.block_2_ctile_map_))
{
throw std::runtime_error(
"wrong! GridwiseGemm_km_kn_m0m1n0n1_xdlops_v3r2 has invalid setting");
}
const index_t grid_size = GridwiseGemm::CalculateGridSize(arg.c_grid_desc_m_n_);
const index_t grid_size =
arg.block_2_ctile_map_.CalculateGridSize(arg.c_grid_desc_m_n_);
const auto K =
arg.a_grid_desc_k0_m_k1_.GetLength(I0) * arg.a_grid_desc_k0_m_k1_.GetLength(I2);
......@@ -684,8 +685,8 @@ struct DeviceConv2dFwdXdl_C_Shuffle_Bias_Activation_Input_N_Hi_Wi_C_Weight_K_Y_X
true>;
ave_time = launch_and_time_kernel(
stream_config,
kernel,
nrepeat,
dim3(grid_size),
dim3(BlockSize),
0,
......@@ -723,8 +724,8 @@ struct DeviceConv2dFwdXdl_C_Shuffle_Bias_Activation_Input_N_Hi_Wi_C_Weight_K_Y_X
false>;
ave_time = launch_and_time_kernel(
stream_config,
kernel,
nrepeat,
dim3(grid_size),
dim3(BlockSize),
0,
......@@ -745,9 +746,10 @@ struct DeviceConv2dFwdXdl_C_Shuffle_Bias_Activation_Input_N_Hi_Wi_C_Weight_K_Y_X
return ave_time;
}
float Run(const BaseArgument* p_arg, int nrepeat = 1) override
float Run(const BaseArgument* p_arg,
const StreamConfig& stream_config = StreamConfig{}) override
{
return Run(*dynamic_cast<const Argument*>(p_arg), nrepeat);
return Run(*dynamic_cast<const Argument*>(p_arg), stream_config);
}
};
......@@ -801,8 +803,7 @@ struct DeviceConv2dFwdXdl_C_Shuffle_Bias_Activation_Input_N_Hi_Wi_C_Weight_K_Y_X
return GridwiseGemm::CheckValidity(arg.a_grid_desc_k0_m_k1_,
arg.b_grid_desc_k0_n_k1_,
arg.c_grid_desc_m_n_,
arg.M01_,
arg.N01_);
arg.block_2_ctile_map_);
}
bool IsSupportedArgument(const BaseArgument* p_arg) override
......
include/ck/tensor_operation/gpu/device/device_conv2d_fwd_xdl_c_shuffle_nhwc_kyxc_nhwk.hpp
View file @ 6e3cf8b0
......@@ -520,18 +520,20 @@ struct DeviceConv2dFwdXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_W
a_grid_desc_k0_m_k1_ = descs[I0];
b_grid_desc_k0_n_k1_ = descs[I1];
c_grid_desc_m_n_ = descs[I2];
block_2_ctile_map_ =
GridwiseGemm::MakeDefaultBlock2CTileMap(c_grid_desc_m_n_, M01, N01);
if(GridwiseGemm::CheckValidity(
a_grid_desc_k0_m_k1_, b_grid_desc_k0_n_k1_, c_grid_desc_m_n_, M01_, N01_))
c_grid_desc_m_n_ = descs[I2];
if(GridwiseGemm::CheckValidity(a_grid_desc_k0_m_k1_,
b_grid_desc_k0_n_k1_,
c_grid_desc_m_n_,
block_2_ctile_map_))
{
c_grid_desc_mblock_mxdlperwave_mwavemperxdl_nblock_nxdlperwave_nwavenperxdl_ =
GridwiseGemm::
MakeCGridDescriptor_MBlock_MXdlPerWave_MWaveMPerXdl_NBlock_NXdlPerWave_NWaveNPerXdl(
c_grid_desc_m_n_);
block_2_ctile_map_ =
GridwiseGemm::MakeDefaultBlock2CTileMap(c_grid_desc_m_n_, M01, N01);
}
}
......@@ -568,7 +570,7 @@ struct DeviceConv2dFwdXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_W
{
using Argument = DeviceOp::Argument;
float Run(const Argument& arg, int nrepeat = 1)
float Run(const Argument& arg, const StreamConfig& stream_config = StreamConfig{})
{
#if 0
{
......@@ -631,14 +633,14 @@ struct DeviceConv2dFwdXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_W
if(!GridwiseGemm::CheckValidity(arg.a_grid_desc_k0_m_k1_,
arg.b_grid_desc_k0_n_k1_,
arg.c_grid_desc_m_n_,
arg.M01_,
arg.N01_))
arg.block_2_ctile_map_))
{
throw std::runtime_error(
"wrong! GridwiseGemm_km_kn_m0m1n0n1_xdlops_v3r1 has invalid setting");
}
const index_t grid_size = GridwiseGemm::CalculateGridSize(arg.c_grid_desc_m_n_);
const index_t grid_size =
arg.block_2_ctile_map_.CalculateGridSize(arg.c_grid_desc_m_n_);
const auto K =
arg.a_grid_desc_k0_m_k1_.GetLength(I0) * arg.a_grid_desc_k0_m_k1_.GetLength(I2);
......@@ -663,8 +665,8 @@ struct DeviceConv2dFwdXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_W
true>;
ave_time = launch_and_time_kernel(
stream_config,
kernel,
nrepeat,
dim3(grid_size),
dim3(BlockSize),
0,
......@@ -697,8 +699,8 @@ struct DeviceConv2dFwdXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_W
false>;
ave_time = launch_and_time_kernel(
stream_config,
kernel,
nrepeat,
dim3(grid_size),
dim3(BlockSize),
0,
......@@ -717,9 +719,10 @@ struct DeviceConv2dFwdXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_W
return ave_time;
}
float Run(const BaseArgument* p_arg, int nrepeat = 1) override
float Run(const BaseArgument* p_arg,
const StreamConfig& stream_config = StreamConfig{}) override
{
return Run(*dynamic_cast<const Argument*>(p_arg), nrepeat);
return Run(*dynamic_cast<const Argument*>(p_arg), stream_config);
}
};
......@@ -773,8 +776,7 @@ struct DeviceConv2dFwdXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_W
return GridwiseGemm::CheckValidity(arg.a_grid_desc_k0_m_k1_,
arg.b_grid_desc_k0_n_k1_,
arg.c_grid_desc_m_n_,
arg.M01_,
arg.N01_);
arg.block_2_ctile_map_);
}
bool IsSupportedArgument(const BaseArgument* p_arg) override
......
include/ck/tensor_operation/gpu/device/device_conv2d_fwd_xdl_nhwc_kyxc_nhwk.hpp
View file @ 6e3cf8b0
......@@ -408,15 +408,16 @@ struct DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K
a_grid_desc_k0_m_k1_ = descs[I0];
b_grid_desc_k0_n_k1_ = descs[I1];
c_grid_desc_m_n_ = descs[I2];
block_2_ctile_map_ =
GridwiseGemm::MakeDefaultBlock2CTileMap(c_grid_desc_m_n_, M01, N01);
if(GridwiseGemm::CheckValidity(
a_grid_desc_k0_m_k1_, b_grid_desc_k0_n_k1_, c_grid_desc_m_n_, M01_, N01_))
if(GridwiseGemm::CheckValidity(a_grid_desc_k0_m_k1_,
b_grid_desc_k0_n_k1_,
c_grid_desc_m_n_,
block_2_ctile_map_))
{
c_grid_desc_m0_n0_m1_n1_m2_m3_m4_n2_ =
GridwiseGemm::MakeCGridDescriptor_M0_N0_M1_N1_M2_M3_M4_N2(c_grid_desc_m_n_);
block_2_ctile_map_ =
GridwiseGemm::MakeDefaultBlock2CTileMap(c_grid_desc_m_n_, M01, N01);
}
}
......@@ -450,7 +451,7 @@ struct DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K
{
using Argument = DeviceOp::Argument;
float Run(const Argument& arg, int nrepeat = 1)
float Run(const Argument& arg, const StreamConfig& stream_config = StreamConfig{})
{
#if 0
{
......@@ -469,14 +470,14 @@ struct DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K
if(!GridwiseGemm::CheckValidity(arg.a_grid_desc_k0_m_k1_,
arg.b_grid_desc_k0_n_k1_,
arg.c_grid_desc_m_n_,
arg.M01_,
arg.N01_))
arg.block_2_ctile_map_))
{
throw std::runtime_error(
"wrong! GridwiseGemm_k0mk1_k0nk1_mn_xdlops_v2r3 has invalid setting");
}
const index_t grid_size = GridwiseGemm::CalculateGridSize(arg.c_grid_desc_m_n_);
const index_t grid_size =
arg.block_2_ctile_map_.CalculateGridSize(arg.c_grid_desc_m_n_);
const auto K =
arg.a_grid_desc_k0_m_k1_.GetLength(I0) * arg.a_grid_desc_k0_m_k1_.GetLength(I2);
......@@ -498,8 +499,8 @@ struct DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K
remove_reference_t<typename GridwiseGemm::DefaultBlock2CTileMap>,
true>;
ave_time = launch_and_time_kernel(kernel,
nrepeat,
ave_time = launch_and_time_kernel(stream_config,
kernel,
dim3(grid_size),
dim3(BlockSize),
0,
......@@ -529,8 +530,8 @@ struct DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K
remove_reference_t<typename GridwiseGemm::DefaultBlock2CTileMap>,
false>;
ave_time = launch_and_time_kernel(kernel,
nrepeat,
ave_time = launch_and_time_kernel(stream_config,
kernel,
dim3(grid_size),
dim3(BlockSize),
0,
......@@ -549,9 +550,10 @@ struct DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K
return ave_time;
}
float Run(const BaseArgument* p_arg, int nrepeat = 1) override
float Run(const BaseArgument* p_arg,
const StreamConfig& stream_config = StreamConfig{}) override
{
return Run(*dynamic_cast<const Argument*>(p_arg), nrepeat);
return Run(*dynamic_cast<const Argument*>(p_arg), stream_config);
}
};
......@@ -605,8 +607,7 @@ struct DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K
return GridwiseGemm::CheckValidity(arg.a_grid_desc_k0_m_k1_,
arg.b_grid_desc_k0_n_k1_,
arg.c_grid_desc_m_n_,
arg.M01_,
arg.N01_);
arg.block_2_ctile_map_);
}
bool IsSupportedArgument(const BaseArgument* p_arg) override
......
include/ck/tensor_operation/gpu/device/device_conv3d_fwd_naive_ndhwc_kzyxc_ndhwk.hpp
View file @ 6e3cf8b0
......@@ -92,7 +92,7 @@ struct DeviceConv3dFwdNaive_Input_N_Di_Hi_Wi_C_Weight_K_Z_Y_X_C_Output_N_Do_Ho_W
{
using Argument = DeviceOp::Argument;
float Run(const Argument& arg, int nrepeat = 1)
float Run(const Argument& arg, const StreamConfig& stream_config = StreamConfig{})
{
const auto naive_conv3d_fwd =
ref::naive_conv_fwd_ndhwc_kzyxc_ndhwk<InDataType,
......@@ -103,8 +103,8 @@ struct DeviceConv3dFwdNaive_Input_N_Di_Hi_Wi_C_Weight_K_Z_Y_X_C_Output_N_Do_Ho_W
WeiElementwiseOperation,
OutElementwiseOperation>;
float ave_time = launch_and_time_kernel(naive_conv3d_fwd,
nrepeat,
float ave_time = launch_and_time_kernel(stream_config,
naive_conv3d_fwd,
dim3(256),
dim3(256),
0,
......@@ -137,9 +137,10 @@ struct DeviceConv3dFwdNaive_Input_N_Di_Hi_Wi_C_Weight_K_Z_Y_X_C_Output_N_Do_Ho_W
}
// polymorphic
float Run(const BaseArgument* p_arg, int nrepeat = 1) override
float Run(const BaseArgument* p_arg,
const StreamConfig& stream_config = StreamConfig{}) override
{
return Run(*dynamic_cast<const Argument*>(p_arg), nrepeat);
return Run(*dynamic_cast<const Argument*>(p_arg), stream_config);
}
};
......
include/ck/tensor_operation/gpu/device/device_conv3d_fwd_xdl_ndhwc_kzyxc_ndhwk.hpp
View file @ 6e3cf8b0
......@@ -259,50 +259,6 @@ struct DeviceConv3dFwdXdl_Input_N_Di_Hi_Wi_C_Weight_K_Z_Y_X_C_Output_N_Do_Ho_Wo_
using BGridDesc_K0_N_K1 = remove_cvref_t<decltype(ABCGridDescs{}[I1])>;
using CGridDesc_M_N = remove_cvref_t<decltype(ABCGridDescs{}[I2])>;
struct Block2CTileMapMaker
{
Block2CTileMapMaker(index_t num_batches) : num_batches_(num_batches) {}
__host__ __device__ constexpr auto
MakeBlock2CTileMap(const CGridDesc_M_N& c_grid_desc_m_n, index_t M01, index_t N01)
{
const auto M = c_grid_desc_m_n.GetLength(I0);
const auto N = c_grid_desc_m_n.GetLength(I1);
constexpr auto M1 = Number<MPerBlock>{};
constexpr auto N1 = Number<NPerBlock>{};
const auto M0 = M / M1;
const auto N0 = N / N1;
const auto M00 = M0 / M01;
const auto N00 = N0 / N01;
const auto g_m00_m01_n00_n01_to_m0_n0_block_cluster_adaptor =
make_single_stage_tensor_adaptor(
make_tuple(make_insert_transform(num_batches_),
make_unmerge_transform(make_tuple(M00, M01)),
make_unmerge_transform(make_tuple(N00, N01))),
make_tuple(Sequence<>{}, Sequence<0>{}, Sequence<1>{}),
make_tuple(Sequence<0>{}, Sequence<1, 3>{}, Sequence<2, 4>{}));
const auto globalblockid_to_g_m00_m01_n00_n01_block_cluster_adaptor =
make_single_stage_tensor_adaptor(
make_tuple(make_merge_transform(make_tuple(num_batches_, M00, N00, M01, N01))),
make_tuple(Sequence<0, 1, 2, 3, 4>{}),
make_tuple(Sequence<0>{}));
const auto globalblockid_to_m0_n0_block_cluster_adaptor =
chain_tensor_adaptors(g_m00_m01_n00_n01_to_m0_n0_block_cluster_adaptor,
globalblockid_to_g_m00_m01_n00_n01_block_cluster_adaptor);
return globalblockid_to_m0_n0_block_cluster_adaptor;
}
private:
index_t num_batches_;
};
using GridwiseGemm = GridwiseGemm_k0mk1_k0nk1_mn_xdlops_v2r3<
BlockSize,
InDataType,
......@@ -345,8 +301,7 @@ struct DeviceConv3dFwdXdl_Input_N_Di_Hi_Wi_C_Weight_K_Z_Y_X_C_Output_N_Do_Ho_Wo_
using CGridDesc_M0_N0_M1_N1_M2_M3_M4_N2 =
decltype(GridwiseGemm::MakeCGridDescriptor_M0_N0_M1_N1_M2_M3_M4_N2(CGridDesc_M_N{}));
using Block2CTileMap =
decltype(Block2CTileMapMaker{1}.MakeBlock2CTileMap(CGridDesc_M_N{}, 1, 1));
using Block2CTileMap = typename GridwiseGemm::DefaultBlock2CTileMap;
// Argument
struct Argument : public BaseArgument
......@@ -398,18 +353,20 @@ struct DeviceConv3dFwdXdl_Input_N_Di_Hi_Wi_C_Weight_K_Z_Y_X_C_Output_N_Do_Ho_Wo_
b_grid_desc_k0_n_k1_ = descs[I1];
c_grid_desc_m_n_ = descs[I2];
block_2_ctile_map_ =
GridwiseGemm::MakeDefaultBlock2CTileMap(c_grid_desc_m_n_, M01, N01);
a_batch_stride_ = a_grid_desc_k0_m_k1_.GetElementSpaceSize();
b_batch_stride_ = 0;
c_batch_stride_ = c_grid_desc_m_n_.GetElementSpaceSize();
if(GridwiseGemm::CheckValidity(
a_grid_desc_k0_m_k1_, b_grid_desc_k0_n_k1_, c_grid_desc_m_n_, M01_, N01_))
if(GridwiseGemm::CheckValidity(a_grid_desc_k0_m_k1_,
b_grid_desc_k0_n_k1_,
c_grid_desc_m_n_,
block_2_ctile_map_))
{
c_grid_desc_m0_n0_m1_n1_m2_m3_m4_n2_ =
GridwiseGemm::MakeCGridDescriptor_M0_N0_M1_N1_M2_M3_M4_N2(c_grid_desc_m_n_);
block_2_ctile_map_ = Block2CTileMapMaker{num_subbatches_}.MakeBlock2CTileMap(
c_grid_desc_m_n_, M01, N01);
}
}
......@@ -438,7 +395,7 @@ struct DeviceConv3dFwdXdl_Input_N_Di_Hi_Wi_C_Weight_K_Z_Y_X_C_Output_N_Do_Ho_Wo_
{
using Argument = DeviceOp::Argument;
float Run(const Argument& arg, int nrepeat = 1)
float Run(const Argument& arg, const StreamConfig& stream_config = StreamConfig{})
{
{
std::cout << "num_batches_of_GEMM = " << arg.num_subbatches_ << std::endl;
......@@ -457,16 +414,15 @@ struct DeviceConv3dFwdXdl_Input_N_Di_Hi_Wi_C_Weight_K_Z_Y_X_C_Output_N_Do_Ho_Wo_
if(!GridwiseGemm::CheckValidity(arg.a_grid_desc_k0_m_k1_,
arg.b_grid_desc_k0_n_k1_,
arg.c_grid_desc_m_n_,
arg.M01_,
arg.N01_))
arg.block_2_ctile_map_))
{
throw std::runtime_error(
"wrong! GridwiseGemm_k0mk1_k0nk1_mn_xdlops_v2r3 has invalid setting");
}
// todo: grid_size times arg.num_subbatches_
const index_t grid_size =
GridwiseGemm::CalculateGridSize(arg.c_grid_desc_m_n_) * arg.num_subbatches_;
arg.block_2_ctile_map_.CalculateGridSize(arg.c_grid_desc_m_n_) *
arg.num_subbatches_;
const auto K0 = arg.a_grid_desc_k0_m_k1_.GetLength(I0);
......@@ -487,8 +443,8 @@ struct DeviceConv3dFwdXdl_Input_N_Di_Hi_Wi_C_Weight_K_Z_Y_X_C_Output_N_Do_Ho_Wo_
OutElementwiseOperation,
remove_reference_t<Block2CTileMap>,
true>;
ave_time = launch_and_time_kernel(kernel,
nrepeat,
ave_time = launch_and_time_kernel(stream_config,
kernel,
dim3(grid_size),
dim3(BlockSize),
0,
......@@ -522,8 +478,8 @@ struct DeviceConv3dFwdXdl_Input_N_Di_Hi_Wi_C_Weight_K_Z_Y_X_C_Output_N_Do_Ho_Wo_
remove_reference_t<Block2CTileMap>,
false>;
ave_time = launch_and_time_kernel(kernel,
nrepeat,
ave_time = launch_and_time_kernel(stream_config,
kernel,
dim3(grid_size),
dim3(BlockSize),
0,
......@@ -547,9 +503,10 @@ struct DeviceConv3dFwdXdl_Input_N_Di_Hi_Wi_C_Weight_K_Z_Y_X_C_Output_N_Do_Ho_Wo_
}
// polymorphic
float Run(const BaseArgument* p_arg, int nrepeat = 1) override
float Run(const BaseArgument* p_arg,
const StreamConfig& stream_config = StreamConfig{}) override
{
return Run(*dynamic_cast<const Argument*>(p_arg), nrepeat);
return Run(*dynamic_cast<const Argument*>(p_arg), stream_config);
}
};
......@@ -564,8 +521,7 @@ struct DeviceConv3dFwdXdl_Input_N_Di_Hi_Wi_C_Weight_K_Z_Y_X_C_Output_N_Do_Ho_Wo_
return GridwiseGemm::CheckValidity(arg.a_grid_desc_k0_m_k1_,
arg.b_grid_desc_k0_n_k1_,
arg.c_grid_desc_m_n_,
arg.M01_,
arg.N01_);
arg.block_2_ctile_map_);
}
// polymorphic
......
include/ck/tensor_operation/gpu/device/device_convnd_bwd_data_xdl_ndhwc_kzyxc_ndhwk.hpp
View file @ 6e3cf8b0
......@@ -1073,13 +1073,15 @@ struct DeviceConvndBwdDataXdl_Input_N_Di_Hi_Wi_C_Weight_K_Z_Y_X_C_Output_N_Do_Ho
b_grid_desc_k0_n_k1_container_.push_back(descs[I1]);
c_grid_desc_m_n_container_.push_back(descs[I2]);
if(GridwiseGemm::CheckValidity(descs[I0], descs[I1], descs[I2], M01_, N01_))
auto block_2_ctile_map =
GridwiseGemm::MakeDefaultBlock2CTileMap(descs[I2], M01_, N01_);
if(GridwiseGemm::CheckValidity(descs[I0], descs[I1], descs[I2], block_2_ctile_map))
{
c_grid_desc_m0_n0_m1_n1_m2_m3_m4_n2_container_.push_back(
GridwiseGemm::MakeCGridDescriptor_M0_N0_M1_N1_M2_M3_M4_N2(descs[I2]));
block_2_ctile_map_container_.push_back(
GridwiseGemm::MakeDefaultBlock2CTileMap(descs[I2], M01_, N01_));
block_2_ctile_map_container_.push_back(block_2_ctile_map);
}
}
}
......@@ -1129,13 +1131,16 @@ struct DeviceConvndBwdDataXdl_Input_N_Di_Hi_Wi_C_Weight_K_Z_Y_X_C_Output_N_Do_Ho
b_grid_desc_k0_n_k1_container_.push_back(descs[I1]);
c_grid_desc_m_n_container_.push_back(descs[I2]);
if(GridwiseGemm::CheckValidity(descs[I0], descs[I1], descs[I2], M01_, N01_))
auto block_2_ctile_map =
GridwiseGemm::MakeDefaultBlock2CTileMap(descs[I2], M01_, N01_);
if(GridwiseGemm::CheckValidity(
descs[I0], descs[I1], descs[I2], block_2_ctile_map))
{
c_grid_desc_m0_n0_m1_n1_m2_m3_m4_n2_container_.push_back(
GridwiseGemm::MakeCGridDescriptor_M0_N0_M1_N1_M2_M3_M4_N2(descs[I2]));
block_2_ctile_map_container_.push_back(
GridwiseGemm::MakeDefaultBlock2CTileMap(descs[I2], M01_, N01_));
block_2_ctile_map_container_.push_back(block_2_ctile_map);
}
}
}
......@@ -1194,14 +1199,17 @@ struct DeviceConvndBwdDataXdl_Input_N_Di_Hi_Wi_C_Weight_K_Z_Y_X_C_Output_N_Do_Ho
b_grid_desc_k0_n_k1_container_.push_back(descs[I1]);
c_grid_desc_m_n_container_.push_back(descs[I2]);
if(GridwiseGemm::CheckValidity(descs[I0], descs[I1], descs[I2], M01_, N01_))
auto block_2_ctile_map =
GridwiseGemm::MakeDefaultBlock2CTileMap(descs[I2], M01_, N01_);
if(GridwiseGemm::CheckValidity(
descs[I0], descs[I1], descs[I2], block_2_ctile_map))
{
c_grid_desc_m0_n0_m1_n1_m2_m3_m4_n2_container_.push_back(
GridwiseGemm::MakeCGridDescriptor_M0_N0_M1_N1_M2_M3_M4_N2(
descs[I2]));
block_2_ctile_map_container_.push_back(
GridwiseGemm::MakeDefaultBlock2CTileMap(descs[I2], M01_, N01_));
block_2_ctile_map_container_.push_back(block_2_ctile_map);
}
}
}
......@@ -1241,7 +1249,7 @@ struct DeviceConvndBwdDataXdl_Input_N_Di_Hi_Wi_C_Weight_K_Z_Y_X_C_Output_N_Do_Ho
{
using Argument = DeviceOp::Argument;
float Run(const Argument& arg, int nrepeat = 1)
float Run(const Argument& arg, const StreamConfig& stream_config = StreamConfig{})
{
float ave_time = 0;
for(size_t i = 0; i < arg.a_grid_desc_k0_m_k1_container_.size(); i++)
......@@ -1286,15 +1294,14 @@ struct DeviceConvndBwdDataXdl_Input_N_Di_Hi_Wi_C_Weight_K_Z_Y_X_C_Output_N_Do_Ho
if(!GridwiseGemm::CheckValidity(arg.a_grid_desc_k0_m_k1_container_[i],
arg.b_grid_desc_k0_n_k1_container_[i],
arg.c_grid_desc_m_n_container_[i],
arg.M01_,
arg.N01_))
arg.block_2_ctile_map_container_[i]))
{
throw std::runtime_error(
"wrong! GridwiseGemm_km_kn_m0m1n0n1_xdlops_v3r1 has invalid setting");
}
const index_t grid_size =
GridwiseGemm::CalculateGridSize(arg.c_grid_desc_m_n_container_[i]);
const index_t grid_size = arg.block_2_ctile_map_container_[i].CalculateGridSize(
arg.c_grid_desc_m_n_container_[i]);
const auto K = arg.a_grid_desc_k0_m_k1_container_[i].GetLength(I0) *
arg.a_grid_desc_k0_m_k1_container_[i].GetLength(I2);
......@@ -1316,8 +1323,8 @@ struct DeviceConvndBwdDataXdl_Input_N_Di_Hi_Wi_C_Weight_K_Z_Y_X_C_Output_N_Do_Ho
true>;
ave_time += launch_and_time_kernel(
stream_config,
kernel,
nrepeat,
dim3(grid_size),
dim3(BlockSize),
0,
......@@ -1349,8 +1356,8 @@ struct DeviceConvndBwdDataXdl_Input_N_Di_Hi_Wi_C_Weight_K_Z_Y_X_C_Output_N_Do_Ho
false>;
ave_time += launch_and_time_kernel(
stream_config,
kernel,
nrepeat,
dim3(grid_size),
dim3(BlockSize),
0,
......@@ -1369,9 +1376,10 @@ struct DeviceConvndBwdDataXdl_Input_N_Di_Hi_Wi_C_Weight_K_Z_Y_X_C_Output_N_Do_Ho
return ave_time;
}
float Run(const BaseArgument* p_arg, int nrepeat = 1) override
float Run(const BaseArgument* p_arg,
const StreamConfig& stream_config = StreamConfig{}) override
{
return Run(*dynamic_cast<const Argument*>(p_arg), nrepeat);
return Run(*dynamic_cast<const Argument*>(p_arg), stream_config);
}
};
......@@ -1417,8 +1425,7 @@ struct DeviceConvndBwdDataXdl_Input_N_Di_Hi_Wi_C_Weight_K_Z_Y_X_C_Output_N_Do_Ho
if(!GridwiseGemm::CheckValidity(arg.a_grid_desc_k0_m_k1_container_[i],
arg.b_grid_desc_k0_n_k1_container_[i],
arg.c_grid_desc_m_n_container_[i],
arg.M01_,
arg.N01_))
arg.block_2_ctile_map_container_[i]))
{
return false;
}
......@@ -1527,10 +1534,10 @@ struct DeviceConvndBwdDataXdl_Input_N_Di_Hi_Wi_C_Weight_K_Z_Y_X_C_Output_N_Do_Ho
<< ">";
if constexpr(ConvBackwardDataSpecialization ==
ConvolutionBackwardDataSpecialization::Filter1x1Stride1Pad0){
str<< " Filter1x1Stride1Pad0";
}
return str.str();
}
......
include/ck/tensor_operation/gpu/device/device_convnd_fwd_xdl_nhwc_kyxc_nhwk.hpp
View file @ 6e3cf8b0
......@@ -705,15 +705,16 @@ struct DeviceConvNDFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K
a_grid_desc_k0_m_k1_ = descs[I0];
b_grid_desc_k0_n_k1_ = descs[I1];
c_grid_desc_m_n_ = descs[I2];
block_2_ctile_map_ =
GridwiseGemm::MakeDefaultBlock2CTileMap(c_grid_desc_m_n_, M01, N01);
if(GridwiseGemm::CheckValidity(
a_grid_desc_k0_m_k1_, b_grid_desc_k0_n_k1_, c_grid_desc_m_n_, M01_, N01_))
if(GridwiseGemm::CheckValidity(a_grid_desc_k0_m_k1_,
b_grid_desc_k0_n_k1_,
c_grid_desc_m_n_,
block_2_ctile_map_))
{
c_grid_desc_m0_n0_m1_n1_m2_m3_m4_n2_ =
GridwiseGemm::MakeCGridDescriptor_M0_N0_M1_N1_M2_M3_M4_N2(c_grid_desc_m_n_);
block_2_ctile_map_ =
GridwiseGemm::MakeDefaultBlock2CTileMap(c_grid_desc_m_n_, M01, N01);
}
}
......@@ -747,7 +748,7 @@ struct DeviceConvNDFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K
{
using Argument = DeviceOp::Argument;
float Run(const Argument& arg, int nrepeat = 1)
float Run(const Argument& arg, const StreamConfig& stream_config = StreamConfig{})
{
#if 0
{
......@@ -766,14 +767,14 @@ struct DeviceConvNDFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K
if(!GridwiseGemm::CheckValidity(arg.a_grid_desc_k0_m_k1_,
arg.b_grid_desc_k0_n_k1_,
arg.c_grid_desc_m_n_,
arg.M01_,
arg.N01_))
arg.block_2_ctile_map_))
{
throw std::runtime_error(
"wrong! GridwiseGemm_km_kn_m0m1n0n1_xdlops_v2r3 has invalid setting");
}
const index_t grid_size = GridwiseGemm::CalculateGridSize(arg.c_grid_desc_m_n_);
const index_t grid_size =
arg.block_2_ctile_map_.CalculateGridSize(arg.c_grid_desc_m_n_);
const auto K =
arg.a_grid_desc_k0_m_k1_.GetLength(I0) * arg.a_grid_desc_k0_m_k1_.GetLength(I2);
......@@ -795,8 +796,8 @@ struct DeviceConvNDFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K
remove_reference_t<typename GridwiseGemm::DefaultBlock2CTileMap>,
true>;
ave_time = launch_and_time_kernel(kernel,
nrepeat,
ave_time = launch_and_time_kernel(stream_config,
kernel,
dim3(grid_size),
dim3(BlockSize),
0,
......@@ -826,8 +827,8 @@ struct DeviceConvNDFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K
remove_reference_t<typename GridwiseGemm::DefaultBlock2CTileMap>,
false>;
ave_time = launch_and_time_kernel(kernel,
nrepeat,
ave_time = launch_and_time_kernel(stream_config,
kernel,
dim3(grid_size),
dim3(BlockSize),
0,
......@@ -846,9 +847,10 @@ struct DeviceConvNDFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K
return ave_time;
}
float Run(const BaseArgument* p_arg, int nrepeat = 1) override
float Run(const BaseArgument* p_arg,
const StreamConfig& stream_config = StreamConfig{}) override
{
return Run(*dynamic_cast<const Argument*>(p_arg), nrepeat);
return Run(*dynamic_cast<const Argument*>(p_arg), stream_config);
}
};
......@@ -915,8 +917,7 @@ struct DeviceConvNDFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K
return GridwiseGemm::CheckValidity(arg.a_grid_desc_k0_m_k1_,
arg.b_grid_desc_k0_n_k1_,
arg.c_grid_desc_m_n_,
arg.M01_,
arg.N01_);
arg.block_2_ctile_map_);
}
bool IsSupportedArgument(const BaseArgument* p_arg) override
......@@ -1011,7 +1012,7 @@ struct DeviceConvNDFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K
auto str = std::stringstream();
// clang-format off
str << "DeviceConv" << std::to_string(NumDimSpatial)
str << "DeviceConv" << std::to_string(NumDimSpatial)
<< "DFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K"
<< "<"
<< BlockSize << ", "
......
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