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Unverified Commit 52c3fe05 authored by Chao Liu's avatar Chao Liu Committed by GitHub
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Refactor for MIOpen integration (#4) 

Refactor, so can bring multi-index transformation and padding support into MIOpen
parent 9aaeacc8
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Showing with 1341 additions and 2038 deletions
composable_kernel/include/tensor_description/ConstantMatrixDescriptor.hpp
View file @ 52c3fe05
......@@ -2,7 +2,7 @@
#define CK_CONSTANT_MATRIX_DESCRIPTOR_HPP
#include "common_header.hpp"
#include "ConstantTensorDescriptor.hpp"
#include "ConstantTensorDescriptor_deprecated.hpp"
#include "tensor_descriptor.hpp"
namespace ck {
......@@ -32,6 +32,11 @@ struct ConstantMatrixDescriptor
return irow * RowStride_ + icol;
}
__host__ __device__ static index_t CalculateOffset(index_t irow, index_t icol)
{
return GetOffsetFromMultiIndex(irow, icol);
}
template <index_t SubNRow, index_t SubNCol>
__host__ __device__ static constexpr auto MakeSubMatrixDescriptor(Number<SubNRow>,
Number<SubNCol>)
......@@ -54,9 +59,10 @@ __host__ __device__ constexpr auto
}
template <typename... Ts>
__host__ __device__ constexpr auto make_ConstantMatrixDescriptor(ConstantTensorDescriptor<Ts...>)
__host__ __device__ constexpr auto
make_ConstantMatrixDescriptor(ConstantTensorDescriptor_deprecated<Ts...>)
{
using TDesc = ConstantTensorDescriptor<Ts...>;
using TDesc = ConstantTensorDescriptor_deprecated<Ts...>;
static_assert(TDesc::GetNumOfDimension() == 2, "wrong");
static_assert(TDesc::GetStrides()[1] == 1, "wrong");
return ConstantMatrixDescriptor<TDesc::GetLengths()[0],
......
composable_kernel/include/tensor_description/ConstantMergedTensorDescriptor.hpp → composable_kernel/include/tensor_description/ConstantMergedTensorDescriptor_deprecated.hpp
View file @ 52c3fe05
#ifndef CK_CONSTANT_MERGED_TENSOR_DESCRIPTOR_HPP
#define CK_CONSTANT_MERGED_TENSOR_DESCRIPTOR_HPP
#ifndef CK_CONSTANT_MERGED_TENSOR_DESCRIPTOR_DEPRECATED_HPP
#define CK_CONSTANT_MERGED_TENSOR_DESCRIPTOR_DEPRECATED_HPP
#include "common_header.hpp"
#include "ConstantTensorDescriptor.hpp"
#include "ConstantTensorDescriptor_deprecated.hpp"
namespace ck {
// OriginalTensorDesc : ConstantTensorDescriptor<...>
// OriginalTensorDesc : ConstantTensorDescriptor_deprecated<...>
// it's the tensor whose dimensions are to be merged
// OriginalDimMergeSeqs : Sequence<...>...
// each is a sequence of original dimensions (of OriginalTensorDesc) to be merged
template <class OriginalTensorDesc, class... OriginalDimMergeSeqs>
struct ConstantMergedTensorDescriptor
struct ConstantMergedTensorDescriptor_deprecated
{
using Type = ConstantMergedTensorDescriptor;
using Type = ConstantMergedTensorDescriptor_deprecated;
static constexpr auto mOriginalDimMergeSeqs = std::tuple<OriginalDimMergeSeqs...>{};
static constexpr index_t nDim = sizeof...(OriginalDimMergeSeqs);
static constexpr index_t nOriginalDim = OriginalTensorDesc::GetNumOfDimension();
__host__ __device__ constexpr ConstantMergedTensorDescriptor()
__host__ __device__ constexpr ConstantMergedTensorDescriptor_deprecated()
{
static_assert(nDim <= nOriginalDim, "wrong!");
......@@ -189,7 +189,7 @@ struct ConstantMergedTensorDescriptor
{
constexpr auto lengths = GetLengths();
constexpr auto strides = calculate_tensor_strides_packed(lengths);
return ConstantTensorDescriptor<decltype(lengths), decltype(strides)>{};
return ConstantTensorDescriptor_deprecated<decltype(lengths), decltype(strides)>{};
}
};
......@@ -197,7 +197,7 @@ template <class OriginalTensorDesc, class... OriginalDimMergeSeqs>
__host__ __device__ constexpr auto make_ConstantMergedTensorDescriptor(OriginalTensorDesc,
OriginalDimMergeSeqs...)
{
return ConstantMergedTensorDescriptor<OriginalTensorDesc, OriginalDimMergeSeqs...>{};
return ConstantMergedTensorDescriptor_deprecated<OriginalTensorDesc, OriginalDimMergeSeqs...>{};
}
template <class TDesc>
......
composable_kernel/include/tensor_description/ConstantTensorDescriptor.hpp → composable_kernel/include/tensor_description/ConstantTensorDescriptor_deprecated.hpp
View file @ 52c3fe05
#ifndef CK_CONSTANT_TENSOR_DESCRIPTOR_HPP
#define CK_CONSTANT_TENSOR_DESCRIPTOR_HPP
#ifndef CK_CONSTANT_TENSOR_DESCRIPTOR_DEPRECATED_HPP
#define CK_CONSTANT_TENSOR_DESCRIPTOR_DEPRECATED_HPP
#include "common_header.hpp"
namespace ck {
template <class Lengths>
__host__ __device__ constexpr auto calculate_tensor_strides_packed_old(Lengths)
__host__ __device__ constexpr auto calculate_tensor_strides_packed_deprecated(Lengths)
{
return reverse_inclusive_scan_sequence(
Lengths{}.PopFront(), math::multiplies<index_t>{}, Number<1>{})
......@@ -19,18 +19,18 @@ __host__ __device__ constexpr auto calculate_tensor_strides_aligned_old(Lengths,
constexpr index_t L_back_align =
Align * math::integer_divide_ceiler<index_t>{}(Lengths{}.Back(), Align);
return calculate_tensor_strides_packed_old(
return calculate_tensor_strides_packed_deprecated(
Lengths{}.Modify(Number<Lengths{}.GetSize() - 1>{}, Number<L_back_align>{}));
}
template <class Lengths, class Strides>
struct ConstantTensorDescriptor
struct ConstantTensorDescriptor_deprecated
{
using Type = ConstantTensorDescriptor;
using Type = ConstantTensorDescriptor_deprecated;
static constexpr index_t nDim = Lengths::GetSize();
__host__ __device__ constexpr ConstantTensorDescriptor()
__host__ __device__ constexpr ConstantTensorDescriptor_deprecated()
{
static_assert(Lengths::GetSize() == Strides::GetSize(), "nDim not consistent");
}
......@@ -186,7 +186,7 @@ struct ConstantTensorDescriptor
{
Array<index_t, nDim> multi_id;
using PackedStrides = decltype(calculate_tensor_strides_packed_old(GetLengths()));
using PackedStrides = decltype(calculate_tensor_strides_packed_deprecated(GetLengths()));
// calculate index in each of the dimensions in the order of their dimension
static_for<0, nDim - 1, 1>{}(lambda_GetMultiIndexFrom1dIndex<PackedStrides>(id, multi_id));
......@@ -284,7 +284,7 @@ struct ConstantTensorDescriptor
using extract_lengths = decltype(Lengths::Extract(extract_dims...));
using extract_strides = decltype(Strides::Extract(extract_dims...));
return ConstantTensorDescriptor<extract_lengths, extract_strides>{};
return ConstantTensorDescriptor_deprecated<extract_lengths, extract_strides>{};
}
template <index_t... IDims>
......@@ -294,13 +294,13 @@ struct ConstantTensorDescriptor
}
template <class... Ts>
__host__ __device__ static constexpr auto Embed(ConstantTensorDescriptor<Ts...>)
__host__ __device__ static constexpr auto Embed(ConstantTensorDescriptor_deprecated<Ts...>)
{
using leaf_tensor = ConstantTensorDescriptor<Ts...>;
using leaf_tensor = ConstantTensorDescriptor_deprecated<Ts...>;
return ConstantTensorDescriptor<decltype(GetLengths().PushBack(leaf_tensor::GetLengths())),
decltype(
GetStrides().PushBack(leaf_tensor::GetStrides()))>{};
return ConstantTensorDescriptor_deprecated<
decltype(GetLengths().PushBack(leaf_tensor::GetLengths())),
decltype(GetStrides().PushBack(leaf_tensor::GetStrides()))>{};
}
template <index_t IDimVector, index_t DataPerVector>
......@@ -351,7 +351,7 @@ struct ConstantTensorDescriptor
using vectorized_strides =
decltype((Strides{} / Number<DataPerVector>{}).Modify(Number<IDim>{}, Number<1>{}));
return ConstantTensorDescriptor<vectorized_lengths, vectorized_strides>{};
return ConstantTensorDescriptor_deprecated<vectorized_lengths, vectorized_strides>{};
}
template <index_t IDim, index_t SliceLen>
......@@ -359,7 +359,7 @@ struct ConstantTensorDescriptor
{
using slice_lengths = decltype(Lengths::Modify(Number<IDim>{}, Number<SliceLen>{}));
return ConstantTensorDescriptor<slice_lengths, Strides>{};
return ConstantTensorDescriptor_deprecated<slice_lengths, Strides>{};
}
template <index_t... Is>
......@@ -367,7 +367,7 @@ struct ConstantTensorDescriptor
{
static_assert(slice_lengths.GetSize() == nDim, "wrong!");
return ConstantTensorDescriptor<decltype(slice_lengths), Strides>{};
return ConstantTensorDescriptor_deprecated<decltype(slice_lengths), Strides>{};
}
template <index_t IDim, index_t SliceLength, index_t SliceStride>
......@@ -379,7 +379,7 @@ struct ConstantTensorDescriptor
using new_lengths = decltype(Lengths::Modify(Number<IDim>{}, Number<SliceLength>{}));
using new_strides = decltype(Strides::Modify(Number<IDim>{}, Number<new_stride>{}));
return ConstantTensorDescriptor<new_lengths, new_strides>{};
return ConstantTensorDescriptor_deprecated<new_lengths, new_strides>{};
}
template <index_t IDim, index_t... FoldIntervals>
......@@ -418,7 +418,7 @@ struct ConstantTensorDescriptor
constexpr auto new_strides =
GetStrides().Extract(left).PushBack(fold_strides).PushBack(GetStrides().Extract(right));
return ConstantTensorDescriptor<decltype(new_lengths), decltype(new_strides)>{};
return ConstantTensorDescriptor_deprecated<decltype(new_lengths), decltype(new_strides)>{};
}
template <index_t IDim, index_t... FoldIntervals>
......@@ -462,26 +462,28 @@ struct ConstantTensorDescriptor
.PushBack(Number<unfold_stride>{})
.PushBack(GetStrides().Extract(right));
return ConstantTensorDescriptor<decltype(new_lengths), decltype(new_strides)>{};
return ConstantTensorDescriptor_deprecated<decltype(new_lengths), decltype(new_strides)>{};
}
__host__ __device__ static constexpr auto Pack()
{
using packed_strides = decltype(calculate_tensor_strides_packed_old(Lengths{}));
return ConstantTensorDescriptor<Lengths, packed_strides>{};
using packed_strides = decltype(calculate_tensor_strides_packed_deprecated(Lengths{}));
return ConstantTensorDescriptor_deprecated<Lengths, packed_strides>{};
}
template <class MapNew2Old>
__host__ __device__ static constexpr auto ReorderGivenNew2Old(MapNew2Old)
{
return ConstantTensorDescriptor<decltype(Lengths::ReorderGivenNew2Old(MapNew2Old{})),
return ConstantTensorDescriptor_deprecated<
decltype(Lengths::ReorderGivenNew2Old(MapNew2Old{})),
decltype(Strides::ReorderGivenNew2Old(MapNew2Old{}))>{};
}
template <class MapOld2New>
__host__ __device__ static constexpr auto ReorderGivenOld2New(MapOld2New)
{
return ConstantTensorDescriptor<decltype(Lengths::ReorderGivenOld2New(MapOld2New{})),
return ConstantTensorDescriptor_deprecated<
decltype(Lengths::ReorderGivenOld2New(MapOld2New{})),
decltype(Strides::ReorderGivenOld2New(MapOld2New{}))>{};
}
};
......@@ -489,27 +491,26 @@ struct ConstantTensorDescriptor
template <class Lengths>
__host__ __device__ constexpr auto make_ConstantTensorDescriptor_packed(Lengths)
{
using Strides = decltype(calculate_tensor_strides_packed_old(Lengths{}));
return ConstantTensorDescriptor<Lengths, Strides>{};
using Strides = decltype(calculate_tensor_strides_packed_deprecated(Lengths{}));
return ConstantTensorDescriptor_deprecated<Lengths, Strides>{};
}
template <class Lengths, class Strides>
__host__ __device__ constexpr auto make_ConstantTensorDescriptor(Lengths, Strides)
{
return ConstantTensorDescriptor<Lengths, Strides>{};
return ConstantTensorDescriptor_deprecated<Lengths, Strides>{};
}
template <class Lengths, index_t Align>
__host__ __device__ constexpr auto make_ConstantTensorDescriptor_aligned(Lengths, Number<Align>)
{
using Strides = decltype(calculate_tensor_strides_aligned_old(Lengths{}, Number<Align>{}));
return ConstantTensorDescriptor<Lengths, Strides>{};
return ConstantTensorDescriptor_deprecated<Lengths, Strides>{};
}
template <index_t... Lengths, index_t... Strides>
__host__ __device__ void
print_ConstantTensorDescriptor(const char* s,
ConstantTensorDescriptor<Sequence<Lengths...>, Sequence<Strides...>>)
__host__ __device__ void print_ConstantTensorDescriptor(
const char* s, ConstantTensorDescriptor_deprecated<Sequence<Lengths...>, Sequence<Strides...>>)
{
constexpr index_t ndim = sizeof...(Lengths);
......
composable_kernel/include/tensor_description/print_tensor_descriptor.hpp 0 → 100644
View file @ 52c3fe05
#ifndef CK_PRINT_TENSOR_DESCRIPTOR_HPP
#define CK_PRINT_TENSOR_DESCRIPTOR_HPP
#include "common_header.hpp"
#include "tensor_descriptor.hpp"
namespace ck {
template <typename... NativeDimensions>
__host__ __device__ void
print_tensor_descriptor(const char* s, const NativeTensorDescriptor<NativeDimensions...>& desc)
{
print_tensor_descriptor_impl(s, desc.GetLengths(), desc.GetStrides());
}
template <typename... Ts>
__host__ __device__ void print_tensor_descriptor(const char* s,
const TransformedTensorDescriptor<Ts...>& desc)
{
print_tensor_descriptor_impl(s, desc.GetLengths());
}
template <index_t... Lengths, index_t... Strides>
__host__ __device__ void
print_tensor_descriptor_impl(const char* s, Sequence<Lengths...>, Sequence<Strides...>)
{
constexpr index_t nDim = sizeof...(Lengths);
static_assert(nDim > 0 && nDim <= 12, "wrong!");
static_if<nDim == 1>{}([&](auto) {
printf("%s dim %u, lengths {%u}, strides {%u}\n", s, nDim, Lengths..., Strides...);
});
static_if<nDim == 2>{}([&](auto) {
printf("%s dim %u, lengths {%u %u}, strides {%u %u}\n", s, nDim, Lengths..., Strides...);
});
static_if<nDim == 3>{}([&](auto) {
printf(
"%s dim %u, lengths {%u %u %u}, strides {%u %u %u}\n", s, nDim, Lengths..., Strides...);
});
static_if<nDim == 4>{}([&](auto) {
printf("%s dim %u, lengths {%u %u %u %u}, strides {%u %u %u %u}\n",
s,
nDim,
Lengths...,
Strides...);
});
static_if<nDim == 5>{}([&](auto) {
printf("%s dim %u, lengths {%u %u %u %u %u}, strides {%u %u %u %u %u}\n",
s,
nDim,
Lengths...,
Strides...);
});
static_if<nDim == 6>{}([&](auto) {
printf("%s dim %u, lengths {%u %u %u %u %u %u}, strides {%u %u %u %u %u %u}\n",
s,
nDim,
Lengths...,
Strides...);
});
static_if<nDim == 7>{}([&](auto) {
printf("%s dim %u, lengths {%u %u %u %u %u %u %u}, strides {%u %u %u %u %u %u %u}\n",
s,
nDim,
Lengths...,
Strides...);
});
static_if<nDim == 8>{}([&](auto) {
printf("%s dim %u, lengths {%u %u %u %u %u %u %u %u}, strides {%u %u %u %u %u %u %u %u}\n",
s,
nDim,
Lengths...,
Strides...);
});
static_if<nDim == 9>{}([&](auto) {
printf("%s dim %u, lengths {%u %u %u %u %u %u %u %u %u}, strides {%u %u %u %u %u %u %u %u "
"%u}\n",
s,
nDim,
Lengths...,
Strides...);
});
static_if<nDim == 10>{}([&](auto) {
printf("%s dim %u, lengths {%u %u %u %u %u %u %u %u %u %u}, strides {%u %u %u %u %u %u %u "
"%u %u %u}\n",
s,
nDim,
Lengths...,
Strides...);
});
static_if<nDim == 11>{}([&](auto) {
printf("%s dim %u, lengths {%u %u %u %u %u %u %u %u %u %u %u}, strides {%u %u %u %u %u %u "
"%u %u "
"%u %u %u}\n",
s,
nDim,
Lengths...,
Strides...);
});
static_if<nDim == 12>{}([&](auto) {
printf("%s dim %u, lengths {%u %u %u %u %u %u %u %u %u %u %u %u}, strides {%u %u %u %u %u "
"%u %u %u %u "
"%u %u %u}\n",
s,
nDim,
Lengths...,
Strides...);
});
}
template <index_t... Lengths>
__host__ __device__ void print_tensor_descriptor_impl(const char* s, Sequence<Lengths...>)
{
constexpr index_t nDim = sizeof...(Lengths);
static_assert(nDim > 0 && nDim <= 12, "wrong!");
static_if<nDim == 1>{}([&](auto) { printf("%s dim %u, lengths {%u}\n", s, nDim, Lengths...); });
static_if<nDim == 2>{}(
[&](auto) { printf("%s dim %u, lengths {%u %u}\n", s, nDim, Lengths...); });
static_if<nDim == 3>{}(
[&](auto) { printf("%s dim %u, lengths {%u %u %u}\n", s, nDim, Lengths...); });
static_if<nDim == 4>{}(
[&](auto) { printf("%s dim %u, lengths {%u %u %u %u}\n", s, nDim, Lengths...); });
static_if<nDim == 5>{}(
[&](auto) { printf("%s dim %u, lengths {%u %u %u %u %u}\n", s, nDim, Lengths...); });
static_if<nDim == 6>{}(
[&](auto) { printf("%s dim %u, lengths {%u %u %u %u %u %u}, \n", s, nDim, Lengths...); });
static_if<nDim == 7>{}(
[&](auto) { printf("%s dim %u, lengths {%u %u %u %u %u %u %u}\n", s, nDim, Lengths...); });
static_if<nDim == 8>{}([&](auto) {
printf("%s dim %u, lengths {%u %u %u %u %u %u %u %u}\n", s, nDim, Lengths...);
});
static_if<nDim == 9>{}([&](auto) {
printf("%s dim %u, lengths {%u %u %u %u %u %u %u %u %u}\n", s, nDim, Lengths...);
});
static_if<nDim == 10>{}([&](auto) {
printf("%s dim %u, lengths {%u %u %u %u %u %u %u %u %u %u}\n", s, nDim, Lengths...);
});
static_if<nDim == 11>{}([&](auto) {
printf("%s dim %u, lengths {%u %u %u %u %u %u %u %u %u %u %u}\n", s, nDim, Lengths...);
});
static_if<nDim == 12>{}([&](auto) {
printf("%s dim %u, lengths {%u %u %u %u %u %u %u %u %u %u %u %u}\n", s, nDim, Lengths...);
});
}
} // namespace ck
#endif
composable_kernel/include/tensor_description/tensor_coordinate.hpp
View file @ 52c3fe05
#ifndef CK_TENSOR_COORDINATE_V2_HPP
#define CK_TENSOR_COORDINATE_V2_HPP
#ifndef CK_TENSOR_COORDINATE_HPP
#define CK_TENSOR_COORDINATE_HPP
#include "common_header.hpp"
#include "dimension.hpp"
......@@ -8,9 +8,24 @@
namespace ck {
// A "tensor cooridnate" is an opaque object that represents a "point of location" inside a tensor
// At the bare minimun, user should be able to query the following information from a tensor
// coordinate:
// 1. Tensor descriptor
// 2. Location, represented in the form of multi-index
// 3. Location, represented in the form of the offset to the origin of the tensor
// 4. If the location is inside invalid area or not, i.e. the padding area of an implicitly padded
// tensor is considered invalid, because the padding area doesn't have any physical memory
// allocation
// A tensor cooridnate also provides following functionality:
// 1. Given step size in each dimension, update itself, or return a new tensor cooridnate, so user
// can freely move the "point of location" inside the tensor
// wrapper class for NativeTensorCoordinate and TransformedTensorCoordinate
template <typename TensorDesc>
struct TensorCoordinate;
// tensor coordinate for native tensor
template <typename NativeTensorDesc>
struct NativeTensorCoordinate
{
......@@ -78,12 +93,10 @@ struct NativeTensorCoordinate
return coord;
}
#if 0 // tweaking
__host__ __device__ static constexpr index_t CalculateOffsetDiff(const Index& idx_diff)
{
return tensor_desc_type::CalculateOffsetDiff(idx_diff);
}
#endif
__host__ __device__ static constexpr bool IsUpperIndexMappedToValidOffset() { return true; }
......@@ -96,6 +109,7 @@ struct NativeTensorCoordinate
index_t mOffset;
};
// tensor coordinate for transformed tensor
template <typename TransformedTensorDesc>
struct TransformedTensorCoordinate
{
......@@ -177,10 +191,10 @@ struct TransformedTensorCoordinate
return coord_up;
}
#if 0 // tweaking
// Calculate offset diff without updating tensor-coordinate
// If idx_up_diff is know at compile time, and has only non-zero entries on linear dimensions,
// then all calculation can be done at compile-time.
// TODO: this function is not compiled to expected ISA
__host__ __device__ constexpr index_t CalculateOffsetDiff(const UpperIndex& idx_up_diff) const
{
// For transformation of multi-index difference, not all transformation functions need to
......@@ -191,7 +205,6 @@ struct TransformedTensorCoordinate
return GetLowerCoordinate().CalculateOffsetDiff(idx_low_diff);
}
#endif
__host__ __device__ constexpr bool IsUpperIndexMappedToValidOffset() const
{
......
composable_kernel/include/tensor_description/tensor_coordinate_deprecated.hpp
View file @ 52c3fe05
......@@ -2,12 +2,12 @@
#define CK_TENSOR_COORDINATE_DEPRECATED_HPP
#include "common_header.hpp"
#include "ConstantTensorDescriptor.hpp"
#include "ConstantMergedTensorDescriptor.hpp"
#include "ConstantTensorDescriptor_deprecated.hpp"
#include "ConstantMergedTensorDescriptor_deprecated.hpp"
namespace ck {
// TensorDesc is ConstantTensorDescriptor
// TensorDesc is ConstantTensorDescriptor_deprecated
template <class TensorDesc>
struct NormalTensorCoordinate_deprecated
{
......@@ -95,18 +95,19 @@ struct NormalTensorCoordinate_deprecated
index_t mOffset;
};
// TensorDesc is ConstantMergedTensorDescriptor
// TensorDesc is ConstantMergedTensorDescriptor_deprecated
template <class TensorDesc>
struct MergedTensorCoordinate
struct MergedTensorCoordinate_deprecated
{
using type = MergedTensorCoordinate;
using type = MergedTensorCoordinate_deprecated;
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)
__host__
__device__ constexpr MergedTensorCoordinate_deprecated(Array<index_t, nDim> tensor_index)
: mOriginalIndex{tensor_desc_type::GetOriginalMultiIndexFromMultiIndex(tensor_index)}
{
// partial offset on each dimension
......@@ -127,8 +128,8 @@ struct MergedTensorCoordinate
}
template <class... Xs>
__host__ __device__ constexpr MergedTensorCoordinate(Xs... xs)
: MergedTensorCoordinate(Array<index_t, nDim>{xs...})
__host__ __device__ constexpr MergedTensorCoordinate_deprecated(Xs... xs)
: MergedTensorCoordinate_deprecated(Array<index_t, nDim>{xs...})
{
}
......@@ -311,7 +312,7 @@ struct MergedTensorCoordinate
// 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
// and simplify implementation of ConstantMergedTensorDescriptor_deprecated, 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;
......@@ -326,16 +327,17 @@ struct TensorCoordinate_deprecated
private:
template <class... Ts>
__host__ __device__ static constexpr auto
MakeDummyTensorCoordinate(ConstantTensorDescriptor<Ts...>)
MakeDummyTensorCoordinate(ConstantTensorDescriptor_deprecated<Ts...>)
{
return NormalTensorCoordinate_deprecated<ConstantTensorDescriptor<Ts...>>();
return NormalTensorCoordinate_deprecated<ConstantTensorDescriptor_deprecated<Ts...>>();
}
template <class... Ts>
__host__ __device__ static constexpr auto
MakeDummyTensorCoordinate(ConstantMergedTensorDescriptor<Ts...>)
MakeDummyTensorCoordinate(ConstantMergedTensorDescriptor_deprecated<Ts...>)
{
return MergedTensorCoordinate<ConstantMergedTensorDescriptor<Ts...>>();
return MergedTensorCoordinate_deprecated<
ConstantMergedTensorDescriptor_deprecated<Ts...>>();
}
public:
......
composable_kernel/include/tensor_description/tensor_coordinate_helper.hpp
View file @ 52c3fe05
#ifndef CK_TENSOR_COORDINATE_HELPER_HPP
#define CK_TENSOR_COORDINATE_HELPER_HPP
#include "tensor_coordiante_v2.hpp"
#include "tensor_coordiante_hpp"
namespace ck {
template <typename TensorDesc>
__host__ __device__ constexpr auto
make_tensor_coordinate_v2(TensorDesc, MultiIndex<TensorDesc::GetNumOfDimension()> idx)
make_tensor_coordinate(TensorDesc, MultiIndex<TensorDesc::GetNumOfDimension()> idx)
{
return typename TensorCoordinate<TensorDesc>::type(idx);
}
......
composable_kernel/include/tensor_description/tensor_descriptor.hpp
View file @ 52c3fe05
......@@ -7,6 +7,8 @@
namespace ck {
// tensor descriptor for "native tensor"
// A "native tensor" is a "true" tensor that can be represented by Lengths and Strides
template <typename... NativeDimensions>
struct NativeTensorDescriptor
{
......@@ -113,12 +115,10 @@ struct NativeTensorDescriptor
__host__ __device__ static constexpr auto GetNonLinearDimensions() { return Sequence<>{}; }
#if 0
__host__ __device__ static constexpr auto GetNonLinearIndependentDimensionGroups()
{
return Tuple<>{};
}
#endif
__host__ __device__ static constexpr bool
IsUpperIndexMappedToValidOffset(const Index& /* idx */)
......@@ -127,14 +127,11 @@ struct NativeTensorDescriptor
}
};
// LowerTensorDescriptor
// Transforms: Tuple<DimensionTransforms...>
// LowerDimensionIds: Tuple<Sequence<...>>
// UpperDimensionIds: Tuple<Sequence<...>>
template <typename LowTensorDescriptor,
typename Transforms,
typename LowDimensionIds,
typename UpDimensionIds>
// Tensor descriptor for "transformed tensor"
template <typename LowTensorDescriptor, // NativeTensorDescriptor or TransformedTensorDescriptor
typename Transforms, // Tuple<MultIndexTransforms...>
typename LowDimensionIds, // Tuple<Sequence<...>>
typename UpDimensionIds> // Tuple<Sequence<...>>
struct TransformedTensorDescriptor
{
using type = TransformedTensorDescriptor;
......@@ -412,6 +409,7 @@ struct TransformedTensorDescriptor
{
#if 0
// create tuple of linear dimension masks, for all transformations
// TODO: this doesn't compile, because transform_tuples() complain about constexpr
constexpr auto tuple_of_linear_dimension_mask =
transform_tuples(lambda_get_linear_dimension_mask_of_single_tranform{},
Transforms{},
......@@ -419,7 +417,7 @@ struct TransformedTensorDescriptor
UpDimensionIds{});
#else
// create tuple of linear dimension masks, for all transformations
// TODO: this is a hack, transform_tuples() doesn't compile, complain about constexpr
// TODO: this is a hack
constexpr auto tuple_of_linear_dimension_mask = dummy_transform_tuples_impl(
lambda_get_linear_dimension_mask_of_single_tranform{},
Transforms{},
......@@ -465,7 +463,7 @@ struct TransformedTensorDescriptor
#if 0
__host__ __device__ static constexpr auto GetNonLinearIndependentDimensionGroups()
{
// not implemented
// TODO: not implemented
}
#endif
......
composable_kernel/include/tensor_description/tensor_descriptor_helper.hpp
View file @ 52c3fe05
......@@ -63,7 +63,8 @@ template <typename LowerTensorDescriptor,
index_t... LowerLengths,
index_t... LowerDimensionIds,
index_t... UpperDimensionIds>
__host__ __device__ constexpr auto reorder_tensor_descriptor_impl(LowerTensorDescriptor,
__host__ __device__ constexpr auto
reorder_transformed_tensor_descriptor_impl(LowerTensorDescriptor,
Sequence<LowerLengths...>,
Sequence<LowerDimensionIds...>,
Sequence<UpperDimensionIds...>)
......@@ -74,17 +75,40 @@ __host__ __device__ constexpr auto reorder_tensor_descriptor_impl(LowerTensorDes
Tuple<Sequence<UpperDimensionIds>...>>{};
}
template <typename LowerTensorDescriptor, typename MapLower2Upper>
// reorder a NativeTensorDescriptor
template <typename... Ts, typename MapLower2Upper>
__host__ __device__ constexpr auto
reorder_tensor_descriptor_given_lower2upper(NativeTensorDescriptor<Ts...>, MapLower2Upper)
{
static_assert(is_valid_sequence_map<MapLower2Upper>{},
"wrong! MapLower2Upper is not a valid map");
constexpr auto old_desc = NativeTensorDescriptor<Ts...>{};
static_assert(old_desc.GetNumOfDimension() == MapLower2Upper::Size(), "wrong!");
constexpr auto new_lengths = old_desc.GetLengths().ReorderGivenOld2New(MapLower2Upper{});
constexpr auto new_strides = old_desc.GetStrides().ReorderGivenOld2New(MapLower2Upper{});
return make_native_tensor_descriptor(new_lengths, new_strides);
}
// reorder a TransformedTensorDescriptor
template <typename... Ts, typename MapLower2Upper>
__host__ __device__ constexpr auto
reorder_tensor_descriptor_given_lower2upper(LowerTensorDescriptor, MapLower2Upper)
reorder_tensor_descriptor_given_lower2upper(TransformedTensorDescriptor<Ts...>, MapLower2Upper)
{
static_assert(is_valid_sequence_map<MapLower2Upper>{},
"wrong! MapLower2Upper is not a valid map");
return reorder_tensor_descriptor_impl(
LowerTensorDescriptor{},
LowerTensorDescriptor::GetLengths(),
typename arithmetic_sequence_gen<0, LowerTensorDescriptor::GetNumOfDimension(), 1>::type{},
constexpr auto low_desc = TransformedTensorDescriptor<Ts...>{};
static_assert(low_desc.GetNumOfDimension() == MapLower2Upper::Size(), "wrong!");
return reorder_transformed_tensor_descriptor_impl(
low_desc,
low_desc.GetLengths(),
typename arithmetic_sequence_gen<0, low_desc.GetNumOfDimension(), 1>::type{},
MapLower2Upper{});
}
......@@ -97,7 +121,7 @@ __host__ __device__ constexpr auto
}
template <typename Lengths, typename Strides>
__host__ __device__ constexpr bool AreDimensionsUnfoldable(Lengths, Strides)
__host__ __device__ constexpr bool are_dimensions_unfoldable(Lengths, Strides)
{
static_assert(Lengths::Size() == Strides::Size(), "wrong!");
......@@ -129,7 +153,7 @@ __host__ __device__ constexpr auto unfold_tensor_descriptor(NativeTensorDescript
constexpr auto right = typename arithmetic_sequence_gen<LastUnfoldDim + 1, nDim, 1>::type{};
// sanity-checknfoldable
static_assert(AreDimensionsUnfoldable(desc.GetLengths(middle), desc.GetStrides(middle)),
static_assert(are_dimensions_unfoldable(desc.GetLengths(middle), desc.GetStrides(middle)),
"wrong! not unfoldable");
// unfolded length, stride
......@@ -148,30 +172,6 @@ __host__ __device__ constexpr auto unfold_tensor_descriptor(NativeTensorDescript
return make_native_tensor_descriptor(new_lengths, new_strides);
}
#if 0
// not implemented
template <typename LowerTensorDescriptor,
typename PadDimensionIds,
typename LeftPads,
typename RightPads>
__host__ __device__ constexpr auto
pad_tensor_descriptor(LowerTensorDescriptor, PadLowerDimensionIds, LeftPads, RightPads)
{
constexpr index_t nDim = LowerTensorDescriptor::GetNumOfDimension();
constexpr auto non_pad_low_dim_ids = xxx;
return transform_tensor_descriptor(
LowerTensorDescriptor{},
make_tuple(Pad<decltype(LowerTensorDescriptor::GetLengths(PadLowerDimensionIds{})),
LeftPads,
RightPads>{})
.PushBack(PassThrough<xxxx>...),
make_tuple(PadLowerDimensionIds{}).PushBack(xxxx),
sequence_to_tuple(typename arithmetic_sequence_gen<0, nDim, 1> i::type{}));
}
#endif
// a cluster map 1d index to N-d index
template <typename Lengths, typename ArrangeOrder>
struct ClusterDescriptor
......@@ -205,169 +205,7 @@ template <typename Lengths,
__host__ __device__ constexpr auto make_cluster_descriptor(
Lengths, ArrangeOrder order = typename arithmetic_sequence_gen<0, Lengths::Size(), 1>::type{})
{
return ClusterDescriptor<Lengths, ArrangeOrder>{};
}
template <typename... NativeDimensions>
__host__ __device__ void
print_tensor_descriptor(const char* s, const NativeTensorDescriptor<NativeDimensions...>& desc)
{
print_tensor_descriptor_impl(s, desc.GetLengths(), desc.GetStrides());
}
template <typename... Ts>
__host__ __device__ void print_tensor_descriptor(const char* s,
const TransformedTensorDescriptor<Ts...>& desc)
{
print_tensor_descriptor_impl(s, desc.GetLengths());
}
template <index_t... Lengths, index_t... Strides>
__host__ __device__ void
print_tensor_descriptor_impl(const char* s, Sequence<Lengths...>, Sequence<Strides...>)
{
constexpr index_t nDim = sizeof...(Lengths);
static_assert(nDim > 0 && nDim <= 12, "wrong!");
static_if<nDim == 1>{}([&](auto) {
printf("%s dim %u, lengths {%u}, strides {%u}\n", s, nDim, Lengths..., Strides...);
});
static_if<nDim == 2>{}([&](auto) {
printf("%s dim %u, lengths {%u %u}, strides {%u %u}\n", s, nDim, Lengths..., Strides...);
});
static_if<nDim == 3>{}([&](auto) {
printf(
"%s dim %u, lengths {%u %u %u}, strides {%u %u %u}\n", s, nDim, Lengths..., Strides...);
});
static_if<nDim == 4>{}([&](auto) {
printf("%s dim %u, lengths {%u %u %u %u}, strides {%u %u %u %u}\n",
s,
nDim,
Lengths...,
Strides...);
});
static_if<nDim == 5>{}([&](auto) {
printf("%s dim %u, lengths {%u %u %u %u %u}, strides {%u %u %u %u %u}\n",
s,
nDim,
Lengths...,
Strides...);
});
static_if<nDim == 6>{}([&](auto) {
printf("%s dim %u, lengths {%u %u %u %u %u %u}, strides {%u %u %u %u %u %u}\n",
s,
nDim,
Lengths...,
Strides...);
});
static_if<nDim == 7>{}([&](auto) {
printf("%s dim %u, lengths {%u %u %u %u %u %u %u}, strides {%u %u %u %u %u %u %u}\n",
s,
nDim,
Lengths...,
Strides...);
});
static_if<nDim == 8>{}([&](auto) {
printf("%s dim %u, lengths {%u %u %u %u %u %u %u %u}, strides {%u %u %u %u %u %u %u %u}\n",
s,
nDim,
Lengths...,
Strides...);
});
static_if<nDim == 9>{}([&](auto) {
printf("%s dim %u, lengths {%u %u %u %u %u %u %u %u %u}, strides {%u %u %u %u %u %u %u %u "
"%u}\n",
s,
nDim,
Lengths...,
Strides...);
});
static_if<nDim == 10>{}([&](auto) {
printf("%s dim %u, lengths {%u %u %u %u %u %u %u %u %u %u}, strides {%u %u %u %u %u %u %u "
"%u %u %u}\n",
s,
nDim,
Lengths...,
Strides...);
});
static_if<nDim == 11>{}([&](auto) {
printf("%s dim %u, lengths {%u %u %u %u %u %u %u %u %u %u %u}, strides {%u %u %u %u %u %u "
"%u %u "
"%u %u %u}\n",
s,
nDim,
Lengths...,
Strides...);
});
static_if<nDim == 12>{}([&](auto) {
printf("%s dim %u, lengths {%u %u %u %u %u %u %u %u %u %u %u %u}, strides {%u %u %u %u %u "
"%u %u %u %u "
"%u %u %u}\n",
s,
nDim,
Lengths...,
Strides...);
});
}
template <index_t... Lengths>
__host__ __device__ void print_tensor_descriptor_impl(const char* s, Sequence<Lengths...>)
{
constexpr index_t nDim = sizeof...(Lengths);
static_assert(nDim > 0 && nDim <= 12, "wrong!");
static_if<nDim == 1>{}([&](auto) { printf("%s dim %u, lengths {%u}\n", s, nDim, Lengths...); });
static_if<nDim == 2>{}(
[&](auto) { printf("%s dim %u, lengths {%u %u}\n", s, nDim, Lengths...); });
static_if<nDim == 3>{}(
[&](auto) { printf("%s dim %u, lengths {%u %u %u}\n", s, nDim, Lengths...); });
static_if<nDim == 4>{}(
[&](auto) { printf("%s dim %u, lengths {%u %u %u %u}\n", s, nDim, Lengths...); });
static_if<nDim == 5>{}(
[&](auto) { printf("%s dim %u, lengths {%u %u %u %u %u}\n", s, nDim, Lengths...); });
static_if<nDim == 6>{}(
[&](auto) { printf("%s dim %u, lengths {%u %u %u %u %u %u}, \n", s, nDim, Lengths...); });
static_if<nDim == 7>{}(
[&](auto) { printf("%s dim %u, lengths {%u %u %u %u %u %u %u}\n", s, nDim, Lengths...); });
static_if<nDim == 8>{}([&](auto) {
printf("%s dim %u, lengths {%u %u %u %u %u %u %u %u}\n", s, nDim, Lengths...);
});
static_if<nDim == 9>{}([&](auto) {
printf("%s dim %u, lengths {%u %u %u %u %u %u %u %u %u}\n", s, nDim, Lengths...);
});
static_if<nDim == 10>{}([&](auto) {
printf("%s dim %u, lengths {%u %u %u %u %u %u %u %u %u %u}\n", s, nDim, Lengths...);
});
static_if<nDim == 11>{}([&](auto) {
printf("%s dim %u, lengths {%u %u %u %u %u %u %u %u %u %u %u}\n", s, nDim, Lengths...);
});
static_if<nDim == 12>{}([&](auto) {
printf("%s dim %u, lengths {%u %u %u %u %u %u %u %u %u %u %u %u}\n", s, nDim, Lengths...);
});
return ClusterDescriptor<Lengths, decltype(order)>{};
}
} // namespace ck
......
composable_kernel/include/tensor_operation/blockwise_gemm.hpp
View file @ 52c3fe05
......@@ -5,19 +5,17 @@
#include "ConstantMatrixDescriptor.hpp"
#include "threadwise_gemm.hpp"
#ifndef CK_BLOCKWISE_GEMM_USE_AMD_INLINE_ASM
#define CK_BLOCKWISE_GEMM_USE_AMD_INLINE_ASM 1
#endif
namespace ck {
// if following number are power of 2, index calculation shall be greatly reduced:
// blockwise GEMM: C += transpose(A) * B
// A and B are visable to the whole block, C is distributed among each thread
// If following number are power of 2, index calculation shall be greatly reduced:
// MPerThreadSubC, NPerThreadSubC, MLevel0ThreadCluster, NLevel0ThreadCluster,
// MLevel1ThreadCluster, NLevel1ThreadCluster
template <index_t BlockSize,
class BlockMatrixA,
class BlockMatrixB,
class ThreadMatrixC,
typename BlockMatrixA,
typename BlockMatrixB,
typename ThreadMatrixC,
index_t MPerThreadSubC,
index_t NPerThreadSubC,
index_t MLevel0ThreadCluster,
......@@ -117,23 +115,27 @@ struct BlockwiseGemmBlockABlockBThreadCTransANormalBNormalC_v2
n_repeat * NPerLevel1Cluster + n_in_sub_c};
}
#if CK_USE_AMD_INLINE_ASM
template <class FloatA, class FloatB, class FloatC>
__device__ void Run_amd_asm(const FloatA* __restrict__ p_a_block,
const FloatB* __restrict__ p_b_block,
FloatC* __restrict__ p_c_thread) const
template <typename FloatA, typename FloatB, typename FloatC>
__device__ void
Run_naive(const FloatA* p_a_block, const FloatB* p_b_block, FloatC* p_c_thread) const
{
constexpr auto a_block_mtx = BlockMatrixA{};
constexpr auto b_block_mtx = BlockMatrixB{};
constexpr auto c_thread_mtx = ThreadMatrixC{};
constexpr index_t M = a_block_mtx.NCol();
constexpr index_t N = b_block_mtx.NCol();
constexpr index_t K = a_block_mtx.NRow();
constexpr index_t MPerThread = c_thread_mtx.NRow();
constexpr index_t NPerThread = c_thread_mtx.NCol();
constexpr index_t MPerLevel1Cluster =
MPerThreadSubC * MLevel0ThreadCluster * MLevel1ThreadCluster;
constexpr index_t NPerLevel1Cluster =
NPerThreadSubC * NLevel0ThreadCluster * NLevel1ThreadCluster;
constexpr index_t MRepeat = MPerThread / MPerThreadSubC;
constexpr index_t NRepeat = NPerThread / NPerThreadSubC;
// thread A, B for GEMM
constexpr auto a_thread_mtx =
make_ConstantMatrixDescriptor_packed(Number<KPerThreadLoop>{}, Number<MPerThread>{});
......@@ -144,271 +146,201 @@ struct BlockwiseGemmBlockABlockBThreadCTransANormalBNormalC_v2
FloatA p_a_thread[a_thread_mtx.GetElementSpace()];
FloatB p_b_thread[b_thread_mtx.GetElementSpace()];
constexpr index_t MPerLevel1Cluster =
MPerThreadSubC * MLevel0ThreadCluster * MLevel1ThreadCluster;
constexpr index_t NPerLevel1Cluster =
NPerThreadSubC * NLevel0ThreadCluster * NLevel1ThreadCluster;
// assertion for inline asm
static_assert(is_same<FloatA, float>{} && is_same<FloatB, float>{} &&
is_same<FloatC, float>{},
"Run_amd_asm only deal with float");
static_assert(MPerThreadSubC == 4 && NPerThreadSubC == 4 && KPerThreadLoop == 1 &&
MPerThread == 8 && NPerThread == 8,
"Run_amd_asm cannot deal with this GEMM shape yet");
static_assert(DataPerReadA == 4 && DataPerReadB == 4, "Run_amd_asm only do float4 read");
using Float4 = vector_type<float, 4>::MemoryType;
Float4* reg_a = reinterpret_cast<Float4*>(p_a_thread);
Float4* reg_b = reinterpret_cast<Float4*>(p_b_thread);
Float4* reg_c = reinterpret_cast<Float4*>(p_c_thread);
constexpr auto a_thread_copy = ThreadwiseMatrixSliceCopy<BlockMatrixA,
decltype(a_thread_mtx),
KPerThreadLoop,
MPerThreadSubC,
DataPerReadA>{};
constexpr auto b_thread_copy = ThreadwiseMatrixSliceCopy<BlockMatrixB,
decltype(b_thread_mtx),
KPerThreadLoop,
NPerThreadSubC,
DataPerReadB>{};
constexpr auto threadwise_gemm =
ThreadwiseGemmTransANormalBNormalC<decltype(a_thread_mtx),
decltype(b_thread_mtx),
decltype(c_thread_mtx)>{};
#pragma unroll
// loop over k
for(index_t k_begin = 0; k_begin < K; k_begin += KPerThreadLoop)
{
#pragma unroll
// read A
for(index_t m_repeat = 0; m_repeat < MRepeat; ++m_repeat)
{
a_thread_copy.Run(
p_a_block + a_block_mtx.CalculateOffset(k_begin, m_repeat * MPerLevel1Cluster) +
mMyThreadOffsetA,
p_a_thread + a_thread_mtx.CalculateOffset(0, m_repeat * MPerThreadSubC));
}
reg_a[0] = *reinterpret_cast<const Float4*>(&p_a_block[mMyThreadOffsetA]);
reg_b[0] = *reinterpret_cast<const Float4*>(&p_b_block[mMyThreadOffsetB]);
reg_b[1] =
*reinterpret_cast<const Float4*>(&p_b_block[mMyThreadOffsetB + NPerLevel1Cluster]);
reg_a[1] =
*reinterpret_cast<const Float4*>(&p_a_block[mMyThreadOffsetA + MPerLevel1Cluster]);
outerProduct4x4(reg_a[0], reg_b[0], reg_c[0], reg_c[2], reg_c[4], reg_c[6]);
outerProduct4x4(reg_a[0], reg_b[1], reg_c[1], reg_c[3], reg_c[5], reg_c[7]);
#pragma unroll
for(index_t k = 1; k < K; ++k)
// read B
for(index_t n_repeat = 0; n_repeat < NRepeat; ++n_repeat)
{
reg_a[0] = *reinterpret_cast<const Float4*>(&p_a_block[mMyThreadOffsetA + k * M]);
outerProduct4x4(reg_a[1], reg_b[0], reg_c[8], reg_c[10], reg_c[12], reg_c[14]);
reg_b[0] = *reinterpret_cast<const Float4*>(&p_b_block[mMyThreadOffsetB + k * N]);
outerProduct4x4(reg_a[1], reg_b[1], reg_c[9], reg_c[11], reg_c[13], reg_c[15]);
reg_b[1] = *reinterpret_cast<const Float4*>(
&p_b_block[mMyThreadOffsetB + k * N + NPerLevel1Cluster]);
reg_a[1] = *reinterpret_cast<const Float4*>(
&p_a_block[mMyThreadOffsetA + k * M + MPerLevel1Cluster]);
outerProduct4x4(reg_a[0], reg_b[0], reg_c[0], reg_c[2], reg_c[4], reg_c[6]);
outerProduct4x4(reg_a[0], reg_b[1], reg_c[1], reg_c[3], reg_c[5], reg_c[7]);
b_thread_copy.Run(
p_b_block + b_block_mtx.CalculateOffset(k_begin, n_repeat * NPerLevel1Cluster) +
mMyThreadOffsetB,
p_b_thread + b_thread_mtx.CalculateOffset(0, n_repeat * NPerThreadSubC));
}
// C += A * B
threadwise_gemm.Run(p_a_thread, p_b_thread, p_c_thread);
}
outerProduct4x4(reg_a[1], reg_b[0], reg_c[8], reg_c[10], reg_c[12], reg_c[14]);
outerProduct4x4(reg_a[1], reg_b[1], reg_c[9], reg_c[11], reg_c[13], reg_c[15]);
}
__device__ void Run_amd_asm_v2(const float* __restrict__ p_a_block,
const float* __restrict__ p_b_block,
float* __restrict__ p_c_thread) const
template <typename FloatA, typename FloatB, typename FloatC>
__device__ void
Run_pipelined_2x2(const FloatA* p_a_block, const FloatB* p_b_block, FloatC* p_c_thread) const
{
constexpr auto a_block_mtx = BlockMatrixA{};
constexpr auto b_block_mtx = BlockMatrixB{};
constexpr auto c_thread_mtx = ThreadMatrixC{};
constexpr index_t M = a_block_mtx.NCol();
constexpr index_t N = b_block_mtx.NCol();
constexpr index_t K = a_block_mtx.NRow();
constexpr index_t MPerThread = c_thread_mtx.NRow();
constexpr index_t NPerThread = c_thread_mtx.NCol();
// thread A, B for GEMM
constexpr index_t MPerLevel1Cluster =
MPerThreadSubC * MLevel0ThreadCluster * MLevel1ThreadCluster;
constexpr index_t NPerLevel1Cluster =
NPerThreadSubC * NLevel0ThreadCluster * NLevel1ThreadCluster;
constexpr index_t MRepeat = MPerThread / MPerThreadSubC;
constexpr index_t NRepeat = NPerThread / NPerThreadSubC;
static_assert(MRepeat == 2 && NRepeat == 2,
"wrong! inline asm cannot deal with this GEMM config yet");
// thread A, B
constexpr auto a_thread_mtx =
make_ConstantMatrixDescriptor_packed(Number<KPerThreadLoop>{}, Number<MPerThread>{});
constexpr auto b_thread_mtx =
make_ConstantMatrixDescriptor_packed(Number<KPerThreadLoop>{}, Number<NPerThread>{});
float p_a_thread[a_thread_mtx.GetElementSpace()];
float p_b_thread[b_thread_mtx.GetElementSpace()];
// thread A-sub, B-sub
constexpr auto a_thread_sub_mtx = a_thread_mtx.MakeSubMatrixDescriptor(
Number<KPerThreadLoop>{}, Number<MPerThreadSubC>{});
constexpr auto b_thread_sub_mtx = b_thread_mtx.MakeSubMatrixDescriptor(
Number<KPerThreadLoop>{}, Number<NPerThreadSubC>{});
constexpr index_t MThreadCluster = MLevel0ThreadCluster * MLevel1ThreadCluster;
constexpr index_t NThreadCluster = NLevel0ThreadCluster * NLevel1ThreadCluster;
// thread C-sub
constexpr auto c_thread_sub_mtx = ThreadMatrixC::MakeSubMatrixDescriptor(
Number<MPerThreadSubC>{}, Number<NPerThreadSubC>{});
constexpr index_t MDataCluster = M / MPerThreadSubC;
constexpr index_t NDataCluster = N / NPerThreadSubC;
FloatA p_a_thread[a_thread_mtx.GetElementSpace()];
FloatB p_b_thread[b_thread_mtx.GetElementSpace()];
constexpr index_t MRepeat = MDataCluster / MThreadCluster;
constexpr index_t NRepeat = NDataCluster / NThreadCluster;
constexpr auto a_thread_copy = ThreadwiseMatrixSliceCopy<BlockMatrixA,
decltype(a_thread_mtx),
KPerThreadLoop,
MPerThreadSubC,
DataPerReadA>{};
// assertion for inline asm
static_assert((MPerThreadSubC == 4 && NPerThreadSubC == 4 && MRepeat == 2 && NRepeat == 2 &&
KPerThreadLoop == 1) ||
(MPerThreadSubC == 2 && NPerThreadSubC == 4 && MRepeat == 2 &&
NRepeat == 2 && KPerThreadLoop == 1),
"Run_amd_asm cannot deal with this GEMM shape yet");
constexpr auto b_thread_copy = ThreadwiseMatrixSliceCopy<BlockMatrixB,
decltype(b_thread_mtx),
KPerThreadLoop,
NPerThreadSubC,
DataPerReadB>{};
static_assert(DataPerReadA == MPerThreadSubC && DataPerReadB == NPerThreadSubC,
"wrong! Run_amd_asm doesn't support this config");
constexpr auto threadwise_gemm =
ThreadwiseGemmTransANormalBNormalC<decltype(a_thread_sub_mtx),
decltype(b_thread_sub_mtx),
decltype(c_thread_sub_mtx)>{};
if(MPerThreadSubC == 4 && NPerThreadSubC == 4 && MRepeat == 2 && NRepeat == 2 &&
KPerThreadLoop == 1)
{
using float4_type = vector_type<float, 4>::MemoryType;
float4_type* reg_a = reinterpret_cast<float4_type*>(p_a_thread);
float4_type* reg_b = reinterpret_cast<float4_type*>(p_b_thread);
float4_type* reg_c = reinterpret_cast<float4_type*>(p_c_thread);
const float4_type* p_a =
reinterpret_cast<const float4_type*>(&p_a_block[mMyThreadOffsetA]);
const float4_type* p_b =
reinterpret_cast<const float4_type*>(&p_b_block[mMyThreadOffsetB]);
reg_a[0] = p_a[0];
reg_b[0] = p_b[0];
reg_b[1] = p_b[NThreadCluster];
reg_a[1] = p_a[MThreadCluster];
outerProduct4x4(reg_a[0], reg_b[0], reg_c[0], reg_c[2], reg_c[4], reg_c[6]);
outerProduct4x4(reg_a[0], reg_b[1], reg_c[1], reg_c[3], reg_c[5], reg_c[7]);
#pragma unroll
for(index_t k = 1; k < K; ++k)
{
reg_a[0] = p_a[k * MDataCluster];
outerProduct4x4(reg_a[1], reg_b[0], reg_c[8], reg_c[10], reg_c[12], reg_c[14]);
reg_b[0] = p_b[k * NDataCluster];
outerProduct4x4(reg_a[1], reg_b[1], reg_c[9], reg_c[11], reg_c[13], reg_c[15]);
reg_b[1] = p_b[k * NDataCluster + NThreadCluster];
reg_a[1] = p_a[k * MDataCluster + MThreadCluster];
outerProduct4x4(reg_a[0], reg_b[0], reg_c[0], reg_c[2], reg_c[4], reg_c[6]);
outerProduct4x4(reg_a[0], reg_b[1], reg_c[1], reg_c[3], reg_c[5], reg_c[7]);
}
outerProduct4x4(reg_a[1], reg_b[0], reg_c[8], reg_c[10], reg_c[12], reg_c[14]);
outerProduct4x4(reg_a[1], reg_b[1], reg_c[9], reg_c[11], reg_c[13], reg_c[15]);
}
else if(MPerThreadSubC == 2 && NPerThreadSubC == 4 && MRepeat == 2 && NRepeat == 2 &&
KPerThreadLoop == 1)
{
using float2_type = vector_type<float, 2>::MemoryType;
using float4_type = vector_type<float, 4>::MemoryType;
float2_type* reg_a = reinterpret_cast<float2_type*>(p_a_thread);
float4_type* reg_b = reinterpret_cast<float4_type*>(p_b_thread);
float4_type* reg_c = reinterpret_cast<float4_type*>(p_c_thread);
const float2_type* p_a =
reinterpret_cast<const float2_type*>(&p_a_block[mMyThreadOffsetA]);
const float4_type* p_b =
reinterpret_cast<const float4_type*>(&p_b_block[mMyThreadOffsetB]);
reg_a[0] = p_a[0];
reg_b[0] = p_b[0];
reg_b[1] = p_b[NThreadCluster];
reg_a[1] = p_a[MThreadCluster];
outerProduct2x4(reg_a[0], reg_b[0], reg_c[0], reg_c[2]);
outerProduct2x4(reg_a[0], reg_b[1], reg_c[1], reg_c[3]);
#pragma unroll
for(index_t k = 1; k < K; ++k)
{
reg_a[0] = p_a[k * MDataCluster];
outerProduct2x4(reg_a[1], reg_b[0], reg_c[4], reg_c[6]);
reg_b[0] = p_b[k * NDataCluster];
outerProduct2x4(reg_a[1], reg_b[1], reg_c[5], reg_c[7]);
reg_b[1] = p_b[k * NDataCluster + NThreadCluster];
reg_a[1] = p_a[k * MDataCluster + MThreadCluster];
outerProduct2x4(reg_a[0], reg_b[0], reg_c[0], reg_c[2]);
outerProduct2x4(reg_a[0], reg_b[1], reg_c[1], reg_c[3]);
}
outerProduct2x4(reg_a[1], reg_b[0], reg_c[4], reg_c[6]);
outerProduct2x4(reg_a[1], reg_b[1], reg_c[5], reg_c[7]);
}
}
#endif
const FloatA* p_a_block_off = p_a_block + mMyThreadOffsetA;
const FloatB* p_b_block_off = p_b_block + mMyThreadOffsetB;
template <class FloatA, class FloatB, class FloatC>
__device__ void Run_source(const FloatA* const __restrict__ p_a_block,
const FloatB* const __restrict__ p_b_block,
FloatC* const __restrict__ p_c_thread) const
{
constexpr auto True = integral_constant<bool, true>{};
constexpr auto False = integral_constant<bool, false>{};
// read A_sub_0
a_thread_copy.Run(p_a_block_off, p_a_thread);
constexpr auto a_block_mtx = BlockMatrixA{};
constexpr auto b_block_mtx = BlockMatrixB{};
constexpr auto c_thread_mtx = ThreadMatrixC{};
// read B_sub_0
b_thread_copy.Run(p_b_block_off, p_b_thread);
constexpr index_t K = a_block_mtx.NRow();
// read B_sub_1
b_thread_copy.Run(p_b_block_off + b_block_mtx.CalculateOffset(0, NPerLevel1Cluster),
p_b_thread + b_thread_mtx.CalculateOffset(0, NPerThreadSubC));
constexpr index_t MPerThread = c_thread_mtx.NRow();
constexpr index_t NPerThread = c_thread_mtx.NCol();
// read A_sub_1
a_thread_copy.Run(p_a_block_off + a_block_mtx.CalculateOffset(0, MPerLevel1Cluster),
p_a_thread + a_thread_mtx.CalculateOffset(0, MPerThreadSubC));
// thread A, B for GEMM
constexpr auto a_thread_mtx =
make_ConstantMatrixDescriptor_packed(Number<KPerThreadLoop>{}, Number<MPerThread>{});
// C_sub_00 += transpose(A_sub_0) * B_sub_0
threadwise_gemm.Run(p_a_thread, p_b_thread, p_c_thread);
constexpr auto b_thread_mtx =
make_ConstantMatrixDescriptor_packed(Number<KPerThreadLoop>{}, Number<NPerThread>{});
// C_sub_01 += transpose(A_sub_0) * B_sub_1
threadwise_gemm.Run(p_a_thread,
p_b_thread + b_thread_mtx.CalculateOffset(0, NPerThreadSubC),
p_c_thread + ThreadMatrixC::CalculateOffset(0, NPerThreadSubC));
// thread A-sub, B-sub for copy
constexpr auto a_thread_sub_mtx = make_ConstantMatrixDescriptor(
Number<KPerThreadLoop>{}, Number<MPerThreadSubC>{}, Number<MPerThread>{});
#pragma unroll
// loop over rest of k
for(index_t k = KPerThreadLoop; k < K; k += KPerThreadLoop)
{
// read A_sub_0
a_thread_copy.Run(p_a_block_off + a_block_mtx.CalculateOffset(k, 0), p_a_thread);
constexpr auto b_thread_sub_mtx = make_ConstantMatrixDescriptor(
Number<KPerThreadLoop>{}, Number<NPerThreadSubC>{}, Number<NPerThread>{});
// C_sub_10 += transpose(A_sub_1) * B_sub_0
threadwise_gemm.Run(p_a_thread + a_thread_mtx.CalculateOffset(0, MPerThreadSubC),
p_b_thread,
p_c_thread + ThreadMatrixC::CalculateOffset(MPerThreadSubC, 0));
FloatA p_a_thread[a_thread_mtx.GetElementSpace()];
FloatB p_b_thread[b_thread_mtx.GetElementSpace()];
// read B_sub_0
b_thread_copy.Run(p_b_block_off + b_block_mtx.CalculateOffset(k, 0), p_b_thread);
constexpr index_t MPerLevel1Cluster =
MPerThreadSubC * MLevel0ThreadCluster * MLevel1ThreadCluster;
constexpr index_t NPerLevel1Cluster =
NPerThreadSubC * NLevel0ThreadCluster * NLevel1ThreadCluster;
// C_sub_11 += transpose(A_sub_1) * B_sub_1
threadwise_gemm.Run(p_a_thread + a_thread_mtx.CalculateOffset(0, MPerThreadSubC),
p_b_thread + b_thread_mtx.CalculateOffset(0, NPerThreadSubC),
p_c_thread +
ThreadMatrixC::CalculateOffset(MPerThreadSubC, NPerThreadSubC));
constexpr index_t MRepeat = MPerThread / MPerThreadSubC;
constexpr index_t NRepeat = NPerThread / NPerThreadSubC;
// read B_sub_1
b_thread_copy.Run(p_b_block_off + b_block_mtx.CalculateOffset(k, NPerLevel1Cluster),
p_b_thread + b_thread_mtx.CalculateOffset(0, NPerThreadSubC));
#pragma unroll
// loop over k
for(index_t k_begin = 0; k_begin < K; k_begin += KPerThreadLoop)
{
#pragma unroll
// copy A-sub to form A
for(index_t m_repeat = 0; m_repeat < MRepeat; ++m_repeat)
{
threadwise_matrix_copy(
a_block_mtx,
p_a_block +
a_block_mtx.GetOffsetFromMultiIndex(k_begin, m_repeat * MPerLevel1Cluster) +
mMyThreadOffsetA,
a_thread_mtx,
p_a_thread + a_thread_mtx.GetOffsetFromMultiIndex(0, m_repeat * MPerThreadSubC),
a_thread_sub_mtx.GetLengths(),
Number<DataPerReadA>{});
}
// read A_sub_1
a_thread_copy.Run(p_a_block_off + a_block_mtx.CalculateOffset(k, MPerLevel1Cluster),
p_a_thread + a_thread_mtx.CalculateOffset(0, MPerThreadSubC));
#pragma unroll
// copy B-sub to form B
for(index_t n_repeat = 0; n_repeat < NRepeat; ++n_repeat)
{
threadwise_matrix_copy(
b_block_mtx,
p_b_block +
b_block_mtx.GetOffsetFromMultiIndex(k_begin, n_repeat * NPerLevel1Cluster) +
mMyThreadOffsetB,
b_thread_mtx,
p_b_thread + b_thread_mtx.GetOffsetFromMultiIndex(0, n_repeat * NPerThreadSubC),
b_thread_sub_mtx.GetLengths(),
Number<DataPerReadB>{});
// C_sub_00 += transpose(A_sub_0) * B_sub_0
threadwise_gemm.Run(p_a_thread, p_b_thread, p_c_thread);
// C_sub_01 += transpose(A_sub_0) * B_sub_1
threadwise_gemm.Run(p_a_thread,
p_b_thread + b_thread_mtx.CalculateOffset(0, NPerThreadSubC),
p_c_thread + ThreadMatrixC::CalculateOffset(0, NPerThreadSubC));
}
// C = A * B
threadwise_gemm(a_thread_mtx,
True,
p_a_thread,
b_thread_mtx,
False,
// C_sub_10 += transpose(A_sub_1) * B_sub_0
threadwise_gemm.Run(p_a_thread + a_thread_mtx.CalculateOffset(0, MPerThreadSubC),
p_b_thread,
c_thread_mtx,
False,
p_c_thread);
}
}
p_c_thread + ThreadMatrixC::CalculateOffset(MPerThreadSubC, 0));
template <class FloatA, class FloatB, class FloatC>
__device__ void Run(const FloatA* __restrict__ p_a_block,
const FloatB* __restrict__ p_b_block,
FloatC* __restrict__ p_c_thread) const
// C_sub_11 += transpose(A_sub_1) * B_sub_1
threadwise_gemm.Run(p_a_thread + a_thread_mtx.CalculateOffset(0, MPerThreadSubC),
p_b_thread + b_thread_mtx.CalculateOffset(0, NPerThreadSubC),
p_c_thread +
ThreadMatrixC::CalculateOffset(MPerThreadSubC, NPerThreadSubC));
}
template <typename FloatA, typename FloatB, typename FloatC>
__device__ void Run(const FloatA* p_a_block, const FloatB* p_b_block, FloatC* p_c_thread) const
{
#if CK_USE_AMD_INLINE_ASM && CK_BLOCKWISE_GEMM_USE_AMD_INLINE_ASM
Run_amd_asm_v2(p_a_block, p_b_block, p_c_thread);
#if CK_EXPERIMENTAL_BLOCKWISE_GEMM_USE_PIPELINE
constexpr index_t MPerThread = ThreadMatrixC::NRow();
constexpr index_t NPerThread = ThreadMatrixC::NCol();
constexpr index_t MRepeat = MPerThread / MPerThreadSubC;
constexpr index_t NRepeat = NPerThread / NPerThreadSubC;
static_if<MRepeat == 2 && NRepeat == 2>{}([&](auto) {
Run_pipelined_2x2(p_a_block, p_b_block, p_c_thread);
}).Else([&](auto) { Run_naive(p_a_block, p_b_block, p_c_thread); });
#else
Run_source(p_a_block, p_b_block, p_c_thread);
Run_naive(p_a_block, p_b_block, p_c_thread);
#endif
}
};
......
composable_kernel/include/tensor_operation/blockwise_generic_tensor_slice_copy.hpp
View file @ 52c3fe05
......@@ -68,64 +68,118 @@ struct BlockwiseGenericTensorSliceCopy_v4
template <typename BlockSrcData,
typename ThreadBufferData,
address_space_t BlockSrcAddressSpace = address_space_t::generic,
address_space_t ThreadBufferAddressSpace = address_space_t::generic>
AddressSpace BlockSrcAddressSpace,
AddressSpace ThreadBufferAddressSpace>
__device__ void
RunLoadThreadBuffer(const BlockSrcData* p_block_src,
ThreadBufferData* p_thread_buffer,
integral_constant<AddressSpace, BlockSrcAddressSpace>,
integral_constant<AddressSpace, ThreadBufferAddressSpace>) const
{
constexpr auto block_src_address_space =
integral_constant<AddressSpace, BlockSrcAddressSpace>{};
constexpr auto thread_buffer_address_space =
integral_constant<AddressSpace, ThreadBufferAddressSpace>{};
constexpr bool has_optimized_address_calculation =
decltype(mThreadwiseStore)::HasWorkingOptimizedAddressCalculation();
// TODO: threadwise copy is still being tweaked
if(has_optimized_address_calculation)
{
mThreadwiseLoad.Run_optimized_src_address_calculation(
p_block_src, p_thread_buffer, block_src_address_space, thread_buffer_address_space);
}
else
{
mThreadwiseLoad.Run(
p_block_src, p_thread_buffer, block_src_address_space, thread_buffer_address_space);
}
}
template <typename BlockSrcData, typename ThreadBufferData>
__device__ void RunLoadThreadBuffer(const BlockSrcData* p_block_src,
ThreadBufferData* p_thread_buffer) const
{
#if 1
mThreadwiseLoad.template Run<BlockSrcData,
ThreadBufferData,
BlockSrcAddressSpace,
ThreadBufferAddressSpace>(p_block_src, p_thread_buffer);
#else // tweaking
mThreadwiseLoad.template Run_optimized_src_address_calculation<BlockSrcData,
ThreadBufferData,
BlockSrcAddressSpace,
ThreadBufferAddressSpace>(
p_block_src, p_thread_buffer);
#endif
constexpr auto generic_address_space =
integral_constant<AddressSpace, AddressSpace::generic>{};
RunLoadThreadBuffer(
p_block_src, p_thread_buffer, generic_address_space, generic_address_space);
}
template <typename ThreadBufferData,
typename BlockDstData,
address_space_t ThreadBufferAddressSpace = address_space_t::generic,
address_space_t BlockDstAddressSpace = address_space_t::generic>
AddressSpace ThreadBufferAddressSpace,
AddressSpace BlockDstAddressSpace>
__device__ void
RunStoreThreadBuffer(const ThreadBufferData* p_thread_buffer,
BlockDstData* p_block_dst,
integral_constant<AddressSpace, ThreadBufferAddressSpace>,
integral_constant<AddressSpace, BlockDstAddressSpace>) const
{
constexpr auto thread_buffer_address_space =
integral_constant<AddressSpace, ThreadBufferAddressSpace>{};
constexpr auto block_dst_address_space =
integral_constant<AddressSpace, BlockDstAddressSpace>{};
constexpr bool has_optimized_address_calculation =
decltype(mThreadwiseStore)::HasWorkingOptimizedAddressCalculation();
// TODO: threadwise copy is still being tweaked
if(has_optimized_address_calculation)
{
mThreadwiseStore.Run_optimized_dst_address_calculation(
p_thread_buffer, p_block_dst, thread_buffer_address_space, block_dst_address_space);
}
else
{
mThreadwiseStore.Run(
p_thread_buffer, p_block_dst, thread_buffer_address_space, block_dst_address_space);
}
}
template <typename ThreadBufferData, typename BlockDstData>
__device__ void RunStoreThreadBuffer(const ThreadBufferData* p_thread_buffer,
BlockDstData* p_block_dst) const
{
#if 1
mThreadwiseStore.template Run<ThreadBufferData,
BlockDstData,
ThreadBufferAddressSpace,
BlockDstAddressSpace>(p_thread_buffer, p_block_dst);
#else // tweaking
mThreadwiseStore.template Run_optimized_dst_address_calculation<ThreadBufferData,
BlockDstData,
ThreadBufferAddressSpace,
BlockDstAddressSpace>(
p_thread_buffer, p_block_dst);
#endif
constexpr auto generic_address_space =
integral_constant<AddressSpace, AddressSpace::generic>{};
RunStoreThreadBuffer(
p_thread_buffer, p_block_dst, generic_address_space, generic_address_space);
}
template <typename BlockSrcData,
typename BlockDstData,
address_space_t BlockSrcAddressSpace = address_space_t::generic,
address_space_t BlockDstAddressSpace = address_space_t::generic>
__device__ void Run(const BlockSrcData* p_block_src, BlockDstData* p_block_dst) const
AddressSpace BlockSrcAddressSpace,
AddressSpace BlockDstAddressSpace>
__device__ void
Run(const BlockSrcData* p_block_src,
BlockDstData* p_block_dst,
integral_constant<AddressSpace, BlockSrcAddressSpace> block_src_address_space,
integral_constant<AddressSpace, BlockDstAddressSpace> block_dst_address_space) const
{
BlockSrcData p_thread_buffer[GetThreadBufferSize()];
RunLoadThreadBuffer<BlockSrcData,
BlockSrcData,
BlockSrcAddressSpace,
address_space_t::generic>(p_block_src, p_thread_buffer);
constexpr auto generic_address_space =
integral_constant<AddressSpace, AddressSpace::generic>{};
RunLoadThreadBuffer(
p_block_src, p_thread_buffer, block_src_address_space, generic_address_space);
// if there is type conversion, it's done during store
RunStoreThreadBuffer<BlockSrcData,
BlockDstData,
address_space_t::generic,
BlockDstAddressSpace>(p_thread_buffer, p_block_dst);
RunStoreThreadBuffer(
p_thread_buffer, p_block_dst, generic_address_space, block_dst_address_space);
}
template <typename BlockSrcData, typename BlockDstData>
__device__ void Run(const BlockSrcData* p_block_src, BlockDstData* p_block_dst) const
{
constexpr auto generic_address_space =
integral_constant<AddressSpace, AddressSpace::generic>{};
Run(p_block_src, p_block_dst, generic_address_space, generic_address_space);
}
template <typename T, bool PositiveDirection>
......
composable_kernel/include/tensor_operation/blockwise_generic_tensor_slice_copy_deprecated.hpp
View file @ 52c3fe05
......@@ -2,15 +2,11 @@
#define CK_BLOCKWISE_GENERIC_TENSOR_SLICE_COPY_DEPRECATED_HPP
#include "common_header.hpp"
#include "ConstantTensorDescriptor.hpp"
#include "ConstantMergedTensorDescriptor.hpp"
#include "ConstantTensorDescriptor_deprecated.hpp"
#include "ConstantMergedTensorDescriptor_deprecated.hpp"
#include "tensor_coordinate_deprecated.hpp"
#include "threadwise_generic_tensor_slice_copy_deprecated.hpp"
#ifndef CK_EXPERIMENTAL_USE_MORE_COMPILE_STATIC_BLOCKWISE_GENERIC_SLICE_COPY_V1
#define CK_EXPERIMENTAL_USE_MORE_COMPILE_STATIC_BLOCKWISE_GENERIC_SLICE_COPY_V1 1
#endif
namespace ck {
// Slice a (normal or merged) tensor, and copy it into another (normal or merged) tensor
......@@ -20,7 +16,7 @@ namespace ck {
// that, on a merged dimension that constains multiple original dimensions, the length of
// the last original dimension need to be evenly dividable by its sub-lengths. Also, the
// repeat-length on the merged dimension need to be 1. These sanity checks are performed
// in constructor of BlockwiseGenericTensorSliceCopy_v1
// in constructor of BlockwiseGenericTensorSliceCopy_v1_deprecated
template <index_t BlockSize,
typename SrcDesc,
typename DstDesc,
......@@ -34,7 +30,7 @@ template <index_t BlockSize,
index_t DstVectorAccessDim,
index_t SrcDataPerAccess,
index_t DstDataPerAccess>
struct BlockwiseGenericTensorSliceCopy_v1
struct BlockwiseGenericTensorSliceCopy_v1_deprecated
{
static constexpr index_t nDim = SrcDesc::GetNumOfDimension();
......@@ -62,7 +58,8 @@ struct BlockwiseGenericTensorSliceCopy_v1
Array<index_t, nOriginalDimSrc> mThreadSrcOriginalMultiId;
Array<index_t, nOriginalDimDst> mThreadDstOriginalMultiId;
__device__ BlockwiseGenericTensorSliceCopy_v1(Array<index_t, nDim> src_block_data_id_begin,
__device__
BlockwiseGenericTensorSliceCopy_v1_deprecated(Array<index_t, nDim> src_block_data_id_begin,
Array<index_t, nDim> dst_block_data_id_begin)
{
// check NDim consistency
......@@ -196,13 +193,13 @@ struct BlockwiseGenericTensorSliceCopy_v1
return make_ConstantTensorDescriptor_packed(SubLengths{} * repeat_lengths);
}
__device__ static constexpr index_t GetRegisterBufferSize()
__device__ static constexpr index_t GetThreadBufferSize()
{
return GetRegisterBufferDescriptor().GetElementSpace();
}
template <typename TData>
__device__ void RunLoadRegisterBuffer(const TData* __restrict__ p_src,
__device__ void RunLoadThreadBuffer(const TData* __restrict__ p_src,
TData* __restrict__ p_buffer) const
{
constexpr auto thread_sub_tensor_lengths = SubLengths{};
......@@ -244,8 +241,8 @@ struct BlockwiseGenericTensorSliceCopy_v1
// that constains multiple original dimensions, the length of the last original
// dimension need to be evenly dividable by its sub-lengths. Also, the repeat-length on
// the merged dimension need to be 1. These sanity checks are performed in constructor
// of BlockwiseGenericTensorSliceCopy_v1
ThreadwiseGenericTensorSliceCopy_v1r2<SrcDesc,
// of BlockwiseGenericTensorSliceCopy_v1_deprecated
ThreadwiseGenericTensorSliceCopy_v1r2_deprecated<SrcDesc,
decltype(thread_buffer_desc),
SubLengths,
SrcDimAccessOrder,
......@@ -258,7 +255,7 @@ struct BlockwiseGenericTensorSliceCopy_v1
}
template <typename TData>
__device__ void RunStoreRegisterBuffer(const TData* __restrict__ p_buffer,
__device__ void RunStoreThreadBuffer(const TData* __restrict__ p_buffer,
TData* __restrict__ p_dst) const
{
constexpr auto thread_sub_tensor_lengths = SubLengths{};
......@@ -299,8 +296,8 @@ struct BlockwiseGenericTensorSliceCopy_v1
// that constains multiple original dimensions, the length of the last original
// dimension need to be evenly dividable by its sub-lengths. Also, the repeat-length on
// the merged dimension need to be 1. These sanity checks are performed in constructor
// of BlockwiseGenericTensorSliceCopy_v1
ThreadwiseGenericTensorSliceCopy_v1r2<decltype(thread_buffer_desc),
// of BlockwiseGenericTensorSliceCopy_v1_deprecated
ThreadwiseGenericTensorSliceCopy_v1r2_deprecated<decltype(thread_buffer_desc),
DstDesc,
SubLengths,
DstDimAccessOrder,
......@@ -315,10 +312,10 @@ struct BlockwiseGenericTensorSliceCopy_v1
template <typename TData>
__device__ void Run(const TData* __restrict__ p_src, TData* __restrict__ p_dst) const
{
TData p_buffer[GetRegisterBufferSize()];
TData p_buffer[GetThreadBufferSize()];
RunLoadRegisterBuffer(p_src, p_buffer);
RunStoreRegisterBuffer(p_buffer, p_dst);
RunLoadThreadBuffer(p_src, p_buffer);
RunStoreThreadBuffer(p_buffer, p_dst);
}
// When moving the slicing windows along a merged dimension, if the strides of the
......@@ -432,14 +429,14 @@ template <index_t BlockSize,
index_t DstVectorAccessDim,
index_t SrcDataPerAccess,
index_t DstDataPerAccess>
struct BlockwiseGenericTensorSliceCopy_v2
struct BlockwiseGenericTensorSliceCopy_v2_deprecated
{
static constexpr index_t nDim = SrcDesc::GetNumOfDimension();
using Index = MultiIndex<nDim>;
__device__ constexpr BlockwiseGenericTensorSliceCopy_v2(const Index& src_block_slice_origin,
const Index& dst_block_slice_origin)
__device__ constexpr BlockwiseGenericTensorSliceCopy_v2_deprecated(
const Index& src_block_slice_origin, const Index& dst_block_slice_origin)
{
static_assert(
nDim == SrcDesc::GetNumOfDimension() && nDim == DstDesc::GetNumOfDimension() &&
......@@ -478,42 +475,96 @@ struct BlockwiseGenericTensorSliceCopy_v2
return ThreadBufferDesc::GetElementSpace();
}
template <typename SrcData,
typename DstData,
address_space_t BlockSrcAddressSpace = address_space_t::generic,
address_space_t ThreadBufferAddressSpace = address_space_t::generic>
__device__ void RunLoadThreadBuffer(const SrcData* p_block_src, DstData* p_thread_buffer) const
template <typename BlockSrcData,
typename ThreadBufferData,
AddressSpace BlockSrcAddressSpace,
AddressSpace ThreadBufferAddressSpace>
__device__ void
RunLoadThreadBuffer(const BlockSrcData* p_block_src,
ThreadBufferData* p_thread_buffer,
integral_constant<AddressSpace, BlockSrcAddressSpace>,
integral_constant<AddressSpace, ThreadBufferAddressSpace>) const
{
mThreadwiseLoad
.template Run<SrcData, DstData, BlockSrcAddressSpace, ThreadBufferAddressSpace>(
p_block_src, p_thread_buffer);
constexpr auto block_src_address_space =
integral_constant<AddressSpace, BlockSrcAddressSpace>{};
constexpr auto thread_buffer_address_space =
integral_constant<AddressSpace, ThreadBufferAddressSpace>{};
mThreadwiseLoad.Run(
p_block_src, p_thread_buffer, block_src_address_space, thread_buffer_address_space);
}
template <typename SrcData,
typename DstData,
address_space_t ThreadBufferAddressSpace = address_space_t::generic,
address_space_t BlockDstAddressSpace = address_space_t::generic>
__device__ void RunStoreThreadBuffer(const SrcData* p_thread_buffer, DstData* p_block_dst) const
template <typename BlockSrcData, typename ThreadBufferData>
__device__ void RunLoadThreadBuffer(const BlockSrcData* p_block_src,
ThreadBufferData* p_thread_buffer) const
{
mThreadwiseStore
.template Run<SrcData, DstData, ThreadBufferAddressSpace, BlockDstAddressSpace>(
p_thread_buffer, p_block_dst);
constexpr auto generic_address_space =
integral_constant<AddressSpace, AddressSpace::generic>{};
RunLoadThreadBuffer(
p_block_src, p_thread_buffer, generic_address_space, generic_address_space);
}
template <typename SrcData,
typename DstData,
address_space_t BlockSrcAddressSpace = address_space_t::generic,
address_space_t BlockDstAddressSpace = address_space_t::generic>
__device__ void Run(const SrcData* p_block_src, DstData* p_block_dst) const
template <typename ThreadBufferData,
typename BlockDstData,
AddressSpace ThreadBufferAddressSpace,
AddressSpace BlockDstAddressSpace>
__device__ void
RunStoreThreadBuffer(const ThreadBufferData* p_thread_buffer,
BlockDstData* p_block_dst,
integral_constant<AddressSpace, ThreadBufferAddressSpace>,
integral_constant<AddressSpace, BlockDstAddressSpace>) const
{
SrcData p_thread_buffer[GetThreadBufferSize()];
constexpr auto thread_buffer_address_space =
integral_constant<AddressSpace, ThreadBufferAddressSpace>{};
constexpr auto block_dst_address_space =
integral_constant<AddressSpace, BlockDstAddressSpace>{};
RunLoadThreadBuffer<SrcData, SrcData, BlockSrcAddressSpace, address_space_t::generic>(
p_block_src, p_thread_buffer);
mThreadwiseStore.Run(
p_thread_buffer, p_block_dst, thread_buffer_address_space, block_dst_address_space);
}
template <typename ThreadBufferData, typename BlockDstData>
__device__ void RunStoreThreadBuffer(const ThreadBufferData* p_thread_buffer,
BlockDstData* p_block_dst) const
{
constexpr auto generic_address_space =
integral_constant<AddressSpace, AddressSpace::generic>{};
RunStoreThreadBuffer(
p_thread_buffer, p_block_dst, generic_address_space, generic_address_space);
}
template <typename BlockSrcData,
typename BlockDstData,
AddressSpace BlockSrcAddressSpace,
AddressSpace BlockDstAddressSpace>
__device__ void
Run(const BlockSrcData* p_block_src,
BlockDstData* p_block_dst,
integral_constant<AddressSpace, BlockSrcAddressSpace> block_src_address_space,
integral_constant<AddressSpace, BlockDstAddressSpace> block_dst_address_space) const
{
BlockSrcData p_thread_buffer[GetThreadBufferSize()];
constexpr auto generic_address_space =
integral_constant<AddressSpace, AddressSpace::generic>{};
RunLoadThreadBuffer(
p_block_src, p_thread_buffer, block_src_address_space, generic_address_space);
// if there is type conversion, it's done during store
RunStoreThreadBuffer<SrcData, DstData, address_space_t::generic, BlockDstAddressSpace>(
p_thread_buffer, p_block_dst);
RunStoreThreadBuffer(
p_thread_buffer, p_block_dst, generic_address_space, block_dst_address_space);
}
template <typename BlockSrcData, typename BlockDstData>
__device__ void Run(const BlockSrcData* p_block_src, BlockDstData* p_block_dst) const
{
constexpr auto generic_address_space =
integral_constant<AddressSpace, AddressSpace::generic>{};
Run(p_block_src, p_block_dst, generic_address_space, generic_address_space);
}
template <typename T, bool PositiveDirection>
......@@ -533,7 +584,7 @@ struct BlockwiseGenericTensorSliceCopy_v2
private:
using ThreadBufferDesc = decltype(make_ConstantTensorDescriptor_packed(SubLengths{}));
using ThreadwiseLoad = ThreadwiseGenericTensorSliceCopy_v2r1<SrcDesc,
using ThreadwiseLoad = ThreadwiseGenericTensorSliceCopy_v2r1_deprecated<SrcDesc,
ThreadBufferDesc,
SubLengths,
SrcDimAccessOrder,
......@@ -543,7 +594,7 @@ struct BlockwiseGenericTensorSliceCopy_v2
SrcDataPerAccess,
1>;
using ThreadwiseStore = ThreadwiseGenericTensorSliceCopy_v2r1<ThreadBufferDesc,
using ThreadwiseStore = ThreadwiseGenericTensorSliceCopy_v2r1_deprecated<ThreadBufferDesc,
DstDesc,
SubLengths,
DstDimAccessOrder,
......
composable_kernel/include/tensor_operation/threadwise_direct_convolution.hpp
View file @ 52c3fe05
......@@ -2,7 +2,7 @@
#define CK_THREADWISE_DIRECT_CONVOLUTION_HPP
#include "common_header.hpp"
#include "ConstantTensorDescriptor.hpp"
#include "ConstantTensorDescriptor_deprecated.hpp"
#include "threadwise_tensor_slice_copy.hpp"
namespace ck {
......
composable_kernel/include/tensor_operation/threadwise_gemm.hpp
View file @ 52c3fe05
......@@ -3,102 +3,164 @@
#include "common_header.hpp"
#include "ConstantMatrixDescriptor.hpp"
#include "math.hpp"
namespace ck {
template <class Float, class Matrix>
template <typename Float, class Matrix>
__device__ void threadwise_matrix_set_zero(Matrix, Float* __restrict__ p_thread)
{
for(index_t i = 0; i < Matrix::NRow(); ++i)
{
for(index_t j = 0; j < Matrix::NCol(); ++j)
{
const index_t id = Matrix::GetOffsetFromMultiIndex(i, j);
const index_t id = Matrix::CalculateOffset(i, j);
p_thread[id] = Float(0);
}
}
}
template <class Float,
class SrcMatrix,
class DstMatrix,
index_t NRow,
index_t NCol,
index_t DataPerRead>
__device__ void threadwise_matrix_copy(SrcMatrix,
const Float* __restrict__ p_src,
DstMatrix,
Float* __restrict__ p_dst,
Sequence<NRow, NCol>,
Number<DataPerRead>)
template <typename SrcMatrix,
typename DstMatrix,
index_t NSliceRow,
index_t NSliceCol,
index_t DataPerAccess>
struct ThreadwiseMatrixSliceCopy
{
static_assert(NCol % DataPerRead == 0, "wrong! should be NCol % == DataPerRead == 0");
using vector_t = typename vector_type<Float, DataPerRead>::MemoryType;
__device__ constexpr ThreadwiseMatrixSliceCopy()
{
static_assert(SrcMatrix::RowStride() % DataPerAccess == 0 &&
DstMatrix::RowStride() % DataPerAccess == 0,
"wrong! wrong alignment");
static_assert(NSliceCol % DataPerAccess == 0,
"wrong! should be NSliceCol % DataPerAccess == 0");
}
constexpr auto src_mtx = SrcMatrix{};
constexpr auto dst_mtx = DstMatrix{};
template <typename Data>
__device__ static void Run(const Data* p_src, Data* p_dst)
{
using vector_t = typename vector_type<Data, DataPerAccess>::MemoryType;
for(index_t i = 0; i < NRow; ++i)
for(index_t i = 0; i < NSliceRow; ++i)
{
for(index_t j = 0; j < NCol; j += DataPerRead)
for(index_t j = 0; j < NSliceCol; j += DataPerAccess)
{
const index_t src_index = src_mtx.GetOffsetFromMultiIndex(i, j);
const index_t dst_index = dst_mtx.GetOffsetFromMultiIndex(i, j);
const index_t src_index = SrcMatrix::CalculateOffset(i, j);
const index_t dst_index = DstMatrix::CalculateOffset(i, j);
*reinterpret_cast<vector_t*>(&p_dst[dst_index]) =
*reinterpret_cast<const vector_t*>(&p_src[src_index]);
}
}
}
}
};
template <class MatrixA,
class MatrixB,
class MatrixC,
bool TransA,
bool TransB,
bool TransC,
class FloatA,
class FloatB,
class FloatC>
__device__ void threadwise_gemm(MatrixA,
integral_constant<bool, TransA>,
const FloatA* __restrict__ p_a_thread,
MatrixB,
integral_constant<bool, TransB>,
const FloatB* __restrict__ p_b_thread,
MatrixC,
integral_constant<bool, TransC>,
FloatC* __restrict__ p_c_thread)
// C += transpose(A) * B
// Element of matrix can be vectorized data
template <typename MatrixA, typename MatrixB, typename MatrixC>
struct ThreadwiseGemmTransANormalBNormalC
{
static_if<TransA && (!TransB) && (!TransC)>{}([&](auto) {
constexpr auto a_mtx = MatrixA{};
constexpr auto b_mtx = MatrixB{};
constexpr auto c_mtx = MatrixC{};
__device__ constexpr ThreadwiseGemmTransANormalBNormalC()
{
static_assert(MatrixA::NRow() == MatrixB::NRow() && MatrixA::NCol() == MatrixC::NRow() &&
MatrixB::NCol() == MatrixC::NCol(),
"wrong!");
}
constexpr index_t M = c_mtx.NRow();
constexpr index_t N = c_mtx.NCol();
constexpr index_t K = a_mtx.NRow(); // A is transposed
template <typename FloatA, typename FloatB, typename FloatC>
__device__ static void Run_source(const FloatA* p_a, const FloatB* p_b, FloatC* p_c)
{
constexpr index_t M = MatrixC::NRow();
constexpr index_t N = MatrixC::NCol();
constexpr index_t K = MatrixA::NRow(); // A is transposed
for(index_t k = 0; k < K; ++k)
{
for(index_t i = 0; i < M; ++i)
for(index_t m = 0; m < M; ++m)
{
for(index_t j = 0; j < N; ++j)
for(index_t n = 0; n < N; ++n)
{
const index_t aindex = a_mtx.GetOffsetFromMultiIndex(k, i); // A is transposed
const index_t bindex = b_mtx.GetOffsetFromMultiIndex(k, j);
const index_t cindex = c_mtx.GetOffsetFromMultiIndex(i, j);
const index_t aindex = MatrixA::CalculateOffset(k, m); // A is transposed
const index_t bindex = MatrixB::CalculateOffset(k, n);
const index_t cindex = MatrixC::CalculateOffset(m, n);
p_c_thread[cindex] += p_a_thread[aindex] * p_b_thread[bindex];
p_c[cindex] +=
inner_product_with_conversion<FloatC>{}(p_a[aindex], p_b[bindex]);
}
}
}
}).Else([&](auto fwd) {
// not implemented
static_assert(fwd(false), "wrong! support for this config is not implemented");
}
#if CK_THREADWISE_GEMM_USE_AMD_INLINE_ASM
template <typename FloatA, typename FloatB, typename FloatC>
__device__ static void Run_amd_asm(const FloatA* p_a, const FloatB* p_b, FloatC* p_c)
{
constexpr index_t M = MatrixC::NRow();
constexpr index_t N = MatrixC::NCol();
constexpr index_t K = MatrixA::NRow(); // A is transposed
static_assert(N == 4 || N == 2, "wrong! this config not supported by asm yet");
for(index_t k = 0; k < K; ++k)
{
for(index_t m = 0; m < M; ++m)
{
const index_t aindex = MatrixA::CalculateOffset(k, m); // A is transposed
static_if<N == 2>{}([&](auto) {
const index_t bindex_0 = MatrixB::CalculateOffset(k, 0);
const index_t bindex_1 = MatrixB::CalculateOffset(k, 1);
const index_t cindex_0 = MatrixC::CalculateOffset(m, 0);
const index_t cindex_1 = MatrixC::CalculateOffset(m, 1);
__outer_product_1x2(
p_a[aindex], p_b[bindex_0], p_b[bindex_1], p_c[cindex_0], p_c[cindex_1]);
});
}
static_if<N == 4>{}([&](auto) {
const index_t bindex_0 = MatrixB::CalculateOffset(k, 0);
const index_t bindex_1 = MatrixB::CalculateOffset(k, 1);
const index_t bindex_2 = MatrixB::CalculateOffset(k, 2);
const index_t bindex_3 = MatrixB::CalculateOffset(k, 3);
const index_t cindex_0 = MatrixC::CalculateOffset(m, 0);
const index_t cindex_1 = MatrixC::CalculateOffset(m, 1);
const index_t cindex_2 = MatrixC::CalculateOffset(m, 2);
const index_t cindex_3 = MatrixC::CalculateOffset(m, 3);
__outer_product_1x4(p_a[aindex],
p_b[bindex_0],
p_b[bindex_1],
p_b[bindex_2],
p_b[bindex_3],
p_c[cindex_0],
p_c[cindex_1],
p_c[cindex_2],
p_c[cindex_3]);
});
}
}
}
#endif
template <typename FloatA, typename FloatB, typename FloatC>
__device__ static void Run(const FloatA* p_a, const FloatB* p_b, FloatC* p_c)
{
#if CK_THREADWISE_GEMM_USE_AMD_INLINE_ASM
constexpr bool has_amd_asm = is_same<FloatC, float>{} &&
((is_same<FloatA, float>{} && is_same<FloatB, float>{}) ||
(is_same<FloatA, half2_t>{} && is_same<FloatB, half2_t>{}) ||
(is_same<FloatA, half4_t>{} && is_same<FloatB, half4_t>{}));
static_if<has_amd_asm>{}([&](auto fwd) {
Run_amd_asm(p_a, p_b, fwd(p_c));
}).Else([&](auto) { Run_source(p_a, p_b, p_c); });
#else
Run_source(p_a, p_b, p_c);
#endif
}
};
} // namespace ck
#endif
composable_kernel/include/tensor_operation/threadwise_generic_tensor_op.hpp
View file @ 52c3fe05
......@@ -2,8 +2,8 @@
#define CK_THREADWISE_GENERIC_TENSOR_OP_HPP
#include "common_header.hpp"
#include "ConstantTensorDescriptor.hpp"
#include "ConstantMergedTensorDescriptor.hpp"
#include "ConstantTensorDescriptor_deprecated.hpp"
#include "ConstantMergedTensorDescriptor_deprecated.hpp"
namespace ck {
template <class Float, class TDesc>
......
composable_kernel/include/tensor_operation/threadwise_generic_tensor_slice_copy.hpp
View file @ 52c3fe05
......@@ -6,14 +6,6 @@
#include "tensor_descriptor_helper.hpp"
#include "tensor_coordinate.hpp"
#ifndef CK_USE_AMD_INTRINSIC
#define CK_USE_AMD_INTRINSIC 1
#endif
#ifndef CK_USE_AMD_INTRINSIC_BUFFER_LOAD_STORE
#define CK_USE_AMD_INTRINSIC_BUFFER_LOAD_STORE 1
#endif
namespace ck {
// This version use multi-index transformation
......@@ -76,9 +68,12 @@ struct ThreadwiseGenericTensorSliceCopy_v4r2
// Will do padding check on dst data: No write if dst data is in paddin area.
template <typename SrcData,
typename DstData,
address_space_t SrcAddressSpace = address_space_t::generic,
address_space_t DstAddressSpace = address_space_t::generic>
__device__ void Run(const SrcData* p_src, DstData* p_dst) const
AddressSpace SrcAddressSpace,
AddressSpace DstAddressSpace>
__device__ void Run(const SrcData* p_src,
DstData* p_dst,
integral_constant<AddressSpace, SrcAddressSpace>,
integral_constant<AddressSpace, DstAddressSpace>) const
{
using src_vector_t = typename vector_type<SrcData, SrcDataPerAccess>::MemoryType;
using dst_vector_t = typename vector_type<DstData, DstDataPerAccess>::MemoryType;
......@@ -122,15 +117,14 @@ struct ThreadwiseGenericTensorSliceCopy_v4r2
// Check src vector's padding situation, only check the first data in this src
// vector. It's user's responsiblity to make sure all data in the src vector
// has
// the same padding situation
// has the same padding situation
if(src_coord.IsUpperIndexMappedToValidOffset())
{
static_if<SrcAddressSpace == address_space_t::global>{}([&](auto) {
#if CK_USE_AMD_INTRINSIC && CK_USE_AMD_INTRINSIC_BUFFER_LOAD_STORE
static_if<SrcAddressSpace == AddressSpace::global>{}([&](auto fwd) {
#if CK_USE_AMD_BUFFER_ADDRESSING
*reinterpret_cast<src_vector_t*>(&p_src_long_vector[buffer_offset]) =
__buffer_load<SrcData, SrcDataPerAccess>(
p_src, src_coord.GetOffset(), 0);
fwd(p_src), src_coord.GetOffset(), 0);
#else
*reinterpret_cast<src_vector_t*>(&p_src_long_vector[buffer_offset]) =
*reinterpret_cast<const src_vector_t*>(&p_src[src_coord.GetOffset()]);
......@@ -163,15 +157,14 @@ struct ThreadwiseGenericTensorSliceCopy_v4r2
// Check dst vector's padding situation, only check the first data in this dst
// vector. It's user's responsiblity to make sure all data in the dst vector
// has
// the same padding situation
// has the same padding situation
if(dst_coord.IsUpperIndexMappedToValidOffset())
{
static_if<DstAddressSpace == address_space_t::global>{}([&](auto) {
#if CK_USE_AMD_INTRINSIC && CK_USE_AMD_INTRINSIC_BUFFER_LOAD_STORE
static_if<DstAddressSpace == AddressSpace::global>{}([&](auto fwd) {
#if CK_USE_AMD_BUFFER_ADDRESSING
__buffer_store<DstData, DstDataPerAccess>(
*reinterpret_cast<dst_vector_t*>(&p_dst_long_vector[buffer_offset]),
p_dst,
fwd(p_dst),
dst_coord.GetOffset(),
0);
#else
......@@ -188,6 +181,15 @@ struct ThreadwiseGenericTensorSliceCopy_v4r2
});
}
template <typename SrcData, typename DstData>
__device__ void Run(const SrcData* p_src, DstData* p_dst) const
{
constexpr auto generic_address_space =
integral_constant<AddressSpace, AddressSpace::generic>{};
Run(p_src, p_dst, generic_address_space, generic_address_space);
}
// Modify Length to 1, if Mask is set to false
// Used for isolating linear dimension from non-linear dimensions
template <index_t... Lengths, index_t... Mask>
......@@ -202,12 +204,16 @@ struct ThreadwiseGenericTensorSliceCopy_v4r2
// Will do padding check on src data: Read 0 if src data is in padding area.
// Will do padding check on dst data: No write if dst data is in paddin area.
// This version is optimized for address calculation of src tensor
// TODO: this function is not compiled to expected ISA
template <typename SrcData,
typename DstData,
address_space_t SrcAddressSpace = address_space_t::generic,
address_space_t DstAddressSpace = address_space_t::generic>
__device__ void Run_optimized_src_address_calculation(const SrcData* p_src,
DstData* p_dst) const
AddressSpace SrcAddressSpace,
AddressSpace DstAddressSpace>
__device__ void
Run_optimized_src_address_calculation(const SrcData* p_src,
DstData* p_dst,
integral_constant<AddressSpace, SrcAddressSpace>,
integral_constant<AddressSpace, DstAddressSpace>) const
{
using src_vector_t = typename vector_type<SrcData, SrcDataPerAccess>::MemoryType;
using dst_vector_t = typename vector_type<DstData, DstDataPerAccess>::MemoryType;
......@@ -287,14 +293,14 @@ struct ThreadwiseGenericTensorSliceCopy_v4r2
const auto src_coord =
src_nonlinear_coord + (linear_dim_data_steps + scalar_id);
#if 1 // tweaking
#if CK_EXPERIMENTAL_TENSOR_COORDINATE_USE_CALCULATE_OFFSET_DIFF // tweaking
// this is src compile-time offset
const index_t src_linear_offset =
src_coord.GetOffset() - src_nonlinear_coord.GetOffset();
src_nonlinear_coord.CalculateOffsetDiff(linear_dim_data_steps + scalar_id);
#else
// this is src compile-time offset
const index_t src_linear_offset =
src_nonlinear_coord.CalculateOffsetDiff(linear_dim_data_steps + scalar_id);
src_coord.GetOffset() - src_nonlinear_coord.GetOffset();
#endif
// Check src vector's padding situation, only check the first data in
......@@ -302,8 +308,8 @@ struct ThreadwiseGenericTensorSliceCopy_v4r2
// the src vector has the same padding situation
if(src_coord.IsUpperIndexMappedToValidOffset())
{
static_if<SrcAddressSpace == address_space_t::global>{}([&](auto) {
#if CK_USE_AMD_INTRINSIC && CK_USE_AMD_INTRINSIC_BUFFER_LOAD_STORE
static_if<SrcAddressSpace == AddressSpace::global>{}([&](auto) {
#if CK_USE_AMD_BUFFER_ADDRESSING
*reinterpret_cast<src_vector_t*>(&p_src_long_vector[buffer_offset]) =
__buffer_load<SrcData, SrcDataPerAccess>(
p_src, src_nonlinear_coord.GetOffset(), src_linear_offset);
......@@ -360,12 +366,16 @@ struct ThreadwiseGenericTensorSliceCopy_v4r2
// Will do padding check on src data: Read 0 if src data is in padding area.
// Will do padding check on dst data: No write if dst data is in paddin area.
// This version is optimized for address calculation of dst tensor
// TODO: this function is not compiled to expected ISA
template <typename SrcData,
typename DstData,
address_space_t SrcAddressSpace = address_space_t::generic,
address_space_t DstAddressSpace = address_space_t::generic>
__device__ void Run_optimized_dst_address_calculation(const SrcData* p_src,
DstData* p_dst) const
AddressSpace SrcAddressSpace,
AddressSpace DstAddressSpace>
__device__ void
Run_optimized_dst_address_calculation(const SrcData* p_src,
DstData* p_dst,
integral_constant<AddressSpace, SrcAddressSpace>,
integral_constant<AddressSpace, DstAddressSpace>) const
{
using src_vector_t = typename vector_type<SrcData, SrcDataPerAccess>::MemoryType;
using dst_vector_t = typename vector_type<DstData, DstDataPerAccess>::MemoryType;
......@@ -476,14 +486,14 @@ struct ThreadwiseGenericTensorSliceCopy_v4r2
const auto dst_coord =
dst_nonlinear_coord + (linear_dim_data_steps + scalar_id);
#if 1 // tweaking
#if CK_EXPERIMENTAL_TENSOR_COORDINATE_USE_CALCULATE_OFFSET_DIFF // tweaking
// this is dst compile-time offset
const index_t dst_linear_offset =
dst_coord.GetOffset() - dst_nonlinear_coord.GetOffset();
dst_nonlinear_coord.CalculateOffsetDiff(linear_dim_data_steps + scalar_id);
#else
// this is dst compile-time offset
const index_t dst_linear_offset =
dst_nonlinear_coord.CalculateOffsetDiff(linear_dim_data_steps + scalar_id);
dst_coord.GetOffset() - dst_nonlinear_coord.GetOffset();
#endif
// Check dst vector's padding situation, only check the first data in
......@@ -491,8 +501,8 @@ struct ThreadwiseGenericTensorSliceCopy_v4r2
// the dst vector has the same padding situation
if(dst_coord.IsUpperIndexMappedToValidOffset())
{
static_if<DstAddressSpace == address_space_t::global>{}([&](auto) {
#if CK_USE_AMD_INTRINSIC && CK_USE_AMD_INTRINSIC_BUFFER_LOAD_STORE
static_if<DstAddressSpace == AddressSpace::global>{}([&](auto) {
#if CK_USE_AMD_BUFFER_ADDRESSING
__buffer_store<DstData, DstDataPerAccess>(
*reinterpret_cast<dst_vector_t*>(&p_dst_long_vector[buffer_offset]),
p_dst,
......@@ -514,6 +524,15 @@ struct ThreadwiseGenericTensorSliceCopy_v4r2
});
}
__device__ static constexpr bool HasWorkingOptimizedAddressCalculation()
{
#if CK_EXPERIMENTAL_THREADWISE_COPY_V4R2_USE_OPTIMIZED_ADDRESS_CACLULATION // tweaking
return true;
#else
return false;
#endif
}
template <typename T, bool PositiveDirection>
__device__ void MoveSrcSliceWindow(const T& step_sizes_,
integral_constant<bool, PositiveDirection>)
......
composable_kernel/include/tensor_operation/threadwise_generic_tensor_slice_copy_deprecated.hpp
View file @ 52c3fe05
......@@ -2,261 +2,12 @@
#define CK_THREADWISE_GENERIC_TENSOR_SLICE_COPY_DEPRECATED_HPP
#include "common_header.hpp"
#include "ConstantTensorDescriptor.hpp"
#include "ConstantMergedTensorDescriptor.hpp"
#include "ConstantTensorDescriptor_deprecated.hpp"
#include "ConstantMergedTensorDescriptor_deprecated.hpp"
#include "tensor_coordinate_deprecated.hpp"
#ifndef CK_EXPERIMENTAL_USE_MORE_COMPILE_STATIC_THREADWISE_GENERIC_TENSOR_SLICE_COPY_V1R1
#define CK_EXPERIMENTAL_USE_MORE_COMPILE_STATIC_THREADWISE_GENERIC_TENSOR_SLICE_COPY_V1R1 0
#endif
#ifndef CK_EXPERIMENTAL_USE_MORE_COMPILE_STATIC_THREADWISE_GENERIC_TENSOR_SLICE_COPY_V1R2
#define CK_EXPERIMENTAL_USE_MORE_COMPILE_STATIC_THREADWISE_GENERIC_TENSOR_SLICE_COPY_V1R2 0
#endif
#ifndef CK_EXPERIMENTAL_USE_MORE_COMPILE_STATIC_THREADWISE_GENERIC_TENSOR_SLICE_COPY_V2R1
#define CK_EXPERIMENTAL_USE_MORE_COMPILE_STATIC_THREADWISE_GENERIC_TENSOR_SLICE_COPY_V2R1 0
#endif
#ifndef CK_USE_AMD_INTRINSIC
#define CK_USE_AMD_INTRINSIC 1
#endif
#ifndef CK_USE_AMD_INTRINSIC_BUFFER_LOAD_STORE
#define CK_USE_AMD_INTRINSIC_BUFFER_LOAD_STORE 1
#endif
namespace ck {
// This threadwise copy allow vector access of src and dst.
// It allows the dimensions of vector access to be different on src and dst.
// It also allows the vector size to be different on src and dst.
// It also allows order of access to be different on src and dst.
// It use register as buffer to hold all data moving from src to dst.
// It is designed for copying small amount of data, and src and dst are
// device memory or LDS.
// When copying large amout of data, let's hope compiler will reduce register
// used for the buffer.
template <typename SrcDesc,
typename DstDesc,
typename SliceLengths,
typename SrcDimAccessOrder,
typename DstDimAccessOrder,
index_t SrcVectorAccessDim,
index_t DstVectorAccessDim,
index_t SrcDataPerAccess,
index_t DstDataPerAccess>
struct ThreadwiseGenericTensorSliceCopy_v1r1
{
static constexpr index_t nDim = SliceLengths::GetSize();
__device__ constexpr ThreadwiseGenericTensorSliceCopy_v1r1(
Array<index_t, nDim> src_slice_origin, Array<index_t, nDim> dst_slice_origin)
: mSrcSliceOrigin(src_slice_origin), mDstSliceOrigin(dst_slice_origin)
{
static_assert(nDim == SrcDesc::GetNumOfDimension() &&
nDim == DstDesc::GetNumOfDimension() && nDim == SliceLengths::GetSize() &&
nDim == SrcDimAccessOrder::GetSize() &&
nDim == DstDimAccessOrder::GetSize(),
"wrong! # of dimensions not the same");
static_assert(is_valid_sequence_map<SrcDimAccessOrder>::value &&
is_valid_sequence_map<DstDimAccessOrder>::value,
"wrong! map is not valid");
static_assert(SliceLengths{}[SrcVectorAccessDim] % SrcDataPerAccess == 0 &&
SliceLengths{}[DstVectorAccessDim] % DstDataPerAccess == 0,
"wrong! cannot evenly divide");
// check vectorized memory access
constexpr auto src_vector_access_dim = Number<SrcVectorAccessDim>{};
constexpr auto dst_vector_access_dim = Number<DstVectorAccessDim>{};
static_if<!SrcDesc::ContainMultipleOriginalDimensions(src_vector_access_dim)>{}(
[&](auto fwd) {
static_assert(
(fwd(SrcDesc{}).GetStride(src_vector_access_dim) == 1 || SrcDataPerAccess == 1),
"wrong! vectorized access is allowed only if stride == 1");
})
.Else([&](auto fwd) {
static_assert(
(fwd(SrcDesc{}).GetLastOriginalDimensionStride(src_vector_access_dim) == 1 ||
SrcDataPerAccess == 1),
"wrong! vectorized access is allowed only if stride == 1");
});
static_if<!DstDesc::ContainMultipleOriginalDimensions(dst_vector_access_dim)>{}(
[&](auto fwd) {
static_assert(
(fwd(DstDesc{}).GetStride(dst_vector_access_dim) == 1 || DstDataPerAccess == 1),
"wrong! vectorized access is allowed only if stride == 1");
})
.Else([&](auto fwd) {
static_assert(
(fwd(DstDesc{}).GetLastOriginalDimensionStride(dst_vector_access_dim) == 1 ||
DstDataPerAccess == 1),
"wrong! vectorized access is allowed only if stride == 1");
});
}
__device__ constexpr ThreadwiseGenericTensorSliceCopy_v1r1()
: ThreadwiseGenericTensorSliceCopy_v1r1(make_zero_array<index_t, nDim>(),
make_zero_array<index_t, nDim>())
{
}
__device__ void SetSrcSliceOrigin(Array<index_t, nDim> src_slice_origin)
{
mSrcSliceOrigin = src_slice_origin;
}
__device__ void SetDstSliceOrigin(Array<index_t, nDim> dst_slice_origin)
{
mDstSliceOrigin = dst_slice_origin;
}
template <typename TData>
__device__ void Run(const TData* p_src, TData* p_dst) const
{
constexpr auto buffer_desc = make_ConstantTensorDescriptor_packed(SliceLengths{});
TData p_buffer_[buffer_desc.GetElementSpace()];
TData* p_buffer = p_buffer_;
// copy data from src into buffer
{
using vector_t = typename vector_type<TData, SrcDataPerAccess>::MemoryType;
constexpr auto src_vector_access_dim = Number<SrcVectorAccessDim>{};
constexpr auto src_data_per_access = Number<SrcDataPerAccess>{};
constexpr auto src_access_lengths = SliceLengths::Modify(
src_vector_access_dim,
SliceLengths::Get(src_vector_access_dim) / src_data_per_access);
#if CK_EXPERIMENTAL_USE_MORE_COMPILE_STATIC_THREADWISE_GENERIC_TENSOR_SLICE_COPY_V1R1
static_ford<decltype(src_access_lengths), SrcDimAccessOrder>{}([&](auto src_access_id) {
constexpr auto src_data_begin_id = src_access_id.Modify(
src_vector_access_dim,
src_access_id[src_vector_access_dim] * src_data_per_access);
const index_t src_offset =
SrcDesc::GetOffsetFromMultiIndex(mSrcSliceOrigin + src_data_begin_id);
// load vector from src
const vector_t vector_data = *reinterpret_cast<const vector_t*>(&p_src[src_offset]);
// unpack vector into buffer
static_for<0, SrcDataPerAccess, 1>{}([&](auto i) {
constexpr auto scalar_id =
typename uniform_sequence_gen<nDim, 0>::type{}.Modify(src_vector_access_dim,
i);
constexpr index_t buffer_offset =
buffer_desc.GetOffsetFromMultiIndex(src_data_begin_id + scalar_id);
p_buffer[buffer_offset] = reinterpret_cast<const TData*>(&vector_data)[i];
});
});
#else
ford<decltype(src_access_lengths), SrcDimAccessOrder>{}([&](auto src_access_id) {
auto src_data_begin_id = src_access_id;
src_data_begin_id(src_vector_access_dim) =
src_access_id[src_vector_access_dim] * src_data_per_access;
const index_t src_offset =
SrcDesc::GetOffsetFromMultiIndex(mSrcSliceOrigin + src_data_begin_id);
// load vector from src
const vector_t vector_data = *reinterpret_cast<const vector_t*>(&p_src[src_offset]);
// unpack vector into buffer
for(index_t i = 0; i < SrcDataPerAccess; ++i)
{
auto scalar_id = make_zero_array<index_t, nDim>();
scalar_id(src_vector_access_dim) = i;
const index_t buffer_offset =
buffer_desc.GetOffsetFromMultiIndex(src_data_begin_id + scalar_id);
p_buffer[buffer_offset] = reinterpret_cast<const TData*>(&vector_data)[i];
}
});
#endif
}
// copy data from buffer to dst
{
using vector_t = typename vector_type<TData, DstDataPerAccess>::MemoryType;
constexpr auto dst_vector_access_dim = Number<DstVectorAccessDim>{};
constexpr auto dst_data_per_access = Number<DstDataPerAccess>{};
constexpr auto dst_access_lengths = SliceLengths::Modify(
dst_vector_access_dim,
SliceLengths::Get(dst_vector_access_dim) / dst_data_per_access);
#if CK_EXPERIMENTAL_USE_MORE_COMPILE_STATIC_THREADWISE_GENERIC_TENSOR_SLICE_COPY_V1R1
static_ford<decltype(dst_access_lengths), DstDimAccessOrder>{}([&](auto dst_access_id) {
constexpr auto dst_data_begin_id = dst_access_id.Modify(
dst_vector_access_dim,
dst_access_id[dst_vector_access_dim] * dst_data_per_access);
vector_t vector_data{};
// pack vector from buffer
static_for<0, DstDataPerAccess, 1>{}([&](auto i) {
constexpr auto scalar_id =
typename uniform_sequence_gen<nDim, 0>::type{}.Modify(dst_vector_access_dim,
i);
constexpr index_t buffer_offset =
buffer_desc.GetOffsetFromMultiIndex(dst_data_begin_id + scalar_id);
reinterpret_cast<TData*>(&vector_data)[i] = p_buffer[buffer_offset];
});
const index_t dst_offset =
DstDesc::GetOffsetFromMultiIndex(mDstSliceOrigin + dst_data_begin_id);
// store vector into dst
*reinterpret_cast<vector_t*>(&p_dst[dst_offset]) = vector_data;
});
#else
ford<decltype(dst_access_lengths), DstDimAccessOrder>{}([&](auto dst_access_id) {
auto dst_data_begin_id = dst_access_id;
dst_data_begin_id(dst_vector_access_dim) =
dst_access_id[dst_vector_access_dim] * dst_data_per_access;
vector_t vector_data{};
// pack vector from buffer
for(index_t i = 0; i < DstDataPerAccess; ++i)
{
auto scalar_id = make_zero_array<index_t, nDim>();
scalar_id(dst_vector_access_dim) = i;
const index_t buffer_offset =
buffer_desc.GetOffsetFromMultiIndex(dst_data_begin_id + scalar_id);
reinterpret_cast<TData*>(&vector_data)[i] = p_buffer[buffer_offset];
}
const index_t dst_offset =
DstDesc::GetOffsetFromMultiIndex(mDstSliceOrigin + dst_data_begin_id);
// store vector into dst
*reinterpret_cast<vector_t*>(&p_dst[dst_offset]) = vector_data;
});
#endif
}
}
private:
Array<index_t, nDim> mSrcSliceOrigin;
Array<index_t, nDim> mDstSliceOrigin;
};
// This threadwise copy allow vector access of src and dst.
// It allows the vector size to be different on src and dst.
// The dimensions of vector access should be the same on src and dst.
......@@ -270,11 +21,11 @@ template <typename SrcDesc,
index_t VectorAccessDim,
index_t SrcDataPerAccess,
index_t DstDataPerAccess>
struct ThreadwiseGenericTensorSliceCopy_v1r2
struct ThreadwiseGenericTensorSliceCopy_v1r2_deprecated
{
static constexpr index_t nDim = SliceLengths::GetSize();
__device__ constexpr ThreadwiseGenericTensorSliceCopy_v1r2(
__device__ constexpr ThreadwiseGenericTensorSliceCopy_v1r2_deprecated(
Array<index_t, nDim> src_slice_origin, Array<index_t, nDim> dst_slice_origin)
: mSrcSliceOrigin(src_slice_origin), mDstSliceOrigin(dst_slice_origin)
{
......@@ -313,8 +64,8 @@ struct ThreadwiseGenericTensorSliceCopy_v1r2
});
}
__device__ constexpr ThreadwiseGenericTensorSliceCopy_v1r2()
: ThreadwiseGenericTensorSliceCopy_v1r2(make_zero_array<index_t, nDim>(),
__device__ constexpr ThreadwiseGenericTensorSliceCopy_v1r2_deprecated()
: ThreadwiseGenericTensorSliceCopy_v1r2_deprecated(make_zero_array<index_t, nDim>(),
make_zero_array<index_t, nDim>())
{
}
......@@ -329,11 +80,11 @@ struct ThreadwiseGenericTensorSliceCopy_v1r2
mDstSliceOrigin = dst_slice_origin;
}
template <typename TData>
__device__ void Run(const TData* p_src, TData* p_dst) const
template <class SrcData, class DstData>
__device__ void Run(const SrcData* p_src, DstData* p_dst) const
{
using src_vector_t = typename vector_type<TData, SrcDataPerAccess>::MemoryType;
using dst_vector_t = typename vector_type<TData, DstDataPerAccess>::MemoryType;
using src_vector_t = typename vector_type<SrcData, SrcDataPerAccess>::MemoryType;
using dst_vector_t = typename vector_type<DstData, DstDataPerAccess>::MemoryType;
constexpr auto vector_access_dim = Number<VectorAccessDim>{};
......@@ -345,46 +96,6 @@ struct ThreadwiseGenericTensorSliceCopy_v1r2
constexpr auto long_vector_access_lengths = SliceLengths::Modify(
vector_access_dim, SliceLengths::Get(vector_access_dim) / long_vector_size);
#if CK_EXPERIMENTAL_USE_MORE_COMPILE_STATIC_THREADWISE_GENERIC_TENSOR_SLICE_COPY_V1R2
static_ford<decltype(long_vector_access_lengths), DimAccessOrder>{}([&](
auto long_vector_access_id) {
// data id w.r.t slicing-window
constexpr auto long_vector_data_begin_id = long_vector_access_id.Modify(
vector_access_dim, long_vector_access_id[vector_access_dim] * long_vector_size);
// buffer to hold a long-vector
TData p_long_vector[long_vector_size];
// load data from src to the long-vector buffer
static_for<0, long_vector_size / src_data_per_access, 1>{}([&](auto i) {
constexpr auto scalar_id = typename uniform_sequence_gen<nDim, 0>::type{}.Modify(
vector_access_dim, i * src_data_per_access);
const index_t src_offset = SrcDesc::GetOffsetFromMultiIndex(
mSrcSliceOrigin + (long_vector_data_begin_id + scalar_id));
constexpr index_t buffer_offset = i * src_data_per_access;
*reinterpret_cast<src_vector_t*>(&p_long_vector[buffer_offset]) =
*reinterpret_cast<const src_vector_t*>(&p_src[src_offset]);
});
// store data from the long-vector buffer to dst
static_for<0, long_vector_size / dst_data_per_access, 1>{}([&](auto i) {
constexpr auto scalar_id = typename uniform_sequence_gen<nDim, 0>::type{}.Modify(
vector_access_dim, i * dst_data_per_access);
constexpr index_t buffer_offset = i * dst_data_per_access;
const index_t dst_offset = DstDesc::GetOffsetFromMultiIndex(
mDstSliceOrigin + (long_vector_data_begin_id + scalar_id));
*reinterpret_cast<dst_vector_t*>(&p_dst[dst_offset]) =
*reinterpret_cast<dst_vector_t*>(&p_long_vector[buffer_offset]);
});
});
#else
ford<decltype(long_vector_access_lengths), DimAccessOrder>{}(
[&](auto long_vector_access_id) {
......@@ -394,7 +105,8 @@ struct ThreadwiseGenericTensorSliceCopy_v1r2
long_vector_size * long_vector_access_id[vector_access_dim];
// buffer to hold a long-vector
TData p_long_vector[long_vector_size];
SrcData p_src_long_vector[long_vector_size];
DstData p_dst_long_vector[long_vector_size];
// load data from src to the long-vector buffer
for(index_t i = 0; i < long_vector_size / src_data_per_access; ++i)
......@@ -407,10 +119,16 @@ struct ThreadwiseGenericTensorSliceCopy_v1r2
const index_t buffer_offset = i * src_data_per_access;
*reinterpret_cast<src_vector_t*>(&p_long_vector[buffer_offset]) =
*reinterpret_cast<src_vector_t*>(&p_src_long_vector[buffer_offset]) =
*reinterpret_cast<const src_vector_t*>(&p_src[src_offset]);
}
// type conversion
for(index_t i = 0; i < long_vector_size; ++i)
{
p_dst_long_vector[i] = type_convert<DstData>{}(p_src_long_vector[i]);
}
// store data from the long-vector buffer to dst
for(index_t i = 0; i < long_vector_size / dst_data_per_access; ++i)
{
......@@ -423,10 +141,9 @@ struct ThreadwiseGenericTensorSliceCopy_v1r2
mDstSliceOrigin + (long_vector_data_begin_id + scalar_id));
*reinterpret_cast<dst_vector_t*>(&p_dst[dst_offset]) =
*reinterpret_cast<dst_vector_t*>(&p_long_vector[buffer_offset]);
*reinterpret_cast<dst_vector_t*>(&p_dst_long_vector[buffer_offset]);
}
});
#endif
}
private:
......@@ -453,7 +170,7 @@ template <typename SrcDesc,
index_t DstVectorAccessDim,
index_t SrcDataPerAccess,
index_t DstDataPerAccess>
struct ThreadwiseGenericTensorSliceCopy_v2r1
struct ThreadwiseGenericTensorSliceCopy_v2r1_deprecated
{
static constexpr index_t nDim = SliceLengths::GetSize();
......@@ -462,8 +179,8 @@ struct ThreadwiseGenericTensorSliceCopy_v2r1
using SrcCoordinate = typename TensorCoordinate_deprecated<SrcDesc>::type;
using DstCoordinate = typename TensorCoordinate_deprecated<DstDesc>::type;
__device__ constexpr ThreadwiseGenericTensorSliceCopy_v2r1(const Index& src_slice_origin,
const Index& dst_slice_origin)
__device__ constexpr ThreadwiseGenericTensorSliceCopy_v2r1_deprecated(
const Index& src_slice_origin, const Index& dst_slice_origin)
: mSrcSliceOrigin(src_slice_origin), mDstSliceOrigin(dst_slice_origin)
{
static_assert(nDim == SrcDesc::GetNumOfDimension() &&
......@@ -511,8 +228,8 @@ struct ThreadwiseGenericTensorSliceCopy_v2r1
});
}
__device__ constexpr ThreadwiseGenericTensorSliceCopy_v2r1()
: ThreadwiseGenericTensorSliceCopy_v2r1(make_zero_array<index_t, nDim>(),
__device__ constexpr ThreadwiseGenericTensorSliceCopy_v2r1_deprecated()
: ThreadwiseGenericTensorSliceCopy_v2r1_deprecated(make_zero_array<index_t, nDim>(),
make_zero_array<index_t, nDim>())
{
}
......@@ -539,9 +256,12 @@ struct ThreadwiseGenericTensorSliceCopy_v2r1
template <typename SrcData,
typename DstData,
address_space_t SrcAddressSpace = address_space_t::generic,
address_space_t DstAddressSpace = address_space_t::generic>
__device__ void Run(const SrcData* p_src, DstData* p_dst) const
AddressSpace SrcAddressSpace,
AddressSpace DstAddressSpace>
__device__ void Run(const SrcData* p_src,
DstData* p_dst,
integral_constant<AddressSpace, SrcAddressSpace>,
integral_constant<AddressSpace, DstAddressSpace>) const
{
constexpr auto buffer_desc = make_ConstantTensorDescriptor_packed(SliceLengths{});
......@@ -613,10 +333,10 @@ struct ThreadwiseGenericTensorSliceCopy_v2r1
// 2. src_normal_offset must be calculatd at compile time (guaranteed by
// algorithm)
// 3. src_merged_offset can be runtime value (no assumption imposed)
static_if<SrcAddressSpace == address_space_t::global>{}([&](auto) {
#if CK_USE_AMD_INTRINSIC && CK_USE_AMD_INTRINSIC_BUFFER_LOAD_STORE
static_if<SrcAddressSpace == AddressSpace::global>{}([&](auto fwd) {
#if CK_USE_AMD_BUFFER_ADDRESSING
vector_data = __buffer_load<SrcData, SrcDataPerAccess>(
p_src, src_merged_offset, src_normal_offset);
fwd(p_src), src_merged_offset, src_normal_offset);
#else
vector_data = *reinterpret_cast<const src_vector_t*>(
&p_src[src_normal_offset + src_merged_offset]);
......@@ -722,10 +442,10 @@ struct ThreadwiseGenericTensorSliceCopy_v2r1
// 2. dst_normal_offset must be calculatd at compile time (guaranteed by
// algorithm)
// 3. dst_merged_offset can be runtime value (no assumption imposed)
static_if<DstAddressSpace == address_space_t::global>{}([&](auto) {
#if CK_USE_AMD_INTRINSIC && CK_USE_AMD_INTRINSIC_BUFFER_LOAD_STORE
static_if<DstAddressSpace == AddressSpace::global>{}([&](auto fwd) {
#if CK_USE_AMD_BUFFER_ADDRESSING
__buffer_store<SrcData, DstDataPerAccess>(
vector_data, p_dst, dst_merged_offset, dst_normal_offset);
vector_data, fwd(p_dst), dst_merged_offset, dst_normal_offset);
#else
*reinterpret_cast<dst_vector_t*>(
&p_dst[dst_normal_offset + dst_merged_offset]) = vector_data;
......@@ -740,6 +460,15 @@ struct ThreadwiseGenericTensorSliceCopy_v2r1
}
}
template <typename SrcData, typename DstData>
__device__ void Run(const SrcData* p_src, DstData* p_dst) const
{
constexpr auto generic_address_space =
integral_constant<AddressSpace, AddressSpace::generic>{};
Run(p_src, p_dst, generic_address_space, generic_address_space);
}
// T can be Sequence or Array
template <typename T, bool PositiveDirection>
__device__ void MoveSrcSliceWindow(T step_sizes, integral_constant<bool, PositiveDirection>)
......
composable_kernel/include/utility/amd_buffer_addressing.hpp 0 → 100644
View file @ 52c3fe05
#ifndef CK_AMD_BUFFER_ADDRESSING_HPP
#define CK_AMD_BUFFER_ADDRESSING_HPP
#include "float_type.hpp"
namespace ck {
// For 128bit SGPRs in buffer_load and buffer_store instructions
// https://rocm-documentation.readthedocs.io/en/latest/GCN_ISA_Manuals/testdocbook.html#vector-memory-buffer-instructions
template <typename T>
union BufferLoadStoreDwordConfig
{
int32x4_t data;
T* address[2];
int32_t range[4];
};
__device__ float __llvm_amdgcn_buffer_load(int32x4_t rsrc,
index_t vindex,
index_t offset,
bool glc,
bool slc) __asm("llvm.amdgcn.buffer.load");
__device__ float2_t __llvm_amdgcn_buffer_loadx2(int32x4_t rsrc,
index_t vindex,
index_t offset,
bool glc,
bool slc) __asm("llvm.amdgcn.buffer.load.dwordx2");
__device__ float4_t __llvm_amdgcn_buffer_loadx4(int32x4_t rsrc,
index_t vindex,
index_t offset,
bool glc,
bool slc) __asm("llvm.amdgcn.buffer.load.dwordx4");
__device__ void __llvm_amdgcn_buffer_store(float vdata,
int32x4_t rsrc,
index_t vindex,
index_t offset,
bool glc,
bool slc) __asm("llvm.amdgcn.buffer.store");
__device__ void __llvm_amdgcn_buffer_storex2(float2_t vdata,
int32x4_t rsrc,
index_t vindex,
index_t offset,
bool glc,
bool slc) __asm("llvm.amdgcn.buffer.store.dwordx2");
__device__ void __llvm_amdgcn_buffer_storex4(float4_t vdata,
int32x4_t rsrc,
index_t vindex,
index_t offset,
bool glc,
bool slc) __asm("llvm.amdgcn.buffer.store.dwordx4");
template <typename T, index_t VectorSize>
__device__ typename vector_type<T, VectorSize>::MemoryType
__buffer_load(const T* p_src_block, index_t src_thread_data_offset, index_t src_const_data_offset);
template <typename T, index_t VectorSize>
__device__ void __buffer_store(const typename vector_type<T, VectorSize>::MemoryType& src,
T* p_dst_block,
index_t dst_thread_data_offset,
index_t dst_const_data_offset);
template <>
__device__ float __buffer_load<float, 1>(const float* p_src_block,
index_t src_thread_data_offset,
index_t src_const_data_offset)
{
float dst;
index_t src_thread_addr_offset = src_thread_data_offset * sizeof(float);
index_t src_const_addr_offset = src_const_data_offset * sizeof(float);
BufferLoadStoreDwordConfig<float> src_block_config;
// fill in byte 0 - 1
src_block_config.address[0] = const_cast<float*>(p_src_block);
// fill in byte 2
src_block_config.range[2] = -1;
// fill in byte 3
src_block_config.range[3] = 0x00027000;
#if CK_USE_AMD_BUFFER_ADDRESSING_INTRINSIC
dst = __llvm_amdgcn_buffer_load(
src_block_config.data, 0, src_thread_addr_offset + src_const_addr_offset, false, false);
#else
asm volatile(
"\n \
buffer_load_dword %0, %1, %2, %3 offen offset:0 \n \
s_waitcnt 0 \n \
"
: "=v"(dst)
: "v"(src_thread_addr_offset), "s"(src_block_config.data), "s"(src_const_addr_offset));
#endif
return dst;
}
template <>
__device__ float2_t __buffer_load<float, 2>(const float* p_src_block,
index_t src_thread_data_offset,
index_t src_const_data_offset)
{
float2_t dst;
index_t src_thread_addr_offset = src_thread_data_offset * sizeof(float);
index_t src_const_addr_offset = src_const_data_offset * sizeof(float);
BufferLoadStoreDwordConfig<float> src_block_config;
// fill in byte 0 - 1
src_block_config.address[0] = const_cast<float*>(p_src_block);
// fill in byte 2
src_block_config.range[2] = -1;
// fill in byte 3
src_block_config.range[3] = 0x00027000;
#if CK_USE_AMD_BUFFER_ADDRESSING_INTRINSIC
dst = __llvm_amdgcn_buffer_loadx2(
src_block_config.data, 0, src_thread_addr_offset + src_const_addr_offset, false, false);
#else
asm volatile(
"\n \
buffer_load_dwordx2 %0, %1, %2, %3 offen offset:0 \n \
s_waitcnt 0 \n \
"
: "=v"(dst)
: "v"(src_thread_addr_offset), "s"(src_block_config.data), "s"(src_const_addr_offset));
#endif
return dst;
}
template <>
__device__ float4_t __buffer_load<float, 4>(const float* p_src_block,
index_t src_thread_data_offset,
index_t src_const_data_offset)
{
float4_t dst;
index_t src_thread_addr_offset = src_thread_data_offset * sizeof(float);
index_t src_const_addr_offset = src_const_data_offset * sizeof(float);
BufferLoadStoreDwordConfig<float> src_block_config;
// fill in byte 0 - 1
src_block_config.address[0] = const_cast<float*>(p_src_block);
// fill in byte 2
src_block_config.range[2] = -1;
// fill in byte 3
src_block_config.range[3] = 0x00027000;
#if CK_USE_AMD_BUFFER_ADDRESSING_INTRINSIC
dst = __llvm_amdgcn_buffer_loadx4(
src_block_config.data, 0, src_thread_addr_offset + src_const_addr_offset, false, false);
#else
asm volatile(
"\n \
buffer_load_dwordx4 %0, %1, %2, %3 offen offset:0 \n \
s_waitcnt 0 \n \
"
: "=v"(dst)
: "v"(src_thread_addr_offset), "s"(src_block_config.data), "s"(src_const_addr_offset));
#endif
return dst;
}
template <>
__device__ void __buffer_store<float, 1>(const float& src,
float* p_dst_block,
index_t dst_thread_data_offset,
index_t dst_const_data_offset)
{
index_t dst_thread_addr_offset = dst_thread_data_offset * sizeof(float);
index_t dst_const_addr_offset = dst_const_data_offset * sizeof(float);
BufferLoadStoreDwordConfig<float> dst_block_config;
// fill in byte 0 - 1
dst_block_config.address[0] = p_dst_block;
// fill in byte 2
dst_block_config.range[2] = -1;
// fill in byte 3
dst_block_config.range[3] = 0x00027000;
#if CK_USE_AMD_BUFFER_ADDRESSING_INTRINSIC
__llvm_amdgcn_buffer_store(src,
dst_block_config.data,
0,
dst_thread_addr_offset + dst_const_addr_offset,
false,
false);
#else
asm volatile("\n \
buffer_store_dword %1, %2, %0, %3 offen offset:0 \n \
"
:
: "s"(dst_block_config.data),
"v"(src),
"v"(dst_thread_addr_offset),
"s"(dst_const_addr_offset));
#endif
}
template <>
__device__ void __buffer_store<float, 2>(const float2_t& src,
float* p_dst_block,
index_t dst_thread_data_offset,
index_t dst_const_data_offset)
{
index_t dst_thread_addr_offset = dst_thread_data_offset * sizeof(float);
index_t dst_const_addr_offset = dst_const_data_offset * sizeof(float);
BufferLoadStoreDwordConfig<float> dst_block_config;
// fill in byte 0 - 1
dst_block_config.address[0] = p_dst_block;
// fill in byte 2
dst_block_config.range[2] = -1;
// fill in byte 3
dst_block_config.range[3] = 0x00027000;
#if CK_USE_AMD_BUFFER_ADDRESSING_INTRINSIC
__llvm_amdgcn_buffer_storex2(src,
dst_block_config.data,
0,
dst_thread_addr_offset + dst_const_addr_offset,
false,
false);
#else
asm volatile("\n \
buffer_store_dwordx2 %1, %2, %0, %3 offen offset:0 \n \
"
:
: "s"(dst_block_config.data),
"v"(src),
"v"(dst_thread_addr_offset),
"s"(dst_const_addr_offset));
#endif
}
template <>
__device__ void __buffer_store<float, 4>(const float4_t& src,
float* p_dst_block,
index_t dst_thread_data_offset,
index_t dst_const_data_offset)
{
index_t dst_thread_addr_offset = dst_thread_data_offset * sizeof(float);
index_t dst_const_addr_offset = dst_const_data_offset * sizeof(float);
BufferLoadStoreDwordConfig<float> dst_block_config;
// fill in byte 0 - 1
dst_block_config.address[0] = p_dst_block;
// fill in byte 2
dst_block_config.range[2] = -1;
// fill in byte 3
dst_block_config.range[3] = 0x00027000;
#if CK_USE_AMD_BUFFER_ADDRESSING_INTRINSIC
__llvm_amdgcn_buffer_storex4(src,
dst_block_config.data,
0,
dst_thread_addr_offset + dst_const_addr_offset,
false,
false);
#else
asm volatile("\n \
buffer_store_dwordx4 %1, %2, %0, %3 offen offset:0 \n \
"
:
: "s"(dst_block_config.data),
"v"(src),
"v"(dst_thread_addr_offset),
"s"(dst_const_addr_offset));
#endif
}
} // namespace ck
#endif
composable_kernel/include/utility/amd_inline_asm.hpp
View file @ 52c3fe05
#ifndef CK_AMD_INLINE_ASM_HPP
#define CK_AMD_INLINE_ASM_HPP
#include "vector_type.hpp"
#include "float_type.hpp"
namespace ck {
// cast a pointer of LDS to its address
extern "C" __attribute__((address_space(3))) __device__ void* __to_local(void* p);
__device__ void vmcnt(index_t cnt)
{
if(cnt == 0)
{
asm volatile("\n \
s_waitcnt vmcnt(0) \n \
" ::);
}
else if(cnt == 1)
{
asm volatile("\n \
s_waitcnt vmcnt(1) \n \
" ::);
}
else if(cnt == 2)
{
asm volatile("\n \
s_waitcnt vmcnt(2) \n \
" ::);
}
else if(cnt == 4)
{
asm volatile("\n \
s_waitcnt vmcnt(2) \n \
" ::);
}
else
{
assert(false);
}
}
__device__ void lgkmcnt(index_t cnt)
// outer-product: c[i,j] += inner_product(a[i], b[j])
__device__ void __outer_product_1x2(float a, float b0, float b1, float& c0, float& c1)
{
if(cnt == 0)
{
asm volatile("\n \
s_waitcnt lgkmcnt(0) \n \
" ::);
}
else if(cnt == 1)
{
asm volatile("\n \
s_waitcnt lgkmcnt(1) \n \
" ::);
}
else if(cnt == 2)
{
asm volatile("\n \
s_waitcnt lgkmcnt(2) \n \
" ::);
}
else if(cnt == 3)
{
asm volatile("\n \
s_waitcnt lgkmcnt(3) \n \
" ::);
}
else if(cnt == 4)
{
asm volatile("\n \
s_waitcnt lgkmcnt(4) \n \
" ::);
}
else
{
assert(false);
}
// disable inline asm due to the compiler issue: SWDEV-202749
///\to-do: enable the inline asm after the compiler fix
#if CK_WORKAROUND_SWDEV_202749
c0 += a * b0;
c1 += a * b1;
#else
asm volatile("\n \
v_mac_f32 %0, %2, %3 \n \
v_mac_f32 %1, %2, %4 \n \
"
: "=v"(c0), "=v"(c1)
: "v"(a), "v"(b0), "v"(b1), "0"(c0), "1"(c1));
#endif
}
__device__ void outerProduct1x4(const float* a, const float* b, float* c)
// outer-product: c[i,j] += inner_product(a[i], b[j])
__device__ void __outer_product_1x4(
float a, float b0, float b1, float b2, float b3, float& c0, float& c1, float& c2, float& c3)
{
asm volatile("\n \
v_mac_f32 %0, %4, %5 \n \
......@@ -86,596 +33,122 @@ __device__ void outerProduct1x4(const float* a, const float* b, float* c)
v_mac_f32 %2, %4, %7 \n \
v_mac_f32 %3, %4, %8 \n \
"
: "=v"(c[0]), "=v"(c[1]), "=v"(c[2]), "=v"(c[3])
: "v"(a[0]),
"v"(b[0]),
"v"(b[1]),
"v"(b[2]),
"v"(b[3]),
"0"(c[0]),
"1"(c[1]),
"2"(c[2]),
"3"(c[3]));
: "=v"(c0), "=v"(c1), "=v"(c2), "=v"(c3)
: "v"(a), "v"(b0), "v"(b1), "v"(b2), "v"(b3), "0"(c0), "1"(c1), "2"(c2), "3"(c3));
}
__device__ void outerProduct1x4(const float& a,
const vector_type<float, 4>::MemoryType& b,
vector_type<float, 4>::MemoryType& c)
// outer-product: c[i,j] += inner_product(a[i], b[j])
__device__ void __outer_product_1x2(half2_t a, half2_t b0, half2_t b1, float& c0, float& c1)
{
outerProduct1x4(&a, reinterpret_cast<const float*>(&b), reinterpret_cast<float*>(&c));
asm volatile("\n \
v_dot2_f32_f16 %0, %2, %3 %0\n \
v_dot2_f32_f16 %1, %2, %4 %1\n \
"
: "=v"(c0), "=v"(c1) // Dest registers
: "v"(a), // 1st Src register for 1 half2 registers
"v"(b0), // 2nd Src register
"v"(b1),
"0"(c0), // 3rd Src register
"1"(c1));
}
__device__ void outerProduct2x4(const vector_type<float, 2>::MemoryType& a,
const vector_type<float, 4>::MemoryType& b,
vector_type<float, 4>::MemoryType& c0,
vector_type<float, 4>::MemoryType& c1)
// outer-product: c[i,j] += inner_product(a[i], b[j])
__device__ void __outer_product_1x2(half4_t a, half4_t b0, half4_t b1, float& c0, float& c1)
{
outerProduct1x4(a.x, b, c0);
outerProduct1x4(a.y, b, c1);
}
const half2_t* p_a_half2 = reinterpret_cast<const half2_t*>(&a);
const half2_t* p_b0_half2 = reinterpret_cast<const half2_t*>(&b0);
const half2_t* p_b1_half2 = reinterpret_cast<const half2_t*>(&b1);
__device__ void outerProduct4x4(const vector_type<float, 4>::MemoryType& a,
const vector_type<float, 4>::MemoryType& b,
vector_type<float, 4>::MemoryType& c0,
vector_type<float, 4>::MemoryType& c1,
vector_type<float, 4>::MemoryType& c2,
vector_type<float, 4>::MemoryType& c3)
{
outerProduct1x4(a.x, b, c0);
outerProduct1x4(a.y, b, c1);
outerProduct1x4(a.z, b, c2);
outerProduct1x4(a.w, b, c3);
// do dot2 two times
asm volatile("\n \
v_dot2_f32_f16 %0, %2, %4 %0\n \
v_dot2_f32_f16 %1, %2, %6 %1\n \
v_dot2_f32_f16 %0, %3, %5 %0\n \
v_dot2_f32_f16 %1, %3, %7 %1\n \
"
: "=v"(c0), "=v"(c1) // Dest registers
: "v"(p_a_half2[0]),
"v"(p_a_half2[1]), // 1st Src registers for 2 half2 registers
"v"(p_b0_half2[0]),
"v"(p_b0_half2[1]),
"v"(p_b1_half2[0]),
"v"(p_b1_half2[1]), // 2nd Src registers for 2 half2 registers
"0"(c0),
"1"(c1)); // 3rd Src Acc registers for 2 half2 registers
}
__device__ void outerProduct8x8(const vector_type<float, 4>::MemoryType* a,
const vector_type<float, 4>::MemoryType* b,
vector_type<float, 4>::MemoryType* c)
// outer-product: c[i,j] += inner_product(a[i], b[j])
__device__ void __outer_product_1x4(half2_t a,
half2_t b0,
half2_t b1,
half2_t b2,
half2_t b3,
float& c0,
float& c1,
float& c2,
float& c3)
{
outerProduct4x4(a[0], b[0], c[0], c[2], c[4], c[6]);
outerProduct4x4(a[0], b[1], c[1], c[3], c[5], c[7]);
outerProduct4x4(a[1], b[0], c[8], c[10], c[12], c[14]);
outerProduct4x4(a[1], b[1], c[9], c[11], c[13], c[15]);
}
__device__ void ds_read_b128(vector_type<float, 4>::MemoryType& r, void* lds, index_t offset = 0)
{
if(offset == 0)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:0\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 64)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:64\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 128)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:128\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 192)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:192\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 256)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:256\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 320)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:320\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 384)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:384\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 448)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:448\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 512)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:512\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 576)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:576\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 640)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:640\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 704)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:704\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 768)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:768\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 832)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:832\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 896)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:896\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 960)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:960\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 1024)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:1024\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 1088)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:1088\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 1152)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:1152\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 1216)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:1216\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 1280)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:1280\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 1344)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:1344\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 1408)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:1408\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 1472)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:1472\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 1536)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:1536\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 1600)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:1600\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 1664)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:1664\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 1728)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:1728\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 1792)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:1792\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 1856)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:1856\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 1920)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:1920\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 1984)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:1984\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 2048)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:2048\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 2112)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:2112\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 2176)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:2176\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 2240)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:2240\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 2304)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:2304\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 2368)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:2368\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 2432)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:2432\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 2496)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:2496\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 2560)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:2560\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 2624)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:2624\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 2688)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:2688\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 2752)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:2752\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 2816)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:2816\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 2880)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:2880\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 2944)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:2944\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 3008)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:3008\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 3072)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:3072\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 3136)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:3136\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 3200)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:3200\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 3264)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:3264\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 3328)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:3328\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 3392)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:3392\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 3456)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:3456\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 3520)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:3520\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 3584)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:3584\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 3648)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:3648\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 3712)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:3712\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 3776)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:3776\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 3840)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:3840\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 3904)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:3904\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 3968)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:3968\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 4032)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:4032\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
if(offset == 4096)
{
asm volatile("\n \
ds_read_b128 %0, %1 offset:4096\n \
"
: "=v"(r)
: "v"(__to_local(lds)));
}
v_dot2_f32_f16 %0, %4, %5 %0\n \
v_dot2_f32_f16 %1, %4, %6 %1\n \
v_dot2_f32_f16 %2, %4, %7 %2\n \
v_dot2_f32_f16 %3, %4, %8 %3\n \
"
: "=v"(c0), "=v"(c1), "=v"(c2), "=v"(c3) // Dest registers
: "v"(a), // 1st Src register for 1 half2 registers
"v"(b0), // 2nd Src register
"v"(b1),
"v"(b2),
"v"(b3),
"0"(c0), // 3rd Src register
"1"(c1),
"2"(c2),
"3"(c3));
}
__device__ void
ds_write_b128(const vector_type<float, 4>::MemoryType& r, void* lds, index_t offset = 0)
// outer-product: c[i,j] += inner_product(a[i], b[j])
__device__ void __outer_product_1x4(half4_t a,
half4_t b0,
half4_t b1,
half4_t b2,
half4_t b3,
float& c0,
float& c1,
float& c2,
float& c3)
{
if(offset == 0)
{
asm volatile("\n \
ds_write_b128 %0, %1 \n \
"
:
: "v"(__to_local(lds)), "v"(r));
}
else
{
assert(false);
}
const half2_t* p_a_half2 = reinterpret_cast<const half2_t*>(&a);
const half2_t* p_b0_half2 = reinterpret_cast<const half2_t*>(&b0);
const half2_t* p_b1_half2 = reinterpret_cast<const half2_t*>(&b1);
const half2_t* p_b2_half2 = reinterpret_cast<const half2_t*>(&b2);
const half2_t* p_b3_half2 = reinterpret_cast<const half2_t*>(&b3);
// do dot2 two times
asm volatile("\n \
v_dot2_f32_f16 %0, %4, %6 %0\n \
v_dot2_f32_f16 %1, %4, %8 %1\n \
v_dot2_f32_f16 %2, %4, %10 %2\n \
v_dot2_f32_f16 %3, %4, %12 %3\n \
v_dot2_f32_f16 %0, %5, %7 %0\n \
v_dot2_f32_f16 %1, %5, %9 %1\n \
v_dot2_f32_f16 %2, %5, %11 %2\n \
v_dot2_f32_f16 %3, %5, %13 %3\n \
"
: "=v"(c0), "=v"(c1), "=v"(c2), "=v"(c3) // Dest registers
: "v"(p_a_half2[0]),
"v"(p_a_half2[1]), // 1st Src registers for 2 half2 registers
"v"(p_b0_half2[0]),
"v"(p_b0_half2[1]),
"v"(p_b1_half2[0]),
"v"(p_b1_half2[1]), // 2nd Src registers for 2 half2 registers
"v"(p_b2_half2[0]),
"v"(p_b2_half2[1]),
"v"(p_b3_half2[0]),
"v"(p_b3_half2[1]), // 2nd Src registers for 2 half2 registers
"0"(c0),
"1"(c1),
"2"(c2),
"3"(c3)); // 3rd Src Acc registers for 2 half2 registers
}
} // namespace ck
......
composable_kernel/include/utility/amd_intrinsic.hpp deleted 100644 → 0
View file @ 9aaeacc8
#ifndef CK_AMD_INTRINSIC_HPP
#define CK_AMD_INTRINSIC_HPP
#include "vector_type.hpp"
namespace ck {
__device__ float __llvm_amdgcn_buffer_load(int32x4_t rsrc,
uint32_t vindex,
uint32_t offset,
bool glc,
bool slc) __asm("llvm.amdgcn.buffer.load");
__device__ vector_type<float, 2>::MemoryType
__llvm_amdgcn_buffer_loadx2(int32x4_t rsrc,
uint32_t vindex,
uint32_t offset,
bool glc,
bool slc) __asm("llvm.amdgcn.buffer.load.dwordx2");
__device__ vector_type<float, 4>::MemoryType
__llvm_amdgcn_buffer_loadx4(int32x4_t rsrc,
uint32_t vindex,
uint32_t offset,
bool glc,
bool slc) __asm("llvm.amdgcn.buffer.load.dwordx4");
__device__ void __llvm_amdgcn_buffer_store(float vdata,
int32x4_t rsrc,
uint32_t vindex,
uint32_t offset,
bool glc,
bool slc) __asm("llvm.amdgcn.buffer.store");
__device__ void __llvm_amdgcn_buffer_storex2(vector_type<float, 2>::MemoryType vdata,
int32x4_t rsrc,
uint32_t vindex,
uint32_t offset,
bool glc,
bool slc) __asm("llvm.amdgcn.buffer.store.dwordx2");
__device__ void __llvm_amdgcn_buffer_storex4(vector_type<float, 4>::MemoryType vdata,
int32x4_t rsrc,
uint32_t vindex,
uint32_t offset,
bool glc,
bool slc) __asm("llvm.amdgcn.buffer.store.dwordx4");
// buffer_load and buffer_store
template <typename T, index_t VectorSize>
__device__ typename vector_type<T, VectorSize>::MemoryType __buffer_load(
const T* p_src_block, uint32_t src_thread_data_offset, uint32_t src_const_data_offset);
template <typename T, index_t VectorSize>
__device__ void __buffer_store(const typename vector_type<T, VectorSize>::MemoryType& src,
T* p_dst_block,
uint32_t dst_thread_data_offset,
uint32_t dst_const_data_offset);
template <>
__device__ float __buffer_load<float, 1>(const float* p_src_block,
uint32_t src_thread_data_offset,
uint32_t src_const_data_offset)
{
#if 0
float dst;
uint32_t src_thread_addr_offset = src_thread_data_offset * sizeof(float);
uint32_t src_const_addr_offset = src_const_data_offset * sizeof(float);
int32x4_t src_block_setting{0};
// fill in byte 0 - 1
*reinterpret_cast<float**>(&src_block_setting) = const_cast<float*>(p_src_block);
// fill in byte 2
reinterpret_cast<int*>(&src_block_setting)[2] = -1;
// fill in byte 3
reinterpret_cast<int*>(&src_block_setting)[3] = 0x00027000;
asm volatile("\n \
buffer_load_dword %0, %1, %2, %3 offen offset:0 \n \
s_waitcnt 0 \n \
"
: "=v"(dst)
: "v"(src_thread_addr_offset), "s"(src_block_setting), "s"(src_const_addr_offset));
return dst;
#else
float dst;
uint32_t src_thread_addr_offset = src_thread_data_offset * sizeof(float);
uint32_t src_const_addr_offset = src_const_data_offset * sizeof(float);
int32x4_t src_block_setting{0};
// fill in byte 0 - 1
*reinterpret_cast<float**>(&src_block_setting) = const_cast<float*>(p_src_block);
// fill in byte 2
reinterpret_cast<int*>(&src_block_setting)[2] = -1;
// fill in byte 3
reinterpret_cast<int*>(&src_block_setting)[3] = 0x00027000;
dst = __llvm_amdgcn_buffer_load(
src_block_setting, 0, src_thread_addr_offset + src_const_addr_offset, false, false);
return dst;
#endif
}
template <>
__device__ vector_type<float, 2>::MemoryType __buffer_load<float, 2>(
const float* p_src_block, uint32_t src_thread_data_offset, uint32_t src_const_data_offset)
{
#if 0
vector_type<float, 2>::MemoryType dst;
uint32_t src_thread_addr_offset = src_thread_data_offset * sizeof(float);
uint32_t src_const_addr_offset = src_const_data_offset * sizeof(float);
int32x4_t src_block_setting{0};
// fill in byte 0 - 1
*reinterpret_cast<float**>(&src_block_setting) = const_cast<float*>(p_src_block);
// fill in byte 2
reinterpret_cast<int*>(&src_block_setting)[2] = -1;
// fill in byte 3
reinterpret_cast<int*>(&src_block_setting)[3] = 0x00027000;
asm volatile("\n \
buffer_load_dwordx2 %0, %1, %2, %3 offen offset:0 \n \
s_waitcnt 0 \n \
"
: "=v"(dst)
: "v"(src_thread_addr_offset), "s"(src_block_setting), "s"(src_const_addr_offset));
return dst;
#else
vector_type<float, 2>::MemoryType dst;
uint32_t src_thread_addr_offset = src_thread_data_offset * sizeof(float);
uint32_t src_const_addr_offset = src_const_data_offset * sizeof(float);
int32x4_t src_block_setting{0};
// fill in byte 0 - 1
*reinterpret_cast<float**>(&src_block_setting) = const_cast<float*>(p_src_block);
// fill in byte 2
reinterpret_cast<int*>(&src_block_setting)[2] = -1;
// fill in byte 3
reinterpret_cast<int*>(&src_block_setting)[3] = 0x00027000;
dst = __llvm_amdgcn_buffer_loadx2(
src_block_setting, 0, src_thread_addr_offset + src_const_addr_offset, false, false);
return dst;
#endif
}
template <>
__device__ vector_type<float, 4>::MemoryType __buffer_load<float, 4>(
const float* p_src_block, uint32_t src_thread_data_offset, uint32_t src_const_data_offset)
{
#if 0
vector_type<float, 4>::MemoryType dst;
uint32_t src_thread_addr_offset = src_thread_data_offset * sizeof(float);
uint32_t src_const_addr_offset = src_const_data_offset * sizeof(float);
int32x4_t src_block_setting{0};
// fill in byte 0 - 1
*reinterpret_cast<float**>(&src_block_setting) = const_cast<float*>(p_src_block);
// fill in byte 2
reinterpret_cast<int*>(&src_block_setting)[2] = -1;
// fill in byte 3
reinterpret_cast<int*>(&src_block_setting)[3] = 0x00027000;
asm volatile("\n \
buffer_load_dwordx4 %0, %1, %2, %3 offen offset:0 \n \
s_waitcnt 0 \n \
"
: "=v"(dst)
: "v"(src_thread_addr_offset), "s"(src_block_setting), "s"(src_const_addr_offset));
return dst;
#elif 1
vector_type<float, 4>::MemoryType dst;
uint32_t src_thread_addr_offset = src_thread_data_offset * sizeof(float);
uint32_t src_const_addr_offset = src_const_data_offset * sizeof(float);
int32x4_t src_block_setting{0};
// fill in byte 0 - 1
*reinterpret_cast<float**>(&src_block_setting) = const_cast<float*>(p_src_block);
// fill in byte 2
reinterpret_cast<int*>(&src_block_setting)[2] = -1;
// fill in byte 3
reinterpret_cast<int*>(&src_block_setting)[3] = 0x00027000;
dst = __llvm_amdgcn_buffer_loadx4(
src_block_setting, 0, src_thread_addr_offset + src_const_addr_offset, false, false);
return dst;
#endif
}
template <>
__device__ void __buffer_store<float, 1>(const float& src,
float* p_dst_block,
uint32_t dst_thread_data_offset,
uint32_t dst_const_data_offset)
{
#if 0
uint32_t dst_thread_addr_offset = dst_thread_data_offset * sizeof(float);
uint32_t dst_const_addr_offset = dst_const_data_offset * sizeof(float);
int32x4_t dst_block_setting{0};
// fill in byte 0 - 1
*reinterpret_cast<float**>(&dst_block_setting) = p_dst_block;
// fill in byte 2
reinterpret_cast<int*>(&dst_block_setting)[2] = -1;
// fill in byte 3
reinterpret_cast<int*>(&dst_block_setting)[3] = 0x00027000;
asm volatile("\n \
buffer_store_dword %1, %2, %0, %3 offen offset:0 \n \
"
:
: "s"(dst_block_setting),
"v"(src),
"v"(dst_thread_addr_offset),
"s"(dst_const_addr_offset));
#else
uint32_t dst_thread_addr_offset = dst_thread_data_offset * sizeof(float);
uint32_t dst_const_addr_offset = dst_const_data_offset * sizeof(float);
int32x4_t dst_block_setting{0};
// fill in byte 0 - 1
*reinterpret_cast<float**>(&dst_block_setting) = p_dst_block;
// fill in byte 2
reinterpret_cast<int*>(&dst_block_setting)[2] = -1;
// fill in byte 3
reinterpret_cast<int*>(&dst_block_setting)[3] = 0x00027000;
__llvm_amdgcn_buffer_store(
src, dst_block_setting, 0, dst_thread_addr_offset + dst_const_addr_offset, false, false);
#endif
}
template <>
__device__ void __buffer_store<float, 2>(const vector_type<float, 2>::MemoryType& src,
float* p_dst_block,
uint32_t dst_thread_data_offset,
uint32_t dst_const_data_offset)
{
#if 0
uint32_t dst_thread_addr_offset = dst_thread_data_offset * sizeof(float);
uint32_t dst_const_addr_offset = dst_const_data_offset * sizeof(float);
int32x4_t dst_block_setting{0};
// fill in byte 0 - 1
*reinterpret_cast<float**>(&dst_block_setting) = p_dst_block;
// fill in byte 2
reinterpret_cast<int*>(&dst_block_setting)[2] = -1;
// fill in byte 3
reinterpret_cast<int*>(&dst_block_setting)[3] = 0x00027000;
asm volatile("\n \
buffer_store_dwordx2 %1, %2, %0, %3 offen offset:0 \n \
"
:
: "s"(dst_block_setting),
"v"(src),
"v"(dst_thread_addr_offset),
"s"(dst_const_addr_offset));
#else
uint32_t dst_thread_addr_offset = dst_thread_data_offset * sizeof(float);
uint32_t dst_const_addr_offset = dst_const_data_offset * sizeof(float);
int32x4_t dst_block_setting{0};
// fill in byte 0 - 1
*reinterpret_cast<float**>(&dst_block_setting) = p_dst_block;
// fill in byte 2
reinterpret_cast<int*>(&dst_block_setting)[2] = -1;
// fill in byte 3
reinterpret_cast<int*>(&dst_block_setting)[3] = 0x00027000;
__llvm_amdgcn_buffer_storex2(
src, dst_block_setting, 0, dst_thread_addr_offset + dst_const_addr_offset, false, false);
#endif
}
template <>
__device__ void __buffer_store<float, 4>(const vector_type<float, 4>::MemoryType& src,
float* p_dst_block,
uint32_t dst_thread_data_offset,
uint32_t dst_const_data_offset)
{
#if 0
uint32_t dst_thread_addr_offset = dst_thread_data_offset * sizeof(float);
uint32_t dst_const_addr_offset = dst_const_data_offset * sizeof(float);
int32x4_t dst_block_setting{0};
// fill in byte 0 - 1
*reinterpret_cast<float**>(&dst_block_setting) = p_dst_block;
// fill in byte 2
reinterpret_cast<int*>(&dst_block_setting)[2] = -1;
// fill in byte 3
reinterpret_cast<int*>(&dst_block_setting)[3] = 0x00027000;
asm volatile("\n \
buffer_store_dwordx4 %1, %2, %0, %3 offen offset:0 \n \
"
:
: "s"(dst_block_setting),
"v"(src),
"v"(dst_thread_addr_offset),
"s"(dst_const_addr_offset));
#else
uint32_t dst_thread_addr_offset = dst_thread_data_offset * sizeof(float);
uint32_t dst_const_addr_offset = dst_const_data_offset * sizeof(float);
int32x4_t dst_block_setting{0};
// fill in byte 0 - 1
*reinterpret_cast<float**>(&dst_block_setting) = p_dst_block;
// fill in byte 2
reinterpret_cast<int*>(&dst_block_setting)[2] = -1;
// fill in byte 3
reinterpret_cast<int*>(&dst_block_setting)[3] = 0x00027000;
__llvm_amdgcn_buffer_storex4(
src, dst_block_setting, 0, dst_thread_addr_offset + dst_const_addr_offset, false, false);
#endif
}
} // namespace ck
#endif
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