Commit 029f2b0e authored by Jianfeng yan's avatar Jianfeng yan
Browse files

WIP: start refactoring threadwise_transfer_v1r3

parent 23f755c7
...@@ -7,8 +7,7 @@ ...@@ -7,8 +7,7 @@
#include "tensor_descriptor_helper.hpp" #include "tensor_descriptor_helper.hpp"
#include "blockwise_gemm_xdlops.hpp" #include "blockwise_gemm_xdlops.hpp"
#include "blockwise_tensor_slice_transfer_v4r1.hpp" #include "blockwise_tensor_slice_transfer_v4r1.hpp"
#include "threadwise_tensor_slice_transfer.hpp" #include "threadwise_tensor_slice_transfer_using_space_filling_curve.hpp"
#include "gridwise_gemm_pipeline_v1.hpp"
namespace ck { namespace ck {
...@@ -564,7 +563,7 @@ struct GridwiseGemm_k0mk1_k0nk1_mn_xdlops_v2r3 ...@@ -564,7 +563,7 @@ struct GridwiseGemm_k0mk1_k0nk1_mn_xdlops_v2r3
make_multi_index(n_thread_data_on_grid)); make_multi_index(n_thread_data_on_grid));
auto c_thread_copy = auto c_thread_copy =
ThreadwiseTensorSliceTransfer_v1r3<FloatAcc, ThreadwiseTensorSliceTransfer_v1r3_using_space_filling_curve<FloatAcc,
FloatC, FloatC,
decltype(c_thread_desc_m0_n0_m1_n1_m2_m3_m4_n2), decltype(c_thread_desc_m0_n0_m1_n1_m2_m3_m4_n2),
decltype(c_grid_desc_m0_n0_m1_n1_m2_m3_m4_n2), decltype(c_grid_desc_m0_n0_m1_n1_m2_m3_m4_n2),
......
...@@ -383,7 +383,7 @@ struct ThreadwiseTensorSliceTransfer_v1r3 ...@@ -383,7 +383,7 @@ struct ThreadwiseTensorSliceTransfer_v1r3
private: private:
DstCoord dst_coord_; DstCoord dst_coord_;
const DstElementwiseOperation dst_element_op_; const DstElementwiseOperation dst_element_op_;
}; // namespace ck }; // struct ThreadwiseTensorSliceTransfer_v1r3
// Assume: // Assume:
// 1. src: // 1. src:
......
#ifndef CK_THREADWISE_TENSOR_SLICE_TRANSFER_USING_SPACE_FILLING_CURVE_HPP
#define CK_THREADWISE_TENSOR_SLICE_TRANSFER_USING_SPACE_FILLING_CURVE_HPP
#include "common_header.hpp"
#include "tensor_descriptor.hpp"
#include "tensor_descriptor_helper.hpp"
#include "tensor_space_filling_curve.hpp"
namespace ck {
// Do following things to avoid "alloca" in LLVM-IR, which would cause scratch memory
// and sometimes useless instructions:
// 1. Don't save a reference to tensor descriptor in class, pass in tensor descriptor as argument
// instead
// 2. Don't construct a new tensor coordinate everytime when using it, update and reuse the same
// tensor coordinate instead
// 3. Don't use a pointer to VGPR buffer, use vector instead
// namespace detail {
// // TODO: How to fix this? It uses an struct instead of lambda because lambda
// // doesn't have constructor
// template <index_t VectorDim, index_t ScalarPerVector>
// struct lambda_scalar_per_access
// {
// __host__ __device__ constexpr auto operator()(index_t i) const
// {
// return (i == VectorDim) ? ScalarPerVector : 1;
// }
// };
//
// template <index_t VectorDim>
// struct lambda_scalar_step_in_vector
// {
// __host__ __device__ constexpr auto operator()(index_t i) const
// {
// return (i == VectorDim) ? 1 : 0;
// }
// };
// } // namespace detail
// Assume:
// 1. src:
// 1. SrcDesc is known at compile-time
// 2. SrcBuffer is StaticBuffer
// 3. SrcSliceOrginIdx is known at compile-time
// 2. dst:
// 1. DstDesc is not known at compile-time
// 2. DstBuffer is DynamicBuffer
// 3. DstSliceOrginIdx is not known at compile time
template <typename SrcData,
typename DstData,
typename SrcDesc,
typename DstDesc,
typename DstElementwiseOperation,
typename SliceLengths,
typename DimAccessOrder,
index_t DstVectorDim,
index_t DstScalarPerVector,
InMemoryDataOperationEnum_t DstInMemOp,
index_t DstScalarStrideInVector,
bool DstResetCoordinateAfterRun,
typename enable_if<SrcDesc::IsKnownAtCompileTime(), bool>::type = false>
struct ThreadwiseTensorSliceTransfer_v1r3_using_space_filling_curve
{
static constexpr index_t nDim = SliceLengths::Size();
using Index = MultiIndex<nDim>;
using DstCoord = decltype(make_tensor_coordinate(DstDesc{}, Index{}));
using DstCoordStep = decltype(make_tensor_coordinate_step(DstDesc{}, Index{}));
__device__ constexpr ThreadwiseTensorSliceTransfer_v1r3_using_space_filling_curve(
const DstDesc& dst_desc,
const Index& dst_slice_origin_idx,
const DstElementwiseOperation& dst_element_op)
: dst_coord_(make_tensor_coordinate(dst_desc, dst_slice_origin_idx)),
dst_element_op_{dst_element_op}
{
static_assert(SrcDesc::IsKnownAtCompileTime(),
"wrong! SrcDesc need to known at compile-time");
}
__device__ void SetDstSliceOrigin(const DstDesc& dst_desc, const Index& dst_slice_origin_idx)
{
dst_coord_ = make_tensor_coordinate(dst_desc, dst_slice_origin_idx);
}
template <typename SrcSliceOriginIdx,
typename SrcBuffer,
typename DstBuffer,
typename DstStepHacks>
__device__ void Run(const SrcDesc&,
const SrcSliceOriginIdx&,
const SrcBuffer& src_buf,
const DstDesc& dst_desc,
DstBuffer& dst_buf,
const DstStepHacks& dst_step_hacks)
{
static_assert(SrcDesc::IsKnownAtCompileTime(),
"wrong! SrcDesc need to known at compile-time");
static_assert(is_known_at_compile_time<remove_cvref_t<SrcSliceOriginIdx>>::value,
"wrong! SrcSliceOrigin need to known at compile-time");
static_assert(SrcBuffer::IsStaticBuffer(), "wrong! SrcBuffer need to be StaticBuffer");
// SrcDesc and src_slice_origin_idx are known at compile-time
constexpr auto src_desc = remove_cvref_t<SrcDesc>{};
constexpr auto src_slice_origin_idx = to_multi_index(SrcSliceOriginIdx{});
constexpr auto I0 = Number<0>{};
constexpr auto I1 = Number<1>{};
// scalar per access on each dim
// TODO: don't use lambda_scalar_per_access
constexpr auto dst_scalar_per_access = generate_sequence(
detail::lambda_scalar_per_access<DstVectorDim, DstScalarPerVector>{}, Number<nDim>{});
constexpr auto dst_scalar_step_in_vector =
generate_sequence(detail::lambda_scalar_step_in_vector<DstVectorDim>{}, Number<nDim>{});
constexpr auto access_lengths = SliceLengths{} / dst_scalar_per_access;
constexpr auto dim_access_order = DimAccessOrder{};
// make forward steps
const auto dst_forward_steps = generate_tuple(
[&](auto i) {
Index forward_step_idx;
static_for<0, nDim, 1>{}([&](auto j) {
forward_step_idx(j) = (i.value == j.value) ? dst_scalar_per_access[i] : 0;
});
return make_tensor_coordinate_step(
dst_desc, forward_step_idx, dst_step_hacks[I0][i]);
},
Number<nDim>{});
// make backward steps
const auto dst_backward_steps = generate_tuple(
[&](auto i) {
Index backward_step_idx;
static_for<0, nDim, 1>{}([&](auto j) {
backward_step_idx(j) = (i.value == j.value) ? -dst_scalar_per_access[i] : 0;
});
return make_tensor_coordinate_step(
dst_desc, backward_step_idx, dst_step_hacks[I1][i]);
},
Number<nDim>{});
using SpaceFillingCurve =
SpaceFillingCurve<SliceLengths, DimAccessOrder, remove_cv_t<decltype(dst_scalar_per_access)>>;
constexpr auto num_accesses = SpaceFillingCurve::GetNumOfAccess();
static_for<0, num_accesses, 1>{}([&](auto idx_1d) {
constexpr auto idx_md = SpaceFillingCurve::GetIndex(idx_1d);
static_assert(DstScalarPerVector == SpaceFillingCurve::ScalarPerVector);
typename vector_type_maker<DstData, DstScalarPerVector>::type dst_vector;
using dst_vector_t =
typename vector_type_maker<DstData, DstScalarPerVector>::type::type;
// copy data from src_buf into dst_vector
static_for<0, DstScalarPerVector, 1>{}([&](auto i) {
constexpr index_t src_offset = src_desc.CalculateOffset(
src_slice_origin_idx + idx_md + i * dst_scalar_step_in_vector);
SrcData dst_v;
// apply element-wise operation
dst_element_op_(dst_v, src_buf[Number<src_offset>{}]);
// apply type convert
dst_vector.template AsType<DstData>()(i) = type_convert<DstData>(dst_v);
});
const bool is_dst_valid =
coordinate_has_valid_offset_assuming_visible_index_is_valid(dst_desc, dst_coord_);
// copy data from dst_vector into dst_buf
if constexpr(DstInMemOp == InMemoryDataOperationEnum_t::Set)
{
dst_buf.template Set<dst_vector_t>(
dst_coord_.GetOffset(),
is_dst_valid,
dst_vector.template AsType<dst_vector_t>()[Number<0>{}]);
}
else if constexpr(DstInMemOp == InMemoryDataOperationEnum_t::AtomicAdd)
{
dst_buf.template AtomicAdd<dst_vector_t>(
dst_coord_.GetOffset(),
is_dst_valid,
dst_vector.template AsType<dst_vector_t>()[Number<0>{}]);
}
else if constexpr(DstInMemOp == InMemoryDataOperationEnum_t::Add)
{
typename vector_type_maker<DstData, DstScalarPerVector>::type tmp;
tmp.template AsType<dst_vector_t>()(Number<0>{}) =
dst_buf.template Get<dst_vector_t>(dst_coord_.GetOffset(), is_dst_valid);
static_for<0, DstScalarPerVector, 1>{}([&](auto t) {
dst_vector.template AsType<DstData>()(t) += tmp.template AsType<DstData>()[t];
});
dst_buf.template Set<dst_vector_t>(
dst_coord_.GetOffset(),
is_dst_valid,
dst_vector.template AsType<dst_vector_t>()[Number<0>{}]);
}
});
// move dst coordinate back to slice origin (or not)
if constexpr(DstResetCoordinateAfterRun)
{
const auto dst_reset_step =
make_tensor_coordinate_step(dst_desc, GetDstCoordinateResetStep());
move_tensor_coordinate(dst_desc, dst_coord_, dst_reset_step);
}
}
template <typename SrcSliceOriginIdx, typename SrcBuffer, typename DstBuffer>
__device__ void Run(const SrcDesc&,
const SrcSliceOriginIdx&,
const SrcBuffer& src_buf,
const DstDesc& dst_desc,
DstBuffer& dst_buf)
{
constexpr index_t ntransform_dst = remove_cvref_t<DstDesc>::GetNumOfTransform();
constexpr auto zeros = typename uniform_sequence_gen<ntransform_dst, 0>::type{};
constexpr auto dst_step_hacks =
make_tuple(generate_tuple([&](auto) { return zeros; }, Number<nDim>{}),
generate_tuple([&](auto) { return zeros; }, Number<nDim>{}));
Run(SrcDesc{}, SrcSliceOriginIdx{}, src_buf, dst_desc, dst_buf, dst_step_hacks);
}
__device__ static constexpr auto GetDstCoordinateResetStep()
{
constexpr auto I0 = Number<0>{};
// scalar per access on each dim
// TODO: don't use lambda_scalar_per_access
constexpr auto dst_scalar_per_access = generate_sequence(
detail::lambda_scalar_per_access<DstVectorDim, DstScalarPerVector>{}, Number<nDim>{});
constexpr auto access_lengths = SliceLengths{} / dst_scalar_per_access;
constexpr auto dim_access_order = DimAccessOrder{};
constexpr auto ordered_access_lengths =
container_reorder_given_new2old(access_lengths, dim_access_order);
// judge move forward or move backward during the last iteration
constexpr auto forward_sweep = [&]() {
StaticallyIndexedArray<bool, nDim> forward_sweep_;
forward_sweep_(I0) = true;
static_for<1, nDim, 1>{}([&](auto i) {
index_t tmp = ordered_access_lengths[I0] - 1;
static_for<1, i, 1>{}([&](auto j) {
tmp = tmp * ordered_access_lengths[j] + ordered_access_lengths[j] - 1;
});
forward_sweep_(i) = tmp % 2 == 0;
});
return forward_sweep_;
}();
// calculate dst data index after last iteration in Run(), if it has not being reset by
// RunWrite()
constexpr auto dst_data_idx = [&]() {
Index ordered_idx;
static_for<0, nDim, 1>{}([&](auto i) {
ordered_idx(i) = forward_sweep[i] ? ordered_access_lengths[i] - 1 : 0;
});
return container_reorder_given_old2new(ordered_idx, dim_access_order) *
dst_scalar_per_access;
}();
//
constexpr auto reset_dst_data_step = [&]() {
Index reset_dst_data_step_;
static_for<0, nDim, 1>{}([&](auto i) { reset_dst_data_step_(i) = -dst_data_idx[i]; });
return reset_dst_data_step_;
}();
return reset_dst_data_step;
}
// dst_slice_origin_step_idx need to be known at compile-time, for performance reason
__device__ void MoveDstSliceWindow(const DstDesc& dst_desc,
const Index& dst_slice_origin_step_idx)
{
// if dst coord was not reset by Run(), then need to adjust the step here
const auto adjusted_step_idx =
DstResetCoordinateAfterRun ? dst_slice_origin_step_idx
: dst_slice_origin_step_idx + GetDstCoordinateResetStep();
// is it OK to construct a new step every time?
const auto adjusted_step = make_tensor_coordinate_step(dst_desc, adjusted_step_idx);
move_tensor_coordinate(dst_desc, dst_coord_, adjusted_step);
}
private:
DstCoord dst_coord_;
const DstElementwiseOperation dst_element_op_;
}; // struct ThreadwiseTensorSliceTransfer_v1r3_using_space_filling_curve
} // namespace ck
#endif
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