Files
composable_kernel/src/include/blockwise_tensor_slice_op.hip.hpp
Chao Liu 97ba755f2f refactor
2019-05-31 22:28:32 -05:00

297 lines
13 KiB
C++

#pragma once
#include "threadwise_tensor_slice_op.hip.hpp"
template <index_t BlockSize,
class Float,
class SrcDesc,
class DstDesc,
class SrcLengths,
class SrcSubLengths,
class SrcClusterLengths,
class MapDst2Src,
class MapThreadCluster2SrcCluster,
index_t SrcDataPerRead,
index_t DstDataPerWrite>
struct BlockwiseTensorSliceReorderCopy_v3
{
static constexpr index_t nDim = SrcLengths::GetSize();
index_t mThreadSrcOffset;
index_t mThreadDstOffset;
__device__
BlockwiseTensorSliceReorderCopy_v3(Array<index_t, nDim> src_block_data_multi_id_begin,
Array<index_t, nDim> dst_block_data_multi_id_begin)
{
constexpr auto src_desc = SrcDesc{};
constexpr auto dst_desc = DstDesc{};
constexpr auto src_lengths = SrcLengths{};
constexpr auto map_dst2src = MapDst2Src{};
constexpr auto src_sub_lengths = SrcSubLengths{};
constexpr auto dst_sub_lengths = src_sub_lengths.ReorderGivenNew2Old(map_dst2src);
constexpr auto map_thread_cluster_2_src_cluster = MapThreadCluster2SrcCluster{};
constexpr auto src_cluster_lengths = SrcClusterLengths{};
constexpr auto thread_cluster_lengths =
src_cluster_lengths.ReorderGivenNew2Old(map_thread_cluster_2_src_cluster);
constexpr auto thread_cluster_desc =
make_ConstantTensorDescriptor_packed(thread_cluster_lengths);
// sanity check: data type
static_assert(is_same<Float, float>::value, "wrong! only support float for now!\n");
// sanity check: nDim
static_assert(SrcDesc::GetNumOfDimension() == nDim &&
DstDesc::GetNumOfDimension() == nDim && SrcLengths::GetSize() == nDim &&
SrcSubLengths::GetSize() == nDim &&
SrcClusterLengths::GetSize() == nDim && MapDst2Src::GetSize() == nDim &&
MapThreadCluster2SrcCluster::GetSize() == nDim,
"wrong! nDim is not consistent\n");
// sanity check: BlockSize
constexpr index_t num_active_thread = thread_cluster_desc.GetElementSize();
static_assert(BlockSize >= num_active_thread,
"wrong! BlockSize is not big enough for ThreadPerDims!");
// sanity check: work division
static_for<0, nDim, 1>{}([&](auto IDim) {
constexpr auto I = decltype(IDim){};
constexpr index_t src_len = src_lengths.Get(I);
constexpr index_t src_sub_len = src_sub_lengths.Get(I);
constexpr index_t src_cluster_len = src_cluster_lengths.Get(I);
static_assert(src_len % (src_sub_len * src_cluster_len) == 0,
"wrong! cannot evenly divide Src tensor lengths");
});
// sanity check: src read
static_assert(SrcDataPerRead == 1 || SrcDataPerRead == 2 || SrcDataPerRead == 4,
"wrong! only support SrcDataPerRead == 1, 2 or 4!\n");
static_assert(SrcDataPerRead == 1 || src_desc.GetStride(Number<nDim - 1>{}) == 1,
"wrong! only support src.stride(nDim-1) == 1 if SrcDataPerRead > 1!\n");
static_assert(src_sub_lengths.Get(Number<nDim - 1>{}) % SrcDataPerRead == 0,
"wrong! src_sub_lengths[nDim-1] % SrcDataPerRead != 0\n");
static_assert(src_desc.GetStride(Number<nDim - 2>{}) % SrcDataPerRead == 0,
"wrong! should satisfy src_desc.stride(nDim-2) % SrcDataPerRead == 0, to "
"keep alignment");
// sanity check: dst write
static_assert(DstDataPerWrite == 1 || DstDataPerWrite == 2 || DstDataPerWrite == 4,
"wrong! only support DstDataPerWrite == 1, 2 or 4!\n");
static_assert(DstDataPerWrite == 1 || dst_desc.GetStride(Number<nDim - 1>{}) == 1,
"wrong! only support dst.stride(nDim-1) == 1 if DstDataPerWrite > 1!\n");
static_assert(dst_sub_lengths.Get(Number<nDim - 1>{}) % DstDataPerWrite == 0,
"wrong! dst_sub_lengths[nDim-1] % DstDataPerWrite != 0\n");
static_assert(dst_desc.GetStride(Number<nDim - 2>{}) % DstDataPerWrite == 0,
"wrong! should satisfy dst_desc.stride(nDim-2) % DstDataPerWrite == 0, to "
"keep alignment");
// start dividing work
if(BlockSize > num_active_thread)
{
if(get_thread_local_1d_id() >= num_active_thread)
{
return;
}
}
const auto thread_multi_id =
thread_cluster_desc.GetMultiIndexFrom1dIndex(get_thread_local_1d_id());
// compiler: thread_multi_id, src_data_multi_id, dst_data_multi_id, will use separate
// regsiters, or only one copy???
auto src_data_multi_id =
reorder_array_given_old2new(thread_multi_id, map_thread_cluster_2_src_cluster);
static_for<0, nDim, 1>{}([&](auto IDim) {
constexpr auto I = decltype(IDim){};
constexpr index_t i = I.Get();
// compiler: will it really compute index here, or be merged with
// GetOffsetFromMultiIndex and
// optimized away???
src_data_multi_id[i] *= src_sub_lengths.Get(I);
});
// compiler: will it really compute index here, or be merged with GetOffsetFromMultiIndex
// and
// optimized away???
const auto dst_data_multi_id = reorder_array_given_new2old(src_data_multi_id, map_dst2src);
mThreadSrcOffset =
src_desc.GetOffsetFromMultiIndex(src_data_multi_id + src_block_data_multi_id_begin);
mThreadDstOffset =
dst_desc.GetOffsetFromMultiIndex(dst_data_multi_id + dst_block_data_multi_id_begin);
#if 0
if(get_block_1d_id() == 0 && get_thread_local_1d_id() == 0)
{
print_ConstantTensorDescriptor(thread_cluster_desc, "thread_cluster_desc: ");
}
if(get_block_1d_id() == 0)
{
printf("id %5u %5u: "
"thread_multi_id: %u %u, "
"src_block_data_multi_id_begin: %u %u, "
"src_data_multi_id: %u %u, "
"mThreadSrcOffset %u, mThreadDstOffset %u \n",
get_block_1d_id(),
get_thread_local_1d_id(),
thread_multi_id[0],
thread_multi_id[1],
src_block_data_multi_id_begin[0],
src_block_data_multi_id_begin[1],
src_data_multi_id[0],
src_data_multi_id[1],
mThreadSrcOffset,
mThreadDstOffset);
}
#endif
}
__device__ static constexpr index_t GetRegisterClipboardSize()
{
constexpr auto thread_sub_tensor_lengths = SrcSubLengths{};
constexpr auto src_data_per_cluster_per_dims =
thread_sub_tensor_lengths * SrcClusterLengths{};
constexpr auto repeat_lengths =
transform_sequences(mod_conv::integer_divide_ceiler<index_t>{},
SrcLengths{},
src_data_per_cluster_per_dims);
constexpr auto thread_tensor_lengths = thread_sub_tensor_lengths * repeat_lengths;
constexpr auto thread_tensor_desc =
make_ConstantTensorDescriptor_packed(thread_tensor_lengths);
return thread_tensor_desc.GetElementSpace();
}
__device__ void RunLoadRegisterClipboard(const Float* __restrict__ p_src,
Float* __restrict__ p_clipboard) const
{
constexpr auto thread_sub_tensor_lengths = SrcSubLengths{};
constexpr auto src_data_per_cluster_per_dims =
thread_sub_tensor_lengths * SrcClusterLengths{};
constexpr auto repeat_lengths =
transform_sequences(mod_conv::integer_divide_ceiler<index_t>{},
SrcLengths{},
src_data_per_cluster_per_dims);
constexpr auto thread_tensor_lengths = thread_sub_tensor_lengths * repeat_lengths;
constexpr auto thread_tensor_desc =
make_ConstantTensorDescriptor_packed(thread_tensor_lengths);
static_ford<decltype(repeat_lengths)>{}([&](auto repeat_multi_id_) {
constexpr auto repeat_multi_id = decltype(repeat_multi_id_){};
constexpr auto src_data_multi_id = repeat_multi_id * src_data_per_cluster_per_dims;
constexpr auto clipboard_data_multi_id = repeat_multi_id * thread_sub_tensor_lengths;
constexpr index_t src_offset = SrcDesc{}.GetOffsetFromMultiIndex(src_data_multi_id);
constexpr index_t clipboard_offset =
thread_tensor_desc.GetOffsetFromMultiIndex(clipboard_data_multi_id);
threadwise_tensor_slice_copy(SrcDesc{},
p_src + src_offset + mThreadSrcOffset,
thread_tensor_desc,
p_clipboard + clipboard_offset,
thread_sub_tensor_lengths,
Number<SrcDataPerRead>{});
});
}
__device__ void RunStoreRegisterClipboard(const Float* __restrict__ p_clipboard,
Float* __restrict__ p_dst) const
{
constexpr auto thread_sub_tensor_lengths = SrcSubLengths{};
constexpr auto src_data_per_cluster_per_dims =
thread_sub_tensor_lengths * SrcClusterLengths{};
constexpr auto repeat_lengths =
transform_sequences(mod_conv::integer_divide_ceiler<index_t>{},
SrcLengths{},
src_data_per_cluster_per_dims);
constexpr auto thread_tensor_lengths = thread_sub_tensor_lengths * repeat_lengths;
constexpr auto thread_tensor_desc =
make_ConstantTensorDescriptor_packed(thread_tensor_lengths);
static_ford<decltype(repeat_lengths)>{}([&](auto repeat_multi_id_) {
constexpr auto repeat_multi_id = decltype(repeat_multi_id_){};
constexpr auto clipboard_data_multi_id = repeat_multi_id * thread_sub_tensor_lengths;
constexpr auto src_data_multi_id = repeat_multi_id * src_data_per_cluster_per_dims;
// reorder src_data_multi_id to get dst_data_multi_id
constexpr auto dst_data_multi_id = src_data_multi_id.ReorderGivenNew2Old(MapDst2Src{});
constexpr index_t clipboard_offset =
thread_tensor_desc.GetOffsetFromMultiIndex(clipboard_data_multi_id);
constexpr index_t dst_offset = DstDesc{}.GetOffsetFromMultiIndex(dst_data_multi_id);
// write in the order of dst
#if 1
threadwise_tensor_slice_copy_reorder_given_dst2src_v2(thread_tensor_desc,
p_clipboard + clipboard_offset,
DstDesc{},
p_dst + dst_offset +
mThreadDstOffset,
thread_sub_tensor_lengths,
MapDst2Src{});
#else
threadwise_tensor_slice_copy_reorder_given_dst2src_v3(thread_tensor_desc,
p_clipboard + clipboard_offset,
DstDesc{},
p_dst + dst_offset +
mThreadDstOffset,
thread_sub_tensor_lengths,
MapDst2Src{},
Number<DstDataPerWrite>{});
#endif
});
}
__device__ void Run(const Float* __restrict__ p_src, Float* __restrict__ p_dst) const
{
Float p_clipboard[GetRegisterClipboardSize()];
RunLoadRegisterClipboard(p_src, p_clipboard);
RunStoreRegisterClipboard(p_clipboard, p_dst);
}
// this function doesn't do santiy check on whether the slicing window is out of the boundary
// of the tensor being sliced
template <index_t IDim_, index_t StepSize, bool PositiveDirection>
__device__ void MoveSlicingWindowOnSourceTensor(
Number<IDim_>, Number<StepSize>, integral_constant<bool, PositiveDirection> direction)
{
constexpr auto IDim = Number<IDim_>{};
static_if<PositiveDirection>{}([&](auto fwd) {
mThreadSrcOffset += StepSize * fwd(SrcDesc{}).GetStride(IDim);
}).Else([&](auto fwd) { mThreadSrcOffset -= StepSize * fwd(SrcDesc{}).GetStride(IDim); });
}
};