ROCm/composable_kernel
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adding implicit gemm v3

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This commit is contained in:
Chao Liu
2019-05-22 19:39:56 -05:00
parent 2a48812edb
commit 8a4b59785b
26 changed files with 373 additions and 259 deletions
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47
src/include/ConstantTensorDescriptor.hip.hpp
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@@ -2,20 +2,20 @@
#include "common.hip.hpp"
template <class Lengths>
__host__ __device__ constexpr auto calculate_packed_tensor_strides(Lengths)
__host__ __device__ constexpr auto calculate_tensor_strides_default_rank_packed(Lengths)
{
return reverse_inclusive_scan_sequence(Lengths{}.PopFront(), std::multiplies<index_t>{})
.PushBack(Number<1>{});
}
template <class Lengths, index_t Align>
__host__ __device__ constexpr auto
calculate_rank_tensor_default_strides_with_alignment(Lengths, Number<Align>)
__host__ __device__ constexpr auto calculate_tensor_strides_default_rank_aligned(Lengths,
Number<Align>)
{
constexpr index_t L_back_align =
Align * mod_conv::integer_divide_ceiler<index_t>{}(Lengths{}.Back(), Align);
return calculate_packed_tensor_strides(
return calculate_tensor_strides_default_rank_packed(
Lengths{}.Modify(Number<Lengths{}.GetSize() - 1>{}, Number<L_back_align>{}));
}
@@ -66,6 +66,12 @@ struct ConstantTensorDescriptor
return MemoryRanks{}.Get(Number<I>{});
}
template <class T>
__host__ __device__ static constexpr bool ContainMultipleOriginalDimensions(T)
{
return false;
}
__host__ __device__ static constexpr index_t GetElementSize()
{
return accumulate_on_sequence(Lengths{}, std::multiplies<index_t>{}, Number<1>{});
@@ -146,7 +152,7 @@ struct ConstantTensorDescriptor
{
Array<index_t, nDim> multi_id;
constexpr auto dummy_strides = calculate_packed_tensor_strides(GetLengths());
constexpr auto dummy_strides = calculate_tensor_strides_default_rank_packed(GetLengths());
// calculate index in each of the dimensions in the order of their dimension (not rank)
static_for<0, nDim - 1, 1>{}([&](auto IDim) {
@@ -181,6 +187,12 @@ struct ConstantTensorDescriptor
return ConstantTensorDescriptor<extract_lengths, extract_strides, new_ranks>{};
}
template <index_t... IDims>
__host__ __device__ static constexpr auto Extract(Sequence<IDims...>)
{
return Extract(Number<IDims>{}...);
}
template <index_t IDim, index_t SliceLen>
__host__ __device__ static constexpr auto Slice(Number<IDim>, Number<SliceLen>)
{
@@ -271,9 +283,11 @@ struct ConstantTensorDescriptor
FirstUnfoldDim <= LastUnfoldDim,
"wrong! should have FirstUnfoldDim <= LastUnfoldDim!");
#if 0 // cannot compile: compiler complain about constexpr
// dimensions to be unfold need to be in descending order (w.r.t. strides), and need to be
// packed in memory, otherwise, unfolding is invalid
static_for<FirstUnfoldDim, LastUnfoldDim, 1>{}([&](auto IDim) {
static_for<FirstUnfoldDim, LastUnfoldDim, 1>{}([&](auto IDim_) {
constexpr auto IDim = decltype(IDim_){};
constexpr auto IDim_p1 = IDim + Number<1>{};
// check stride
@@ -285,11 +299,12 @@ struct ConstantTensorDescriptor
static_assert(GetStride(IDim_p1) * GetLength(IDim_p1) == GetStride(IDim),
"wrong! dimensions to be unfolded need to be packed");
// checkt ranks
// check ranks
static_assert(GetMemoryRank(IDim_p1) == GetMemoryRank(IDim) + 1,
"wrong! ranks of dimensions to be unfolded need to be in increasing and "
"continuous ranks");
});
#endif
// left and right
constexpr auto left = typename arithmetic_sequence_gen<0, FirstUnfoldDim, 1>::SeqType{};
@@ -308,9 +323,9 @@ struct ConstantTensorDescriptor
// decrease the ranks that are larger than the rank of LastUnfoldDim
constexpr auto tmp_ranks =
transform_sequences(GetMemoryRanks(),
f_unfold_impl<GetMemoryRank(Number<LastUnfoldDim>{}),
LastUnfoldDim - FirstUnfoldDim + 1>{});
transform_sequences(f_unfold_impl<GetMemoryRank(Number<LastUnfoldDim>{}),
LastUnfoldDim - FirstUnfoldDim + 1>{},
GetMemoryRanks());
// new lengths, strides and ranks
constexpr auto new_lengths = GetLengths()
@@ -354,26 +369,26 @@ struct ConstantTensorDescriptor
};
template <class Lengths>
__host__ __device__ constexpr auto make_packed_ConstantTensorDescriptor(Lengths)
__host__ __device__ constexpr auto make_ConstantTensorDescriptor_default_rank_packed(Lengths)
{
using Strides = decltype(calculate_packed_tensor_strides(Lengths{}));
using Strides = decltype(calculate_tensor_strides_default_rank_packed(Lengths{}));
using MemoryRanks = typename arithmetic_sequence_gen<0, Lengths::GetSize(), 1>::SeqType;
return ConstantTensorDescriptor<Lengths, Strides, MemoryRanks>{};
}
template <class Lengths, class Strides>
__host__ __device__ constexpr auto make_ranked_ConstantTensorDescriptor(Lengths, Strides)
__host__ __device__ constexpr auto make_ConstantTensorDescriptor_default_rank(Lengths, Strides)
{
using MemoryRanks = typename arithmetic_sequence_gen<0, Lengths::GetSize(), 1>::SeqType;
return ConstantTensorDescriptor<Lengths, Strides, MemoryRanks>{};
}
template <class Lengths, index_t Align>
__host__ __device__ constexpr auto
make_ranked_ConstantTensorDescriptor_with_alignment(Lengths, Number<Align>)
__host__ __device__ constexpr auto make_ConstantTensorDescriptor_default_rank_aligned(Lengths,
Number<Align>)
{
using Strides =
decltype(calculate_rank_tensor_default_strides_with_alignment(Lengths{}, Number<Align>{}));
decltype(calculate_tensor_strides_default_rank_aligned(Lengths{}, Number<Align>{}));
using MemoryRanks = typename arithmetic_sequence_gen<0, Lengths::GetSize(), 1>::SeqType;
return ConstantTensorDescriptor<Lengths, Strides, MemoryRanks>{};
}