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Commit b12bbcee authored by Chao Liu's avatar Chao Liu
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clean up

parent 51a9fa1d
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Showing with 2372 additions and 2299 deletions
composable_kernel/include/kernel_algorithm/gridwise_convolution_implicit_gemm_v4r1_nchw_kcyx_nkhw_lds_double_buffer.hpp
View file @ b12bbcee
......@@ -5,9 +5,9 @@
#include "ConstantTensorDescriptor.hpp"
#include "ConstantMergedTensorDescriptor.hpp"
#include "ConstantMatrixDescriptor.hpp"
#include "blockwise_generic_tensor_slice_copy.hpp"
#include "blockwise_generic_tensor_slice_copy_deprecated.hpp"
#include "blockwise_gemm.hpp"
#include "threadwise_generic_tensor_slice_copy.hpp"
#include "threadwise_generic_tensor_slice_copy_deprecated.hpp"
namespace ck {
......@@ -265,8 +265,10 @@ struct GridwiseConvolutionImplicitGemm_v4r1_nchw_kcyx_nkhw_lds_double_buffer
// LDS double buffer: preload data into LDS
{
blockwise_in_copy.Run(p_in_global, p_in_block_double);
blockwise_wei_copy.Run(p_wei_global, p_wei_block_double);
blockwise_in_copy.template Run<Float, address_space_t::global>(p_in_global,
p_in_block_double);
blockwise_wei_copy.template Run<Float, address_space_t::global>(p_wei_global,
p_wei_block_double);
}
// LDS double buffer: main body
......@@ -288,8 +290,8 @@ struct GridwiseConvolutionImplicitGemm_v4r1_nchw_kcyx_nkhw_lds_double_buffer
Float* p_wei_block_next =
even_loop ? p_wei_block_double + wei_block_space : p_wei_block_double;
Float p_in_register_buffer[blockwise_in_copy.GetRegisterBufferSize()];
Float p_wei_register_buffer[blockwise_wei_copy.GetRegisterBufferSize()];
Float p_in_thread_buffer[blockwise_in_copy.GetThreadBufferSize()];
Float p_wei_thread_buffer[blockwise_wei_copy.GetThreadBufferSize()];
blockwise_in_copy.MoveSrcSliceWindow(Sequence<EPerBlock, 0, 0, 0>{}, True);
blockwise_wei_copy.MoveSrcSliceWindow(Sequence<EPerBlock, 0>{}, True);
......@@ -297,23 +299,25 @@ struct GridwiseConvolutionImplicitGemm_v4r1_nchw_kcyx_nkhw_lds_double_buffer
__syncthreads();
// LDS doubel buffer: load next data from device mem
blockwise_in_copy.RunLoadRegisterBuffer(p_in_global, p_in_register_buffer);
blockwise_wei_copy.RunLoadRegisterBuffer(p_wei_global, p_wei_register_buffer);
blockwise_in_copy.template RunLoadThreadBuffer<Float, address_space_t::global>(
p_in_global, p_in_thread_buffer);
blockwise_wei_copy.template RunLoadThreadBuffer<Float, address_space_t::global>(
p_wei_global, p_wei_thread_buffer);
// LDS double buffer: GEMM on current data
blockwise_gemm.Run(p_wei_block_now, p_in_block_now, p_out_thread);
// LDS double buffer: store next data to LDS
blockwise_in_copy.RunStoreRegisterBuffer(p_in_register_buffer, p_in_block_next);
blockwise_wei_copy.RunStoreRegisterBuffer(p_wei_register_buffer, p_wei_block_next);
blockwise_in_copy.RunStoreThreadBuffer(p_in_thread_buffer, p_in_block_next);
blockwise_wei_copy.RunStoreThreadBuffer(p_wei_thread_buffer, p_wei_block_next);
}
}
// LDS double buffer: tail
{
// even iteration
Float p_in_register_buffer[blockwise_in_copy.GetRegisterBufferSize()];
Float p_wei_register_buffer[blockwise_wei_copy.GetRegisterBufferSize()];
Float p_in_thread_buffer[blockwise_in_copy.GetThreadBufferSize()];
Float p_wei_thread_buffer[blockwise_wei_copy.GetThreadBufferSize()];
blockwise_in_copy.MoveSrcSliceWindow(Sequence<EPerBlock, 0, 0, 0>{}, True);
blockwise_wei_copy.MoveSrcSliceWindow(Sequence<EPerBlock, 0>{}, True);
......@@ -321,17 +325,19 @@ struct GridwiseConvolutionImplicitGemm_v4r1_nchw_kcyx_nkhw_lds_double_buffer
__syncthreads();
// LDS doubel buffer: load next data from device mem
blockwise_in_copy.RunLoadRegisterBuffer(p_in_global, p_in_register_buffer);
blockwise_wei_copy.RunLoadRegisterBuffer(p_wei_global, p_wei_register_buffer);
blockwise_in_copy.template RunLoadThreadBuffer<Float, address_space_t::global>(
p_in_global, p_in_thread_buffer);
blockwise_wei_copy.template RunLoadThreadBuffer<Float, address_space_t::global>(
p_wei_global, p_wei_thread_buffer);
// LDS double buffer: GEMM on current data
blockwise_gemm.Run(p_wei_block_double, p_in_block_double, p_out_thread);
// LDS double buffer: store next data to LDS
blockwise_in_copy.RunStoreRegisterBuffer(p_in_register_buffer,
p_in_block_double + in_block_space);
blockwise_wei_copy.RunStoreRegisterBuffer(p_wei_register_buffer,
p_wei_block_double + wei_block_space);
blockwise_in_copy.RunStoreThreadBuffer(p_in_thread_buffer,
p_in_block_double + in_block_space);
blockwise_wei_copy.RunStoreThreadBuffer(p_wei_thread_buffer,
p_wei_block_double + wei_block_space);
// odd iteration
__syncthreads();
......@@ -390,7 +396,14 @@ struct GridwiseConvolutionImplicitGemm_v4r1_nchw_kcyx_nkhw_lds_double_buffer
0,
b_thread_data_on_global,
0})
.template Run_amd_experiment<Float, 0, 2>(p_out_thread, p_out_global);
#if 0
.Run
#else // tweaking
.template Run_optimized_address_calculation<Float,
address_space_t::generic,
address_space_t::global>
#endif
(p_out_thread, p_out_global);
}
}
};
......
composable_kernel/include/kernel_algorithm/gridwise_convolution_implicit_gemm_v4r4_nchw_kcyx_nkhw_lds_double_buffer.hpp
View file @ b12bbcee
......@@ -5,9 +5,9 @@
#include "ConstantTensorDescriptor.hpp"
#include "ConstantMergedTensorDescriptor.hpp"
#include "ConstantMatrixDescriptor.hpp"
#include "blockwise_generic_tensor_slice_copy.hpp"
#include "blockwise_generic_tensor_slice_copy_deprecated.hpp"
#include "blockwise_gemm.hpp"
#include "threadwise_generic_tensor_slice_copy.hpp"
#include "threadwise_generic_tensor_slice_copy_deprecated.hpp"
namespace ck {
......@@ -251,8 +251,10 @@ struct GridwiseConvolutionImplicitGemm_v4r4_nchw_kcyx_nkhw_lds_double_buffer
// LDS double buffer: preload data into LDS
{
blockwise_in_copy.Run(p_in_global, p_in_block_double);
blockwise_wei_copy.Run(p_wei_global, p_wei_block_double);
blockwise_in_copy.template Run<Float, address_space_t::global>(p_in_global,
p_in_block_double);
blockwise_wei_copy.template Run<Float, address_space_t::global>(p_wei_global,
p_wei_block_double);
}
// LDS double buffer: main body
......@@ -274,51 +276,54 @@ struct GridwiseConvolutionImplicitGemm_v4r4_nchw_kcyx_nkhw_lds_double_buffer
Float* p_wei_block_next =
even_loop ? p_wei_block_double + wei_block_space : p_wei_block_double;
Float p_in_register_buffer[blockwise_in_copy.GetRegisterBufferSize()];
Float p_wei_register_buffer[blockwise_wei_copy.GetRegisterBufferSize()];
Float p_in_thread_buffer[blockwise_in_copy.GetThreadBufferSize()];
Float p_wei_thread_buffer[blockwise_wei_copy.GetThreadBufferSize()];
blockwise_in_copy.MoveSrcSliceWindow(Sequence<EPerBlock, 0>{}, True);
p_wei_block_on_global += EPerBlock * wei_e_k_global_desc.GetStrides()[0];
blockwise_wei_copy.MoveSrcSliceWindow(Sequence<EPerBlock, 0>{}, True);
__syncthreads();
// LDS doubel buffer: load next data from device mem
blockwise_in_copy.RunLoadRegisterBuffer(p_in_global, p_in_register_buffer);
blockwise_wei_copy.RunLoadRegisterBuffer(p_wei_block_on_global,
p_wei_register_buffer);
blockwise_in_copy.template RunLoadThreadBuffer<Float, address_space_t::global>(
p_in_global, p_in_thread_buffer);
blockwise_wei_copy.template RunLoadThreadBuffer<Float, address_space_t::global>(
p_wei_global, p_wei_thread_buffer);
// LDS double buffer: GEMM on current data
blockwise_gemm.Run(p_wei_block_now, p_in_block_now, p_out_thread);
// LDS double buffer: store next data to LDS
blockwise_in_copy.RunStoreRegisterBuffer(p_in_register_buffer, p_in_block_next);
blockwise_wei_copy.RunStoreRegisterBuffer(p_wei_register_buffer, p_wei_block_next);
blockwise_in_copy.RunStoreThreadBuffer(p_in_thread_buffer, p_in_block_next);
blockwise_wei_copy.RunStoreThreadBuffer(p_wei_thread_buffer, p_wei_block_next);
}
}
// LDS double buffer: tail
{
Float p_in_register_buffer[blockwise_in_copy.GetRegisterBufferSize()];
Float p_wei_register_buffer[blockwise_wei_copy.GetRegisterBufferSize()];
Float p_in_thread_buffer[blockwise_in_copy.GetThreadBufferSize()];
Float p_wei_thread_buffer[blockwise_wei_copy.GetThreadBufferSize()];
// even iteration
blockwise_in_copy.MoveSrcSliceWindow(Sequence<EPerBlock, 0>{}, True);
p_wei_block_on_global += EPerBlock * wei_e_k_global_desc.GetStrides()[0];
blockwise_wei_copy.MoveSrcSliceWindow(Sequence<EPerBlock, 0>{}, True);
__syncthreads();
// LDS doubel buffer: load next data from device mem
blockwise_in_copy.RunLoadRegisterBuffer(p_in_global, p_in_register_buffer);
blockwise_wei_copy.RunLoadRegisterBuffer(p_wei_block_on_global, p_wei_register_buffer);
blockwise_in_copy.template RunLoadThreadBuffer<Float, address_space_t::global>(
p_in_global, p_in_thread_buffer);
blockwise_wei_copy.template RunLoadThreadBuffer<Float, address_space_t::global>(
p_wei_global, p_wei_thread_buffer);
// LDS double buffer: GEMM on current data
blockwise_gemm.Run(p_wei_block_double, p_in_block_double, p_out_thread);
// LDS double buffer: store next data to LDS
blockwise_in_copy.RunStoreRegisterBuffer(p_in_register_buffer,
p_in_block_double + in_block_space);
blockwise_wei_copy.RunStoreRegisterBuffer(p_wei_register_buffer,
p_wei_block_double + wei_block_space);
blockwise_in_copy.RunStoreThreadBuffer(p_in_thread_buffer,
p_in_block_double + in_block_space);
blockwise_wei_copy.RunStoreThreadBuffer(p_wei_thread_buffer,
p_wei_block_double + wei_block_space);
// odd iteration
__syncthreads();
......@@ -385,7 +390,15 @@ struct GridwiseConvolutionImplicitGemm_v4r4_nchw_kcyx_nkhw_lds_double_buffer
for(index_t nrepeat = 0; nrepeat < GemmNRepeat; ++nrepeat)
{
threadwise_out_copy.Run(p_out_thread, p_out_global);
threadwise_out_copy
#if 1
.Run
#else // tweaking
.template Run_optimized_address_calculation<Float,
address_space_t::generic,
address_space_t::global>
#endif
(p_out_thread, p_out_global);
threadwise_out_copy.MoveSrcSliceWindow(Sequence<0, 0, GemmNPerThreadSubC>{}, True);
threadwise_out_copy.MoveDstSliceWindow(Sequence<0, 0, B1>{}, True);
......
composable_kernel/include/tensor_description/tensor_coordinate.hpp
View file @ b12bbcee
#ifndef CK_TENSOR_COORDINATE_HPP
#define CK_TENSOR_COORDINATE_HPP
#ifndef CK_TENSOR_COORDINATE_V2_HPP
#define CK_TENSOR_COORDINATE_V2_HPP
#include "common_header.hpp"
#include "ConstantTensorDescriptor.hpp"
#include "ConstantMergedTensorDescriptor.hpp"
#include "dimension.hpp"
#include "multi_index_transform.hpp"
#include "tensor_descriptor.hpp"
namespace ck {
// TensorDesc is ConstantTensorDescriptor
template <class TensorDesc>
struct NormalTensorCoordinate
{
using type = NormalTensorCoordinate;
using tensor_desc_type = TensorDesc;
template <typename TensorDesc>
struct TensorCoordinate;
template <typename NativeTensorDesc>
struct NativeTensorCoordinate
{
using type = NativeTensorCoordinate;
using tensor_desc_type = NativeTensorDesc;
static constexpr index_t nDim = tensor_desc_type::GetNumOfDimension();
using Index = MultiIndex<nDim>;
__host__ __device__ constexpr NormalTensorCoordinate(Array<index_t, nDim> tensor_index)
: mOffset{tensor_desc_type::GetOffsetFromMultiIndex(tensor_index)}
__host__ __device__ constexpr NativeTensorCoordinate(Index idx)
: mIndex(idx), mOffset(tensor_desc_type::CalculateOffset(idx))
{
}
template <class... Xs>
__host__ __device__ constexpr NormalTensorCoordinate(Xs... xs)
: NormalTensorCoordinate(Array<index_t, nDim>{xs...})
template <typename... Xs>
__host__ __device__ constexpr NativeTensorCoordinate(Xs... xs)
: NativeTensorCoordinate(Index{xs...})
{
}
template <index_t... Xs>
__host__ __device__ constexpr NormalTensorCoordinate(Sequence<Xs...>)
: NormalTensorCoordinate(Array<index_t, nDim>{Xs...})
__host__ __device__ constexpr NativeTensorCoordinate(Sequence<Xs...>)
: NativeTensorCoordinate(Index{Xs...})
{
}
__host__ __device__ constexpr index_t GetOffset() const { return mOffset; }
__host__ __device__ static constexpr auto GetTensorDescriptor() { return tensor_desc_type{}; }
__host__ __device__ constexpr const Index& GetIndex() const { return mIndex; }
// T is Array or Sequence
template <class T>
__host__ __device__ type operator+=(T step_sizes)
__host__ __device__ constexpr const index_t& GetOffset() const { return mOffset; }
__host__ __device__ constexpr type operator+=(const Index& idx_diff)
{
static_assert(is_same<typename T::data_type, index_t>{} && T::GetSize() == nDim, "wrong!");
// mIndex is updated here, but some (or all) of its entries may never be used
// compiler should remove those entries as dead code
mIndex += idx_diff;
mOffset += tensor_desc_type::GetOffsetFromMultiIndex(step_sizes);
mOffset += tensor_desc_type::CalculateOffsetDiff(idx_diff);
return *this;
}
template <class T>
__host__ __device__ type operator-=(T step_sizes)
__host__ __device__ constexpr type operator-=(const Index& idx_diff)
{
static_assert(is_same<typename T::data_type, index_t>{} && T::GetSize() == nDim, "wrong!");
// mIndex is updated here, but some (or all) of its entries may never be used
// compiler should remove those entries as dead code
mIndex -= idx_diff;
mOffset -= tensor_desc_type::GetOffsetFromMultiIndex(step_sizes);
mOffset -= tensor_desc_type::CalculateOffsetDiff(idx_diff);
return *this;
}
template <class T>
__host__ __device__ constexpr type operator+(T step_sizes) const
__host__ __device__ constexpr type operator+(const Index& idx_diff) const
{
type coord = *this;
coord += step_sizes;
coord += idx_diff;
return coord;
}
template <class T>
__host__ __device__ constexpr type operator-(T step_sizes) const
__host__ __device__ constexpr type operator-(const Index& idx_diff) const
{
type coord = *this;
coord -= step_sizes;
coord -= idx_diff;
return coord;
}
// reposition point of origin, and return compensated offset.
// This is a hack to reduce index calculation during looping over
// a tensor whose origin is this TensorCoordinate. It does so, by spitting
// out the run-time offset to the pointer (to the tensor data) held by this
// TensorCoordiante, so the caller can add the offset into the run-time pointer of
// the data, so only 1 run-time variable (update pointer) is needed, instead
// of 2 run-time variables (old pointer and this offset)
// TODO: after introducing the concept of "run-time tensor view", which contains the
// run-time pointer to the data, always keep track of the pointer, instead of both
// offset and the pointer. This also bring additional benefit that we don't need to
// worry the offset might underflow (because offset is unsigned integer) when updating it.
__host__ __device__ constexpr index_t RepositionOrigin()
{
index_t offset_diff = mOffset;
mOffset = 0;
return offset_diff;
}
__host__ __device__ static constexpr bool IsUpperIndexMappedToValidOffset() { return true; }
private:
// mIndex may be saved and updated, however, the value of some (or all) of its entries may
// never be used. Compiler should be able to remove these entries as well as its calculation
// as dead code.
// TODO: make sure compiler indeed remove these dead code
Index mIndex;
index_t mOffset;
};
// TensorDesc is ConstantMergedTensorDescriptor
template <class TensorDesc>
struct MergedTensorCoordinate
template <typename TransformedTensorDesc>
struct TransformedTensorCoordinate
{
using type = MergedTensorCoordinate;
using tensor_desc_type = TensorDesc;
using tensor_desc_type = TransformedTensorDesc;
using LowerCoord =
typename TensorCoordinate<decltype(tensor_desc_type::GetLowerTensorDescriptor())>::type;
using UpperCoord = TransformedTensorCoordinate;
static constexpr index_t nDim = tensor_desc_type::GetNumOfDimension();
static constexpr index_t nOriginalDim =
tensor_desc_type::GetOriginalTensorDescriptor().GetNumOfDimension();
using UpperIndex = MultiIndex<nDim>;
__host__ __device__ constexpr MergedTensorCoordinate(Array<index_t, nDim> tensor_index)
: mOriginalIndex{tensor_desc_type::GetOriginalMultiIndexFromMultiIndex(tensor_index)}
__host__ __device__ constexpr TransformedTensorCoordinate(UpperIndex idx)
: mIndexUp{idx}, mCoordLow{tensor_desc_type::CalculateLowerIndex(idx)}
{
// partial offset on each dimension
static_for<0, nDim, 1>{}([&](auto idim) {
constexpr auto partial_original_dims =
tensor_desc_type::GetContainedOriginalDimensions(idim);
constexpr auto partial_original_desc =
tensor_desc_type::GetOriginalTensorDescriptor().Extract(partial_original_dims);
mPartialOffsets(idim) = partial_original_desc.GetOffsetFromMultiIndex(
extract_array(mOriginalIndex, partial_original_dims));
});
}
// complete offset
mOffset =
accumulate_on_array(mPartialOffsets, math::plus<index_t>{}, static_cast<index_t>(0));
template <typename... Xs>
__host__ __device__ constexpr TransformedTensorCoordinate(Xs... xs)
: TransformedTensorCoordinate(UpperIndex{xs...})
{
}
template <class... Xs>
__host__ __device__ constexpr MergedTensorCoordinate(Xs... xs)
: MergedTensorCoordinate(Array<index_t, nDim>{xs...})
template <index_t... Xs>
__host__ __device__ constexpr TransformedTensorCoordinate(Sequence<Xs...>)
: TransformedTensorCoordinate(UpperIndex{Xs...})
{
}
__host__ __device__ constexpr index_t GetOffset() const { return mOffset; }
__host__ __device__ static constexpr auto GetTensorDescriptor() { return tensor_desc_type{}; }
template <class IDim, class T, bool PositiveDirection>
__host__ __device__ void
MoveOnDimension(IDim idim_, T step_size, integral_constant<bool, PositiveDirection>)
{
constexpr auto idim = idim_;
__host__ __device__ constexpr const LowerCoord& GetLowerCoordinate() const { return mCoordLow; }
__host__ __device__ constexpr const UpperIndex& GetUpperIndex() const { return mIndexUp; }
__host__ __device__ constexpr const UpperIndex& GetIndex() const { return GetUpperIndex(); }
// if step_size is known at compile time
static_if<is_static<T>::value>{}(
[&](auto) { static_if<T{} == 0>{}([&](auto) { return; }); });
// update original index
static_if<tensor_desc_type::ContainMultipleOriginalDimensions(idim)>{}([&](auto) {
constexpr auto partial_original_dims =
tensor_desc_type::GetContainedOriginalDimensions(idim);
constexpr index_t ndim_partial_original = partial_original_dims.GetSize();
constexpr auto partial_original_desc =
tensor_desc_type::GetOriginalTensorDescriptor().Extract(partial_original_dims);
const auto partial_original_step_sizes =
partial_original_desc.GetMultiIndexFrom1dIndex(step_size);
// update partial original multi-id
auto partial_original_id = extract_array(mOriginalIndex, partial_original_dims);
static_if<PositiveDirection>{}([&](auto) {
partial_original_id += partial_original_step_sizes;
bool carry = false;
// do carry check in reversed order, starting from lowest dimension
// don't check the highest dimension
static_for<0, ndim_partial_original - 1, 1>{}([&](auto IReverse) {
constexpr index_t i = ndim_partial_original - 1 - IReverse;
if(carry)
{
++partial_original_id(i);
}
carry = false;
if(partial_original_id[i] >= partial_original_desc.GetLength(i))
{
partial_original_id(i) -= partial_original_desc.GetLength(i);
carry = true;
}
});
// highest dimension
if(carry)
{
++partial_original_id(0);
}
}).Else([&](auto) {
// shift up multi-id to avoid unsigned integer underflow during intermediate
// calculations. After the shift, should have new_multi_id[...] >= 1
partial_original_id +=
partial_original_desc.GetLengths() - partial_original_step_sizes;
bool borrow = false;
// do borrow check in reversed order, starting from lowest dimension
// don't check the highest dimension
static_for<0, ndim_partial_original - 1, 1>{}([&](auto IReverse) {
constexpr index_t i = ndim_partial_original - 1 - IReverse;
if(borrow)
{
--partial_original_id(i);
}
borrow = false;
if(partial_original_id[i] < partial_original_desc.GetLength(i))
{
partial_original_id(i) += partial_original_desc.GetLength(i);
borrow = true;
}
});
// highest dimension
if(borrow)
{
--partial_original_id(0);
}
// shift back down multi-id
// here, should have new_multi_id[...] >= GetLengths()
partial_original_id = partial_original_id - partial_original_desc.GetLengths();
});
// update "mOriginalIndex"
static_for<0, ndim_partial_original, 1>{}([&](auto I) {
constexpr auto idim_original = partial_original_dims[I];
mOriginalIndex(idim_original) = partial_original_id[I];
});
// calculate new partial offset on this merged dimension
const index_t old_partial_offset = mPartialOffsets[idim];
mPartialOffsets(idim) =
partial_original_desc.GetOffsetFromMultiIndex(partial_original_id);
// update "mThreadSrcOffset", do "+" before "-" to avoid underflow
mOffset = (mOffset + mPartialOffsets[idim]) - old_partial_offset;
}).Else([&](auto fwd) {
static_if<PositiveDirection>{}([&](auto) {
mOffset += step_size * fwd(tensor_desc_type{}).GetStride(idim);
}).Else([&](auto) { mOffset -= step_size * fwd(tensor_desc_type{}).GetStride(idim); });
});
__host__ __device__ constexpr const index_t& GetOffset() const
{
return GetLowerCoordinate().GetOffset();
}
// T is Array or Sequence
template <class T>
__host__ __device__ type operator+=(T step_sizes)
__host__ __device__ constexpr UpperCoord operator+=(const UpperIndex& idx_up_diff)
{
static_assert(is_same<typename T::data_type, index_t>{} && T::GetSize() == nDim, "wrong!");
// For transformation of multi-index difference, not all transformation functions need to
// know the old lower-index or the old upper-index. We pass both of them to the
// transformation function. The transformation function itself decides to use them or not.
mCoordLow += tensor_desc_type::CalculateLowerIndexDiff(
idx_up_diff, GetIndex(), GetLowerCoordinate().GetIndex());
static_for<0, nDim, 1>{}([&](auto idim) {
// compiler should remove dead code path, because step_sizes is known at
// compile time
if(step_sizes[idim] != 0)
{
this->MoveOnDimension(idim, step_sizes[idim], integral_constant<bool, true>{});
}
});
// mIndexUp is updated here, but some (or all) of its entries may never be used
// compiler should remove those entries as dead code
mIndexUp += idx_up_diff;
return *this;
}
template <class T>
__host__ __device__ type operator-=(T step_sizes)
__host__ __device__ constexpr UpperCoord operator-=(const UpperIndex& idx_up_diff)
{
static_assert(is_same<typename T::data_type, index_t>{} && T::GetSize() == nDim, "wrong!");
mCoordLow -= tensor_desc_type::CalculateLowerIndexDiff(
idx_up_diff, GetIndex(), GetLowerCoordinate().GetIndex());
static_for<0, nDim, 1>{}([&](auto idim) {
// compiler should remove dead code path, because step_sizes is known at
// compile time
if(step_sizes[idim] != 0)
{
this->MoveOnDimension(idim, step_sizes[idim], integral_constant<bool, false>{});
}
});
// mIndex is updated here, but some (or all) of its entries may never be used
// compiler should remove those entries as dead code
mIndexUp -= idx_up_diff;
return *this;
}
template <class T>
__host__ __device__ constexpr type operator+(T step_sizes) const
__host__ __device__ constexpr UpperCoord operator+(const UpperIndex& idx_up_diff) const
{
type coord = *this;
coord += step_sizes;
return coord;
UpperCoord coord_up = *this;
coord_up += idx_up_diff;
return coord_up;
}
template <class T>
__host__ __device__ constexpr type operator-(T step_sizes) const
__host__ __device__ constexpr UpperCoord operator-(const UpperIndex& idx_up_diff) const
{
type coord = *this;
coord -= step_sizes;
return coord;
UpperCoord coord_up = *this;
coord_up -= idx_up_diff;
return coord_up;
}
__host__ __device__ static constexpr index_t RepositionOrigin() { return 0; }
// this function should be inexpensive, because there is no upper-to-lower index transformation
__host__ __device__ constexpr bool IsUpperIndexMappedToValidOffset() const
{
return tensor_desc_type::IsUpperIndexMappedToValidLowerIndex(GetIndex()) &&
mCoordLow.IsUpperIndexMappedToValidOffset();
}
private:
// Allocate register memory for all merged dimensions and normal dimensions.
// However, only those merged dimensions, whose index will be involved in arithmetic
// after the construction of this TensorCoordinate (e.g. when user move a slicing
// window on the merged dimension), will use these register memory.
// Let's hope compiler will optimize away those register memory allocated for normal
// dimensions, and those merged dimensions, that would never be involved in index
// arithmetic after construction of TensorCoordinate.
// TODO: refactor TensorCoordinate, after introducing the concept of "dimensions"
// and simplify implementation of ConstantMergedTensorDescriptor, so we don't need to
// count on compiler to optimize away those register memory for us
Array<index_t, nOriginalDim> mOriginalIndex;
Array<index_t, nDim> mPartialOffsets;
// complete offset
index_t mOffset;
// mIndexUp may be calculated and updated, however, the value of some (or all) of its entries
// may
// never be used. Compiler should be able to remove these entries as well as its calculation
// as dead code.
// TODO: make sure compiler indeed remove these dead code
UpperIndex mIndexUp;
LowerCoord mCoordLow;
};
template <class TensorDesc>
template <typename TensorDesc>
struct TensorCoordinate
{
private:
template <class... Ts>
template <typename... Ts>
__host__ __device__ static constexpr auto
MakeDummyTensorCoordinate(ConstantTensorDescriptor<Ts...>)
MakeDummyTensorCoordinate(NativeTensorDescriptor<Ts...>)
{
return NormalTensorCoordinate<ConstantTensorDescriptor<Ts...>>();
return NativeTensorCoordinate<NativeTensorDescriptor<Ts...>>(
make_zero_array<index_t, TensorDesc::GetNumOfDimension()>());
}
template <class... Ts>
template <typename... Ts>
__host__ __device__ static constexpr auto
MakeDummyTensorCoordinate(ConstantMergedTensorDescriptor<Ts...>)
MakeDummyTensorCoordinate(TransformedTensorDescriptor<Ts...>)
{
return MergedTensorCoordinate<ConstantMergedTensorDescriptor<Ts...>>();
return TransformedTensorCoordinate<TransformedTensorDescriptor<Ts...>>(
make_zero_array<index_t, TensorDesc::GetNumOfDimension()>());
}
public:
......
composable_kernel/include/tensor_description/tensor_coordinate_deprecated.hpp 0 → 100644
View file @ b12bbcee
#ifndef CK_TENSOR_COORDINATE_DEPRECATED_HPP
#define CK_TENSOR_COORDINATE_DEPRECATED_HPP
#include "common_header.hpp"
#include "ConstantTensorDescriptor.hpp"
#include "ConstantMergedTensorDescriptor.hpp"
namespace ck {
// TensorDesc is ConstantTensorDescriptor
template <class TensorDesc>
struct NormalTensorCoordinate_deprecated
{
using type = NormalTensorCoordinate_deprecated;
using tensor_desc_type = TensorDesc;
static constexpr index_t nDim = tensor_desc_type::GetNumOfDimension();
__host__
__device__ constexpr NormalTensorCoordinate_deprecated(Array<index_t, nDim> tensor_index)
: mOffset{tensor_desc_type::GetOffsetFromMultiIndex(tensor_index)}
{
}
template <class... Xs>
__host__ __device__ constexpr NormalTensorCoordinate_deprecated(Xs... xs)
: NormalTensorCoordinate_deprecated(Array<index_t, nDim>{xs...})
{
}
template <index_t... Xs>
__host__ __device__ constexpr NormalTensorCoordinate_deprecated(Sequence<Xs...>)
: NormalTensorCoordinate_deprecated(Array<index_t, nDim>{Xs...})
{
}
__host__ __device__ constexpr index_t GetOffset() const { return mOffset; }
// T is Array or Sequence
template <class T>
__host__ __device__ type operator+=(T step_sizes)
{
static_assert(is_same<typename T::data_type, index_t>{} && T::GetSize() == nDim, "wrong!");
mOffset += tensor_desc_type::GetOffsetFromMultiIndex(step_sizes);
return *this;
}
template <class T>
__host__ __device__ type operator-=(T step_sizes)
{
static_assert(is_same<typename T::data_type, index_t>{} && T::GetSize() == nDim, "wrong!");
mOffset -= tensor_desc_type::GetOffsetFromMultiIndex(step_sizes);
return *this;
}
template <class T>
__host__ __device__ constexpr type operator+(T step_sizes) const
{
type coord = *this;
coord += step_sizes;
return coord;
}
template <class T>
__host__ __device__ constexpr type operator-(T step_sizes) const
{
type coord = *this;
coord -= step_sizes;
return coord;
}
// reposition point of origin, and return compensated offset.
// This is a hack to reduce index calculation during looping over
// a tensor whose origin is this TensorCoordinate. It does so, by spitting
// out the run-time offset to the pointer (to the tensor data) held by this
// TensorCoordiante, so the caller can add the offset into the run-time pointer of
// the data, so only 1 run-time variable (update pointer) is needed, instead
// of 2 run-time variables (old pointer and this offset)
// TODO: after introducing the concept of "run-time tensor view", which contains the
// run-time pointer to the data, always keep track of the pointer, instead of both
// offset and the pointer. This also bring additional benefit that we don't need to
// worry the offset might underflow (because offset is unsigned integer) when updating it.
__host__ __device__ constexpr index_t RepositionOrigin()
{
index_t offset_diff = mOffset;
mOffset = 0;
return offset_diff;
}
private:
index_t mOffset;
};
// TensorDesc is ConstantMergedTensorDescriptor
template <class TensorDesc>
struct MergedTensorCoordinate
{
using type = MergedTensorCoordinate;
using tensor_desc_type = TensorDesc;
static constexpr index_t nDim = tensor_desc_type::GetNumOfDimension();
static constexpr index_t nOriginalDim =
tensor_desc_type::GetOriginalTensorDescriptor().GetNumOfDimension();
__host__ __device__ constexpr MergedTensorCoordinate(Array<index_t, nDim> tensor_index)
: mOriginalIndex{tensor_desc_type::GetOriginalMultiIndexFromMultiIndex(tensor_index)}
{
// partial offset on each dimension
static_for<0, nDim, 1>{}([&](auto idim) {
constexpr auto partial_original_dims =
tensor_desc_type::GetContainedOriginalDimensions(idim);
constexpr auto partial_original_desc =
tensor_desc_type::GetOriginalTensorDescriptor().Extract(partial_original_dims);
mPartialOffsets(idim) = partial_original_desc.GetOffsetFromMultiIndex(
extract_array(mOriginalIndex, partial_original_dims));
});
// complete offset
mOffset =
accumulate_on_array(mPartialOffsets, math::plus<index_t>{}, static_cast<index_t>(0));
}
template <class... Xs>
__host__ __device__ constexpr MergedTensorCoordinate(Xs... xs)
: MergedTensorCoordinate(Array<index_t, nDim>{xs...})
{
}
__host__ __device__ constexpr index_t GetOffset() const { return mOffset; }
template <class IDim, class T, bool PositiveDirection>
__host__ __device__ void
MoveOnDimension(IDim idim_, T step_size, integral_constant<bool, PositiveDirection>)
{
constexpr auto idim = idim_;
// if step_size is known at compile time
static_if<is_static<T>::value>{}(
[&](auto) { static_if<T{} == 0>{}([&](auto) { return; }); });
// update original index
static_if<tensor_desc_type::ContainMultipleOriginalDimensions(idim)>{}([&](auto) {
constexpr auto partial_original_dims =
tensor_desc_type::GetContainedOriginalDimensions(idim);
constexpr index_t ndim_partial_original = partial_original_dims.GetSize();
constexpr auto partial_original_desc =
tensor_desc_type::GetOriginalTensorDescriptor().Extract(partial_original_dims);
const auto partial_original_step_sizes =
partial_original_desc.GetMultiIndexFrom1dIndex(step_size);
// update partial original multi-id
auto partial_original_id = extract_array(mOriginalIndex, partial_original_dims);
static_if<PositiveDirection>{}([&](auto) {
partial_original_id += partial_original_step_sizes;
bool carry = false;
// do carry check in reversed order, starting from lowest dimension
// don't check the highest dimension
static_for<0, ndim_partial_original - 1, 1>{}([&](auto IReverse) {
constexpr index_t i = ndim_partial_original - 1 - IReverse;
if(carry)
{
++partial_original_id(i);
}
carry = false;
if(partial_original_id[i] >= partial_original_desc.GetLength(i))
{
partial_original_id(i) -= partial_original_desc.GetLength(i);
carry = true;
}
});
// highest dimension
if(carry)
{
++partial_original_id(0);
}
}).Else([&](auto) {
// shift up multi-id to avoid unsigned integer underflow during intermediate
// calculations. After the shift, should have new_multi_id[...] >= 1
partial_original_id +=
partial_original_desc.GetLengths() - partial_original_step_sizes;
bool borrow = false;
// do borrow check in reversed order, starting from lowest dimension
// don't check the highest dimension
static_for<0, ndim_partial_original - 1, 1>{}([&](auto IReverse) {
constexpr index_t i = ndim_partial_original - 1 - IReverse;
if(borrow)
{
--partial_original_id(i);
}
borrow = false;
if(partial_original_id[i] < partial_original_desc.GetLength(i))
{
partial_original_id(i) += partial_original_desc.GetLength(i);
borrow = true;
}
});
// highest dimension
if(borrow)
{
--partial_original_id(0);
}
// shift back down multi-id
// here, should have new_multi_id[...] >= GetLengths()
partial_original_id = partial_original_id - partial_original_desc.GetLengths();
});
// update "mOriginalIndex"
static_for<0, ndim_partial_original, 1>{}([&](auto I) {
constexpr auto idim_original = partial_original_dims[I];
mOriginalIndex(idim_original) = partial_original_id[I];
});
// calculate new partial offset on this merged dimension
const index_t old_partial_offset = mPartialOffsets[idim];
mPartialOffsets(idim) =
partial_original_desc.GetOffsetFromMultiIndex(partial_original_id);
// update "mThreadSrcOffset", do "+" before "-" to avoid underflow
mOffset = (mOffset + mPartialOffsets[idim]) - old_partial_offset;
}).Else([&](auto fwd) {
static_if<PositiveDirection>{}([&](auto) {
mOffset += step_size * fwd(tensor_desc_type{}).GetStride(idim);
}).Else([&](auto) { mOffset -= step_size * fwd(tensor_desc_type{}).GetStride(idim); });
});
}
// T is Array or Sequence
template <class T>
__host__ __device__ type operator+=(T step_sizes)
{
static_assert(is_same<typename T::data_type, index_t>{} && T::GetSize() == nDim, "wrong!");
static_for<0, nDim, 1>{}([&](auto idim) {
// compiler should remove dead code path, because step_sizes is known at
// compile time
if(step_sizes[idim] != 0)
{
this->MoveOnDimension(idim, step_sizes[idim], integral_constant<bool, true>{});
}
});
return *this;
}
template <class T>
__host__ __device__ type operator-=(T step_sizes)
{
static_assert(is_same<typename T::data_type, index_t>{} && T::GetSize() == nDim, "wrong!");
static_for<0, nDim, 1>{}([&](auto idim) {
// compiler should remove dead code path, because step_sizes is known at
// compile time
if(step_sizes[idim] != 0)
{
this->MoveOnDimension(idim, step_sizes[idim], integral_constant<bool, false>{});
}
});
return *this;
}
template <class T>
__host__ __device__ constexpr type operator+(T step_sizes) const
{
type coord = *this;
coord += step_sizes;
return coord;
}
template <class T>
__host__ __device__ constexpr type operator-(T step_sizes) const
{
type coord = *this;
coord -= step_sizes;
return coord;
}
__host__ __device__ static constexpr index_t RepositionOrigin() { return 0; }
private:
// Allocate register memory for all merged dimensions and normal dimensions.
// However, only those merged dimensions, whose index will be involved in arithmetic
// after the construction of this TensorCoordinate (e.g. when user move a slicing
// window on the merged dimension), will use these register memory.
// Let's hope compiler will optimize away those register memory allocated for normal
// dimensions, and those merged dimensions, that would never be involved in index
// arithmetic after construction of TensorCoordinate.
// TODO: refactor TensorCoordinate, after introducing the concept of "dimensions"
// and simplify implementation of ConstantMergedTensorDescriptor, so we don't need to
// count on compiler to optimize away those register memory for us
Array<index_t, nOriginalDim> mOriginalIndex;
Array<index_t, nDim> mPartialOffsets;
// complete offset
index_t mOffset;
};
template <class TensorDesc>
struct TensorCoordinate_deprecated
{
private:
template <class... Ts>
__host__ __device__ static constexpr auto
MakeDummyTensorCoordinate(ConstantTensorDescriptor<Ts...>)
{
return NormalTensorCoordinate_deprecated<ConstantTensorDescriptor<Ts...>>();
}
template <class... Ts>
__host__ __device__ static constexpr auto
MakeDummyTensorCoordinate(ConstantMergedTensorDescriptor<Ts...>)
{
return MergedTensorCoordinate<ConstantMergedTensorDescriptor<Ts...>>();
}
public:
using type = decltype(MakeDummyTensorCoordinate(TensorDesc{}));
};
} // namespace ck
#endif
composable_kernel/include/tensor_description/tensor_coordinate_helper.hpp
View file @ b12bbcee
......@@ -9,7 +9,7 @@ template <typename TensorDesc>
__host__ __device__ constexpr auto
make_tensor_coordinate_v2(TensorDesc, MultiIndex<TensorDesc::GetNumOfDimension()> idx)
{
return typename TensorCoordinate_v2<TensorDesc>::type(idx);
return typename TensorCoordinate<TensorDesc>::type(idx);
}
} // namespace ck
......
composable_kernel/include/tensor_description/tensor_coordinate_v2.hpp deleted 100644 → 0
View file @ 51a9fa1d
#ifndef CK_TENSOR_COORDINATE_V2_HPP
#define CK_TENSOR_COORDINATE_V2_HPP
#include "common_header.hpp"
#include "dimension.hpp"
#include "multi_index_transform.hpp"
#include "tensor_descriptor.hpp"
namespace ck {
template <typename TensorDesc>
struct TensorCoordinate_v2;
template <typename NativeTensorDesc>
struct NativeTensorCoordinate
{
using type = NativeTensorCoordinate;
using tensor_desc_type = NativeTensorDesc;
static constexpr index_t nDim = tensor_desc_type::GetNumOfDimension();
using Index = MultiIndex<nDim>;
__host__ __device__ constexpr NativeTensorCoordinate(Index idx)
: mIndex(idx), mOffset(tensor_desc_type::CalculateOffset(idx))
{
}
template <typename... Xs>
__host__ __device__ constexpr NativeTensorCoordinate(Xs... xs)
: NativeTensorCoordinate(Index{xs...})
{
}
template <index_t... Xs>
__host__ __device__ constexpr NativeTensorCoordinate(Sequence<Xs...>)
: NativeTensorCoordinate(Index{Xs...})
{
}
__host__ __device__ static constexpr auto GetTensorDescriptor() { return tensor_desc_type{}; }
__host__ __device__ constexpr const Index& GetIndex() const { return mIndex; }
__host__ __device__ constexpr const index_t& GetOffset() const { return mOffset; }
__host__ __device__ constexpr type operator+=(const Index& idx_diff)
{
// mIndex is updated here, but some (or all) of its entries may never be used
// compiler should remove those entries as dead code
mIndex += idx_diff;
mOffset += tensor_desc_type::CalculateOffsetDiff(idx_diff);
return *this;
}
__host__ __device__ constexpr type operator-=(const Index& idx_diff)
{
// mIndex is updated here, but some (or all) of its entries may never be used
// compiler should remove those entries as dead code
mIndex -= idx_diff;
mOffset -= tensor_desc_type::CalculateOffsetDiff(idx_diff);
return *this;
}
__host__ __device__ constexpr type operator+(const Index& idx_diff) const
{
type coord = *this;
coord += idx_diff;
return coord;
}
__host__ __device__ constexpr type operator-(const Index& idx_diff) const
{
type coord = *this;
coord -= idx_diff;
return coord;
}
__host__ __device__ static constexpr bool IsUpperIndexMappedToValidOffset() { return true; }
private:
// mIndex may be saved and updated, however, the value of some (or all) of its entries may
// never be used. Compiler should be able to remove these entries as well as its calculation
// as dead code.
// TODO: make sure compiler indeed remove these dead code
Index mIndex;
index_t mOffset;
};
template <typename TransformedTensorDesc>
struct TransformedTensorCoordinate
{
using tensor_desc_type = TransformedTensorDesc;
using LowerCoord =
typename TensorCoordinate_v2<decltype(tensor_desc_type::GetLowerTensorDescriptor())>::type;
using UpperCoord = TransformedTensorCoordinate;
static constexpr index_t nDim = tensor_desc_type::GetNumOfDimension();
using UpperIndex = MultiIndex<nDim>;
__host__ __device__ constexpr TransformedTensorCoordinate(UpperIndex idx)
: mIndexUp{idx}, mCoordLow{tensor_desc_type::CalculateLowerIndex(idx)}
{
}
template <typename... Xs>
__host__ __device__ constexpr TransformedTensorCoordinate(Xs... xs)
: TransformedTensorCoordinate(UpperIndex{xs...})
{
}
template <index_t... Xs>
__host__ __device__ constexpr TransformedTensorCoordinate(Sequence<Xs...>)
: TransformedTensorCoordinate(UpperIndex{Xs...})
{
}
__host__ __device__ static constexpr auto GetTensorDescriptor() { return tensor_desc_type{}; }
__host__ __device__ constexpr const LowerCoord& GetLowerCoordinate() const { return mCoordLow; }
__host__ __device__ constexpr const UpperIndex& GetUpperIndex() const { return mIndexUp; }
__host__ __device__ constexpr const UpperIndex& GetIndex() const { return GetUpperIndex(); }
__host__ __device__ constexpr const index_t& GetOffset() const
{
return GetLowerCoordinate().GetOffset();
}
__host__ __device__ constexpr UpperCoord operator+=(const UpperIndex& idx_up_diff)
{
// For transformation of multi-index difference, not all transformation functions need to
// know the old lower-index or the old upper-index. We pass both of them to the
// transformation function. The transformation function itself decides to use them or not.
mCoordLow += tensor_desc_type::CalculateLowerIndexDiff(
idx_up_diff, GetIndex(), GetLowerCoordinate().GetIndex());
// mIndexUp is updated here, but some (or all) of its entries may never be used
// compiler should remove those entries as dead code
mIndexUp += idx_up_diff;
return *this;
}
__host__ __device__ constexpr UpperCoord operator-=(const UpperIndex& idx_up_diff)
{
mCoordLow -= tensor_desc_type::CalculateLowerIndexDiff(
idx_up_diff, GetIndex(), GetLowerCoordinate().GetIndex());
// mIndex is updated here, but some (or all) of its entries may never be used
// compiler should remove those entries as dead code
mIndexUp -= idx_up_diff;
return *this;
}
__host__ __device__ constexpr UpperCoord operator+(const UpperIndex& idx_up_diff) const
{
UpperCoord coord_up = *this;
coord_up += idx_up_diff;
return coord_up;
}
__host__ __device__ constexpr UpperCoord operator-(const UpperIndex& idx_up_diff) const
{
UpperCoord coord_up = *this;
coord_up -= idx_up_diff;
return coord_up;
}
// this function should be inexpensive, because there is no upper-to-lower index transformation
__host__ __device__ constexpr bool IsUpperIndexMappedToValidOffset() const
{
return tensor_desc_type::IsUpperIndexMappedToValidLowerIndex(GetIndex()) &&
mCoordLow.IsUpperIndexMappedToValidOffset();
}
private:
// mIndexUp may be calculated and updated, however, the value of some (or all) of its entries
// may
// never be used. Compiler should be able to remove these entries as well as its calculation
// as dead code.
// TODO: make sure compiler indeed remove these dead code
UpperIndex mIndexUp;
LowerCoord mCoordLow;
};
template <typename TensorDesc>
struct TensorCoordinate_v2
{
private:
template <typename... Ts>
__host__ __device__ static constexpr auto
MakeDummyTensorCoordinate(NativeTensorDescriptor<Ts...>)
{
return NativeTensorCoordinate<NativeTensorDescriptor<Ts...>>(
make_zero_array<index_t, TensorDesc::GetNumOfDimension()>());
}
template <typename... Ts>
__host__ __device__ static constexpr auto
MakeDummyTensorCoordinate(TransformedTensorDescriptor<Ts...>)
{
return TransformedTensorCoordinate<TransformedTensorDescriptor<Ts...>>(
make_zero_array<index_t, TensorDesc::GetNumOfDimension()>());
}
public:
using type = decltype(MakeDummyTensorCoordinate(TensorDesc{}));
};
} // namespace ck
#endif
composable_kernel/include/tensor_description/tensor_view.hpp
View file @ b12bbcee
......@@ -4,7 +4,7 @@
#include "common_header.hpp"
#include "ConstantTensorDescriptor.hpp"
#include "ConstantMergedTensorDescriptor.hpp"
#include "tensor_coordinate.hpp"
#include "tensor_coordinate_deprecated.hpp"
namespace ck {
......@@ -14,7 +14,7 @@ struct NormalTensorView
{
using type = NormalTensorView;
using tensor_desc_type = TensorDesc;
using coordinate_type = typename NormalTensorCoordinate<TensorDesc>::type;
using coordinate_type = typename NormalTensorCoordinate_deprecated<TensorDesc>::type;
using data_type = TData;
static constexpr auto nDim = TensorDesc::GetNumOfDimension();
......
composable_kernel/include/tensor_description/tensor_visit.hpp
View file @ b12bbcee
......@@ -5,7 +5,7 @@
#include "dimension.hpp"
#include "dimension_transform.hpp"
#include "tensor_descriptor.hpp"
#include "tensor_coordinate_v2.hpp"
#include "tensor_coordinate.hpp"
namespace ck {
......@@ -13,7 +13,7 @@ template <class TensorDescriptor>
struct TensorVisit
{
using Index = typename TensorDescriptor::Index;
using Coordinate = typename TensorCoordinate_v2<TensorDescriptor>::type;
using Coordinate = typename TensorCoordinate<TensorDescriptor>::type;
__host__ __device__ static void Run_v1(Index idx_begin)
{
......
driver/include/device_convolution_implicit_gemm_v4r1_nchw_kcyx_nkhw.hpp
View file @ b12bbcee
......@@ -3,7 +3,7 @@
#include "device.hpp"
#include "tensor.hpp"
#include "gridwise_convolution_kernel_wrapper.hpp"
#include "gridwise_convolution_implicit_gemm_v4r1_nchw_kcyx_nkhw.hpp"
//#include "gridwise_convolution_implicit_gemm_v4r1_nchw_kcyx_nkhw.hpp"
#include "gridwise_convolution_implicit_gemm_v4r1_nchw_kcyx_nkhw_lds_double_buffer.hpp"
template <class T,
......
driver/include/device_convolution_implicit_gemm_v4r4_nchw_kcyx_nkhw.hpp
View file @ b12bbcee
......@@ -3,7 +3,7 @@
#include "device.hpp"
#include "tensor.hpp"
#include "gridwise_convolution_kernel_wrapper.hpp"
#include "gridwise_convolution_implicit_gemm_v4r4_nchw_kcyx_nkhw.hpp"
//#include "gridwise_convolution_implicit_gemm_v4r4_nchw_kcyx_nkhw.hpp"
#include "gridwise_convolution_implicit_gemm_v4r4_nchw_kcyx_nkhw_lds_double_buffer.hpp"
using namespace ck;
......@@ -164,7 +164,7 @@ void device_convolution_implicit_gemm_v4r4_nchw_kcyx_nkhw(InDesc,
printf("%s: BlockSize %u, GridSize %u \n", __func__, BlockSize, GridSize);
constexpr auto gridwise_conv =
#if 1
#if 0
GridwiseConvolutionImplicitGemm_v4r4_nchw_kcyx_nkhw
#else
GridwiseConvolutionImplicitGemm_v4r4_nchw_kcyx_nkhw_lds_double_buffer
......
driver/include/device_convolution_implicit_gemm_v4r4_nchw_kcyx_nkhw_padded.hpp
View file @ b12bbcee
......@@ -51,7 +51,7 @@ void device_convolution_implicit_gemm_v4r4_nchw_kcyx_nkhw_padded(InDesc,
wei_kcyx_device_buf.ToDevice(wei_kcyx.mData.data());
out_nkhw_device_buf.ToDevice(out_nkhw.mData.data());
#if 0
#if 1
constexpr index_t BlockSize = 256;
constexpr index_t BPerBlock = 128;
......
driver/src/driver.cpp
View file @ b12bbcee
......@@ -14,11 +14,11 @@
//#include "device_convolution_implicit_gemm_v1_nchw_cyxk_nkhw.hpp"
//#include "device_convolution_implicit_gemm_v2_chwn_cyxk_khwn.hpp"
//#include "device_convolution_implicit_gemm_v3_nchw_cyxk_nkhw.hpp"
//#include "device_convolution_implicit_gemm_v4r1_nchw_kcyx_nkhw.hpp"
#include "device_convolution_implicit_gemm_v4r1_nchw_kcyx_nkhw.hpp"
#include "device_convolution_implicit_gemm_v4r1_nchw_kcyx_nkhw_padded.hpp"
//#include "device_convolution_implicit_gemm_v4r2_nchw_kcyx_nkhw.hpp"
//#include "device_convolution_implicit_gemm_v4r3_nchw_kcyx_nkhw.hpp"
//#include "device_convolution_implicit_gemm_v4r4_nchw_kcyx_nkhw.hpp"
#include "device_convolution_implicit_gemm_v4r4_nchw_kcyx_nkhw.hpp"
#include "device_convolution_implicit_gemm_v4r4_nchw_kcyx_nkhw_padded.hpp"
struct GeneratorTensor_1
......@@ -103,7 +103,7 @@ int main(int argc, char* argv[])
using LeftPads = Sequence<0, 0>;
using RightPads = Sequence<0, 0>;
#elif 1
#elif 0
// 1x1 filter, 8x8 image
// cudnn@V100 68%, ck@V100 72%, ck@P100 52%, ck@VII 42%
constexpr index_t N = 64;
......@@ -295,7 +295,7 @@ int main(int argc, char* argv[])
using LeftPads = Sequence<0, 0>;
using RightPads = Sequence<0, 0>;
#elif 0
#elif 1
// 3x3 filter, 2x2 stride, 35x35 input, 17x17 output
// cudnn@V100 90%, ck@V100 93%, ck@P100 83%, ck@VII 81%
constexpr index_t N = 128;
......@@ -341,7 +341,7 @@ int main(int argc, char* argv[])
using LeftPads = Sequence<3, 0>;
using RightPads = Sequence<3, 0>;
#elif 1
#elif 0
// 1x7 filter, 0x3 pad, 17x17 input
constexpr index_t N = 128;
constexpr index_t C = 128;
......
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