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Commit b0ebfb40 authored by Jianfeng yan's avatar Jianfeng yan
Browse files

refactored threadcopy v3r1, v2; removed old implementations

parent d5d3788f
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composable_kernel/include/tensor_operation/blockwise_tensor_slice_transfer_v6r1.hpp
View file @ b0ebfb40
...@@ -5,8 +5,7 @@ ...@@ -5,8 +5,7 @@
#include "tensor_descriptor.hpp" #include "tensor_descriptor.hpp"
#include "tensor_descriptor_helper.hpp" #include "tensor_descriptor_helper.hpp"
#include "cluster_descriptor.hpp" #include "cluster_descriptor.hpp"
// #include "threadwise_tensor_slice_transfer_v6r1.hpp" #include "threadwise_tensor_slice_transfer_v6r1.hpp"
#include "threadwise_tensor_slice_transfer_v6r1_sfcurve.hpp"
namespace ck { namespace ck {
......
composable_kernel/include/tensor_operation/blockwise_tensor_slice_transfer_v6r2.hpp
View file @ b0ebfb40
...@@ -5,8 +5,7 @@ ...@@ -5,8 +5,7 @@
#include "tensor_descriptor.hpp" #include "tensor_descriptor.hpp"
#include "tensor_descriptor_helper.hpp" #include "tensor_descriptor_helper.hpp"
#include "cluster_descriptor.hpp" #include "cluster_descriptor.hpp"
// #include "threadwise_tensor_slice_transfer_v6r2.hpp" #include "threadwise_tensor_slice_transfer_v6r2.hpp"
#include "threadwise_tensor_slice_transfer_v6r2_sfcurve.hpp"
namespace ck { namespace ck {
......
composable_kernel/include/tensor_operation/blockwise_tensor_slice_transfer_v6r3.hpp
View file @ b0ebfb40
...@@ -5,8 +5,7 @@ ...@@ -5,8 +5,7 @@
#include "tensor_descriptor.hpp" #include "tensor_descriptor.hpp"
#include "tensor_descriptor_helper.hpp" #include "tensor_descriptor_helper.hpp"
#include "cluster_descriptor.hpp" #include "cluster_descriptor.hpp"
// #include "threadwise_tensor_slice_transfer_v6r3.hpp" #include "threadwise_tensor_slice_transfer_v6r3.hpp"
#include "threadwise_tensor_slice_transfer_v6r3_sfcurve.hpp"
namespace ck { namespace ck {
......
composable_kernel/include/tensor_operation/gridwise_gemm_xdlops_v2r3.hpp
View file @ b0ebfb40
...@@ -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_sfcurve.hpp" #include "threadwise_tensor_slice_transfer.hpp"
// #include "threadwise_tensor_slice_transfer.hpp"
#include "gridwise_gemm_pipeline_v1.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
n_thread_data_on_grid_to_n0_n1_n2_adaptor.CalculateBottomIndex( n_thread_data_on_grid_to_n0_n1_n2_adaptor.CalculateBottomIndex(
make_multi_index(n_thread_data_on_grid)); make_multi_index(n_thread_data_on_grid));
auto c_thread_copy = ThreadwiseTensorSliceTransfer_v1r3_sfcurve< auto c_thread_copy = ThreadwiseTensorSliceTransfer_v1r3<
FloatAcc, 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),
......
composable_kernel/include/tensor_operation/threadwise_tensor_slice_transfer_v3r1.hpp
View file @ b0ebfb40
...@@ -5,6 +5,7 @@ ...@@ -5,6 +5,7 @@
#include "tensor_descriptor.hpp" #include "tensor_descriptor.hpp"
#include "tensor_descriptor_helper.hpp" #include "tensor_descriptor_helper.hpp"
#include "static_tensor.hpp" #include "static_tensor.hpp"
#include "tensor_space_filling_curve.hpp"
namespace ck { namespace ck {
...@@ -123,73 +124,16 @@ struct ThreadwiseTensorSliceTransfer_v3r1 ...@@ -123,73 +124,16 @@ struct ThreadwiseTensorSliceTransfer_v3r1
constexpr auto src_scalar_per_access = generate_sequence( constexpr auto src_scalar_per_access = generate_sequence(
detail::lambda_scalar_per_access<SrcVectorDim, SrcScalarPerVector>{}, Number<nDim>{}); detail::lambda_scalar_per_access<SrcVectorDim, SrcScalarPerVector>{}, Number<nDim>{});
constexpr auto src_access_lengths = SliceLengths{} / src_scalar_per_access; using SpaceFillingCurve = SpaceFillingCurve<SliceLengths,
SrcDimAccessOrder,
constexpr auto src_dim_access_order = SrcDimAccessOrder{}; remove_cv_t<decltype(src_scalar_per_access)>>;
constexpr auto ordered_src_access_lengths =
container_reorder_given_new2old(src_access_lengths, src_dim_access_order);
// make forward steps
const auto src_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) ? src_scalar_per_access[i] : 0;
});
return make_tensor_coordinate_step(src_desc, forward_step_idx); // loop over space-filling curve
}, constexpr auto num_accesses = SpaceFillingCurve::GetNumOfAccess();
Number<nDim>{});
// make backward steps
const auto src_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) ? -src_scalar_per_access[i] : 0;
});
return make_tensor_coordinate_step(src_desc, backward_step_idx);
},
Number<nDim>{});
// loop over tensor and copy // loop over tensor and copy
static_ford<decltype(ordered_src_access_lengths)>{}([&](auto ordered_src_access_idx) { static_for<0, num_accesses, 1>{}([&](auto idx_1d) {
// judge move forward or move backward constexpr auto src_data_idx = SpaceFillingCurve::GetIndex(idx_1d);
constexpr auto forward_sweep = [&]() {
StaticallyIndexedArray<bool, nDim> forward_sweep_;
forward_sweep_(I0) = true;
static_for<1, nDim, 1>{}([&](auto i) {
index_t tmp = ordered_src_access_idx[I0];
static_for<1, i, 1>{}([&](auto j) {
tmp = tmp * ordered_src_access_lengths[j] + ordered_src_access_idx[j];
});
forward_sweep_(i) = tmp % 2 == 0;
});
return forward_sweep_;
}();
// calculate src data index
constexpr auto src_data_idx = [&]() {
Index ordered_idx;
static_for<0, nDim, 1>{}([&](auto i) {
ordered_idx(i) = forward_sweep[i] ? ordered_src_access_idx[i]
: ordered_src_access_lengths[i] - 1 -
ordered_src_access_idx[i];
});
return container_reorder_given_old2new(ordered_idx, src_dim_access_order) *
src_scalar_per_access;
}();
constexpr auto src_data_idx_seq = generate_sequence_v2( constexpr auto src_data_idx_seq = generate_sequence_v2(
[&](auto i) { return Number<src_data_idx[i]>{}; }, Number<src_data_idx.Size()>{}); [&](auto i) { return Number<src_data_idx[i]>{}; }, Number<src_data_idx.Size()>{});
...@@ -218,39 +162,13 @@ struct ThreadwiseTensorSliceTransfer_v3r1 ...@@ -218,39 +162,13 @@ struct ThreadwiseTensorSliceTransfer_v3r1
.template SetAsType<src_vector_t>( .template SetAsType<src_vector_t>(
src_data_idx_seq, src_vector_container.template AsType<src_vector_t>()[I0]); src_data_idx_seq, src_vector_container.template AsType<src_vector_t>()[I0]);
constexpr auto move_on_dim = [&]() constexpr // move coordinate
if constexpr(idx_1d.value != num_accesses - 1)
{ {
StaticallyIndexedArray<bool, nDim> move_on_dim_; constexpr auto forward_step = SpaceFillingCurve::GetForwardStep(idx_1d);
move_tensor_coordinate(
static_for<0, nDim, 1>{}([&](auto i) { src_desc, src_coord_, make_tensor_coordinate_step(src_desc, forward_step));
move_on_dim_(i) = ordered_src_access_idx[i] < ordered_src_access_lengths[i] - 1;
static_for<i + 1, nDim, 1>{}([&](auto j) {
move_on_dim_(i) &=
ordered_src_access_idx[j] == ordered_src_access_lengths[j] - 1;
});
});
return move_on_dim_;
} }
();
// move src coord
static_for<0, nDim, 1>{}([&](auto i) {
if constexpr(move_on_dim[i])
{
if constexpr(forward_sweep[i])
{
move_tensor_coordinate(
src_desc, src_coord_, src_forward_steps[src_dim_access_order[i]]);
}
else
{
move_tensor_coordinate(
src_desc, src_coord_, src_backward_steps[src_dim_access_order[i]]);
}
}
});
}); });
// move src coordinate back to slice origin (or not) // move src coordinate back to slice origin (or not)
...@@ -374,73 +292,15 @@ struct ThreadwiseTensorSliceTransfer_v3r1 ...@@ -374,73 +292,15 @@ struct ThreadwiseTensorSliceTransfer_v3r1
constexpr auto dst_scalar_per_access = generate_sequence( constexpr auto dst_scalar_per_access = generate_sequence(
detail::lambda_scalar_per_access<DstVectorDim, DstScalarPerVector>{}, Number<nDim>{}); detail::lambda_scalar_per_access<DstVectorDim, DstScalarPerVector>{}, Number<nDim>{});
constexpr auto dst_access_lengths = SliceLengths{} / dst_scalar_per_access; using SpaceFillingCurve = SpaceFillingCurve<SliceLengths,
DstDimAccessOrder,
constexpr auto dst_dim_access_order = DstDimAccessOrder{}; remove_cv_t<decltype(dst_scalar_per_access)>>;
constexpr auto ordered_dst_access_lengths =
container_reorder_given_new2old(dst_access_lengths, dst_dim_access_order);
// 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);
},
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) { constexpr auto num_accesses = SpaceFillingCurve::GetNumOfAccess();
backward_step_idx(j) = (i.value == j.value) ? -dst_scalar_per_access[i] : 0;
});
return make_tensor_coordinate_step(dst_desc, backward_step_idx);
},
Number<nDim>{});
// loop over tensor and copy // loop over tensor and copy
static_ford<decltype(ordered_dst_access_lengths)>{}([&](auto ordered_dst_access_idx) { static_for<0, num_accesses, 1>{}([&](auto idx_1d) {
// judge move forward or move backward constexpr auto dst_data_idx = SpaceFillingCurve::GetIndex(idx_1d);
constexpr auto forward_sweep = [&]() {
StaticallyIndexedArray<bool, nDim> forward_sweep_;
forward_sweep_(I0) = true;
static_for<1, nDim, 1>{}([&](auto i) {
index_t tmp = ordered_dst_access_idx[I0];
static_for<1, i, 1>{}([&](auto j) {
tmp = tmp * ordered_dst_access_lengths[j] + ordered_dst_access_idx[j];
});
forward_sweep_(i) = tmp % 2 == 0;
});
return forward_sweep_;
}();
// calculate dst data index
constexpr auto dst_data_idx = [&]() {
Index ordered_idx;
static_for<0, nDim, 1>{}([&](auto i) {
ordered_idx(i) = forward_sweep[i] ? ordered_dst_access_idx[i]
: ordered_dst_access_lengths[i] - 1 -
ordered_dst_access_idx[i];
});
return container_reorder_given_old2new(ordered_idx, dst_dim_access_order) *
dst_scalar_per_access;
}();
constexpr auto dst_data_idx_seq = generate_sequence_v2( constexpr auto dst_data_idx_seq = generate_sequence_v2(
[&](auto i) { return Number<dst_data_idx[i]>{}; }, Number<dst_data_idx.Size()>{}); [&](auto i) { return Number<dst_data_idx[i]>{}; }, Number<dst_data_idx.Size()>{});
...@@ -470,39 +330,13 @@ struct ThreadwiseTensorSliceTransfer_v3r1 ...@@ -470,39 +330,13 @@ struct ThreadwiseTensorSliceTransfer_v3r1
is_dst_valid, is_dst_valid,
dst_vector_container.template AsType<dst_vector_t>()[I0]); dst_vector_container.template AsType<dst_vector_t>()[I0]);
constexpr auto move_on_dim = [&]() constexpr // move coordinate
if constexpr(idx_1d.value != num_accesses - 1)
{ {
StaticallyIndexedArray<bool, nDim> move_on_dim_; constexpr auto forward_step = SpaceFillingCurve::GetForwardStep(idx_1d);
move_tensor_coordinate(
static_for<0, nDim, 1>{}([&](auto i) { dst_desc, dst_coord_, make_tensor_coordinate_step(dst_desc, forward_step));
move_on_dim_(i) = ordered_dst_access_idx[i] < ordered_dst_access_lengths[i] - 1;
static_for<i + 1, nDim, 1>{}([&](auto j) {
move_on_dim_(i) &=
ordered_dst_access_idx[j] == ordered_dst_access_lengths[j] - 1;
});
});
return move_on_dim_;
} }
();
// move dst coord
static_for<0, nDim, 1>{}([&](auto i) {
if constexpr(move_on_dim[i])
{
if constexpr(forward_sweep[i])
{
move_tensor_coordinate(
dst_desc, dst_coord_, dst_forward_steps[dst_dim_access_order[i]]);
}
else
{
move_tensor_coordinate(
dst_desc, dst_coord_, dst_backward_steps[dst_dim_access_order[i]]);
}
}
});
}); });
// move dst coordinate back to slice origin (or not) // move dst coordinate back to slice origin (or not)
...@@ -522,55 +356,15 @@ struct ThreadwiseTensorSliceTransfer_v3r1 ...@@ -522,55 +356,15 @@ struct ThreadwiseTensorSliceTransfer_v3r1
constexpr auto src_scalar_per_access = generate_sequence( constexpr auto src_scalar_per_access = generate_sequence(
detail::lambda_scalar_per_access<SrcVectorDim, SrcScalarPerVector>{}, Number<nDim>{}); detail::lambda_scalar_per_access<SrcVectorDim, SrcScalarPerVector>{}, Number<nDim>{});
constexpr auto src_access_lengths = SliceLengths{} / src_scalar_per_access; using SpaceFillingCurve = SpaceFillingCurve<SliceLengths,
SrcDimAccessOrder,
constexpr auto src_dim_access_order = SrcDimAccessOrder{}; remove_cv_t<decltype(src_scalar_per_access)>>;
constexpr auto ordered_src_access_lengths =
container_reorder_given_new2old(src_access_lengths, src_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_src_access_lengths[I0] - 1;
static_for<1, i, 1>{}([&](auto j) {
tmp = tmp * ordered_src_access_lengths[j] + ordered_src_access_lengths[j] - 1;
});
forward_sweep_(i) = tmp % 2 == 0;
});
return forward_sweep_;
}();
// calculate src data index after last iteration in RunRead(), if it has not being reset by constexpr auto num_accesses = SpaceFillingCurve::GetNumOfAccess();
// RunRead() constexpr auto reset_step =
constexpr auto src_data_idx = [&]() { SpaceFillingCurve::GetStepBetween(Number<num_accesses - 1>{}, Number<0>{});
Index ordered_idx;
static_for<0, nDim, 1>{}([&](auto i) { return reset_step;
ordered_idx(i) = forward_sweep[i] ? ordered_src_access_lengths[i] - 1 : 0;
});
return container_reorder_given_old2new(ordered_idx, src_dim_access_order) *
src_scalar_per_access;
}();
//
constexpr auto reset_src_data_step = [&]() {
Index reset_src_data_step_;
static_for<0, nDim, 1>{}([&](auto i) { reset_src_data_step_(i) = -src_data_idx[i]; });
return reset_src_data_step_;
}();
return reset_src_data_step;
} }
__device__ static constexpr auto GetDstCoordinateResetStep() __device__ static constexpr auto GetDstCoordinateResetStep()
...@@ -580,55 +374,15 @@ struct ThreadwiseTensorSliceTransfer_v3r1 ...@@ -580,55 +374,15 @@ struct ThreadwiseTensorSliceTransfer_v3r1
constexpr auto dst_scalar_per_access = generate_sequence( constexpr auto dst_scalar_per_access = generate_sequence(
detail::lambda_scalar_per_access<DstVectorDim, DstScalarPerVector>{}, Number<nDim>{}); detail::lambda_scalar_per_access<DstVectorDim, DstScalarPerVector>{}, Number<nDim>{});
constexpr auto dst_access_lengths = SliceLengths{} / dst_scalar_per_access; using SpaceFillingCurve = SpaceFillingCurve<SliceLengths,
DstDimAccessOrder,
constexpr auto dst_dim_access_order = DstDimAccessOrder{}; remove_cv_t<decltype(dst_scalar_per_access)>>;
constexpr auto ordered_dst_access_lengths =
container_reorder_given_new2old(dst_access_lengths, dst_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_dst_access_lengths[I0] - 1;
static_for<1, i, 1>{}([&](auto j) {
tmp = tmp * ordered_dst_access_lengths[j] + ordered_dst_access_lengths[j] - 1;
});
forward_sweep_(i) = tmp % 2 == 0;
});
return forward_sweep_;
}();
// calculate dst data index after last iteration in RunWrite(), 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_dst_access_lengths[i] - 1 : 0;
});
return container_reorder_given_old2new(ordered_idx, dst_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_; constexpr auto num_accesses = SpaceFillingCurve::GetNumOfAccess();
}(); constexpr auto reset_step =
SpaceFillingCurve::GetStepBetween(Number<num_accesses - 1>{}, Number<0>{});
return reset_dst_data_step; return reset_step;
} }
// src_slice_origin_step_idx need to be known at compile-time, for performance reason // src_slice_origin_step_idx need to be known at compile-time, for performance reason
......
composable_kernel/include/tensor_operation/threadwise_tensor_slice_transfer_v6r1.hpp
View file @ b0ebfb40
#ifndef CK_THREADWISE_TENSOR_SLICE_TRANSFER_V6R1_HPP #ifndef CK_THREADWISE_TENSOR_SLICE_TRANSFER_V6R1_SFCURVE_HPP
#define CK_THREADWISE_TENSOR_SLICE_TRANSFER_V6R1_HPP #define CK_THREADWISE_TENSOR_SLICE_TRANSFER_V6R1_SFCURVE_HPP
#include "common_header.hpp" #include "common_header.hpp"
#include "tensor_descriptor.hpp" #include "tensor_descriptor.hpp"
#include "tensor_descriptor_helper.hpp" #include "tensor_descriptor_helper.hpp"
#include "tensor_space_filling_curve.hpp"
namespace ck { namespace ck {
...@@ -40,9 +41,6 @@ struct ThreadwiseTensorSliceTransfer_v6r1 ...@@ -40,9 +41,6 @@ struct ThreadwiseTensorSliceTransfer_v6r1
using SrcCoord = decltype(make_tensor_coordinate(SrcDesc{}, Index{})); using SrcCoord = decltype(make_tensor_coordinate(SrcDesc{}, Index{}));
using DstCoord = decltype(make_tensor_coordinate(DstDesc{}, Index{})); using DstCoord = decltype(make_tensor_coordinate(DstDesc{}, Index{}));
using SrcCoordStep = decltype(make_tensor_coordinate_step(SrcDesc{}, Index{}));
using DstCoordStep = decltype(make_tensor_coordinate_step(DstDesc{}, Index{}));
static constexpr auto I0 = Number<0>{}; static constexpr auto I0 = Number<0>{};
__device__ constexpr ThreadwiseTensorSliceTransfer_v6r1(const SrcDesc& src_desc, __device__ constexpr ThreadwiseTensorSliceTransfer_v6r1(const SrcDesc& src_desc,
...@@ -79,70 +77,14 @@ struct ThreadwiseTensorSliceTransfer_v6r1 ...@@ -79,70 +77,14 @@ struct ThreadwiseTensorSliceTransfer_v6r1
constexpr auto scalar_per_access = generate_sequence( constexpr auto scalar_per_access = generate_sequence(
detail::lambda_scalar_per_access<VectorDim, ScalarPerVector>{}, Number<nDim>{}); detail::lambda_scalar_per_access<VectorDim, ScalarPerVector>{}, Number<nDim>{});
constexpr auto access_lengths = SliceLengths{} / scalar_per_access; using SpaceFillingCurve = SpaceFillingCurve<SliceLengths,
DimAccessOrder,
constexpr auto dim_access_order = DimAccessOrder{}; remove_cv_t<decltype(scalar_per_access)>>;
constexpr auto ordered_access_lengths =
container_reorder_given_new2old(access_lengths, dim_access_order);
auto make_forward_steps = [&](auto desc) {
return generate_tuple(
[&](auto i) {
Index forward_step_idx;
static_for<0, nDim, 1>{}([&](auto j) {
forward_step_idx(j) = (i.value == j.value) ? scalar_per_access[i] : 0;
});
return make_tensor_coordinate_step(desc, forward_step_idx);
},
Number<nDim>{});
};
auto make_backward_steps = [&](auto desc) {
return generate_tuple(
[&](auto i) {
Index backward_step_idx;
static_for<0, nDim, 1>{}([&](auto j) {
backward_step_idx(j) = (i.value == j.value) ? -scalar_per_access[i] : 0;
});
return make_tensor_coordinate_step(desc, backward_step_idx);
},
Number<nDim>{});
};
// make forward steps
const auto src_forward_steps = make_forward_steps(src_desc);
const auto dst_forward_steps = make_forward_steps(dst_desc);
// make backward steps
const auto src_backward_steps = make_backward_steps(src_desc);
const auto dst_backward_steps = make_backward_steps(dst_desc);
// loop over slice window // loop over space-filling curve
static_ford<decltype(ordered_access_lengths)>{}([&](auto ordered_access_idx) { constexpr auto num_accesses = SpaceFillingCurve::GetNumOfAccess();
// judge move forward or move backward
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_idx[I0];
static_for<1, i, 1>{}([&](auto j) {
tmp = tmp * ordered_access_lengths[j] + ordered_access_idx[j];
});
forward_sweep_(i) = tmp % 2 == 0;
});
return forward_sweep_;
}();
static_for<0, num_accesses, 1>{}([&](auto idx_1d) {
using src_vector_type = vector_type_maker_t<SrcData, ScalarPerVector>; using src_vector_type = vector_type_maker_t<SrcData, ScalarPerVector>;
using src_vector_t = typename src_vector_type::type; using src_vector_t = typename src_vector_type::type;
...@@ -168,59 +110,20 @@ struct ThreadwiseTensorSliceTransfer_v6r1 ...@@ -168,59 +110,20 @@ struct ThreadwiseTensorSliceTransfer_v6r1
coordinate_has_valid_offset_assuming_visible_index_is_valid(dst_desc, dst_coord_); coordinate_has_valid_offset_assuming_visible_index_is_valid(dst_desc, dst_coord_);
// copy data from dst_vector into dst_buf // copy data from dst_vector into dst_buf
if constexpr(DstInMemOp == InMemoryDataOperationEnum_t::Set) dst_buf.template Update<DstInMemOp, dst_vector_t>(
{ dst_coord_.GetOffset(),
dst_buf.template Set<dst_vector_t>( is_dst_valid,
dst_coord_.GetOffset(), dst_vector_container.template AsType<dst_vector_t>()[I0]);
is_dst_valid,
dst_vector_container.template AsType<dst_vector_t>()[I0]);
}
else if constexpr(DstInMemOp == InMemoryDataOperationEnum_t::AtomicAdd)
{
dst_buf.template AtomicAdd<dst_vector_t>(
dst_coord_.GetOffset(),
is_dst_valid,
dst_vector_container.template AsType<dst_vector_t>()[I0]);
}
constexpr auto move_on_dim = [&]() constexpr // move coordinate
if constexpr(idx_1d.value != num_accesses - 1)
{ {
StaticallyIndexedArray<bool, nDim> move_on_dim_; constexpr auto forward_step = SpaceFillingCurve::GetForwardStep(idx_1d);
move_tensor_coordinate(
static_for<0, nDim, 1>{}([&](auto i) { src_desc, src_coord_, make_tensor_coordinate_step(src_desc, forward_step));
move_on_dim_(i) = ordered_access_idx[i] < ordered_access_lengths[i] - 1; move_tensor_coordinate(
dst_desc, dst_coord_, make_tensor_coordinate_step(dst_desc, forward_step));
static_for<i + 1, nDim, 1>{}([&](auto j) {
move_on_dim_(i) &= ordered_access_idx[j] == ordered_access_lengths[j] - 1;
});
});
return move_on_dim_;
} }
();
// move coordinate
static_for<0, nDim, 1>{}([&](auto i) {
if constexpr(move_on_dim[i])
{
if constexpr(forward_sweep[i])
{
move_tensor_coordinate(
src_desc, src_coord_, src_forward_steps[dim_access_order[i]]);
move_tensor_coordinate(
dst_desc, dst_coord_, dst_forward_steps[dim_access_order[i]]);
}
else
{
move_tensor_coordinate(
src_desc, src_coord_, src_backward_steps[dim_access_order[i]]);
move_tensor_coordinate(
dst_desc, dst_coord_, dst_backward_steps[dim_access_order[i]]);
}
}
});
}); });
// move coordinate back to slice origin (or not) // move coordinate back to slice origin (or not)
...@@ -243,59 +146,18 @@ struct ThreadwiseTensorSliceTransfer_v6r1 ...@@ -243,59 +146,18 @@ struct ThreadwiseTensorSliceTransfer_v6r1
__device__ static constexpr auto GetCoordinateResetStep() __device__ static constexpr auto GetCoordinateResetStep()
{ {
// scalar per access on each dim
// TODO: don't use lambda_scalar_per_access
constexpr auto scalar_per_access = generate_sequence( constexpr auto scalar_per_access = generate_sequence(
detail::lambda_scalar_per_access<VectorDim, ScalarPerVector>{}, Number<nDim>{}); detail::lambda_scalar_per_access<VectorDim, ScalarPerVector>{}, Number<nDim>{});
constexpr auto access_lengths = SliceLengths{} / scalar_per_access; using SpaceFillingCurve = SpaceFillingCurve<SliceLengths,
DimAccessOrder,
constexpr auto dim_access_order = DimAccessOrder{}; remove_cv_t<decltype(scalar_per_access)>>;
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 data index after last iteration in Run(), if it has not being reset
constexpr auto 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) *
scalar_per_access;
}();
//
constexpr auto reset_data_step = [&]() {
Index reset_data_step_;
static_for<0, nDim, 1>{}([&](auto i) { reset_data_step_(i) = -data_idx[i]; });
return reset_data_step_; constexpr auto num_accesses = SpaceFillingCurve::GetNumOfAccess();
}(); constexpr auto reset_step =
SpaceFillingCurve::GetStepBetween(Number<num_accesses - 1>{}, Number<0>{});
return reset_data_step; return reset_step;
} }
// src_slice_origin_step_idx need to be known at compile-time, for performance reason // src_slice_origin_step_idx need to be known at compile-time, for performance reason
...@@ -332,7 +194,7 @@ struct ThreadwiseTensorSliceTransfer_v6r1 ...@@ -332,7 +194,7 @@ struct ThreadwiseTensorSliceTransfer_v6r1
SrcCoord src_coord_; SrcCoord src_coord_;
DstCoord dst_coord_; DstCoord dst_coord_;
const ElementwiseOperation element_op_; const ElementwiseOperation element_op_;
}; }; // namespace ck
} // namespace ck } // namespace ck
#endif #endif
composable_kernel/include/tensor_operation/threadwise_tensor_slice_transfer_v6r1_sfcurve.hpp deleted 100644 → 0
View file @ d5d3788f
#ifndef CK_THREADWISE_TENSOR_SLICE_TRANSFER_V6R1_SFCURVE_HPP
#define CK_THREADWISE_TENSOR_SLICE_TRANSFER_V6R1_SFCURVE_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
// Assume:
// 1. src_desc and dst_desc are not known at compile-time
// 2. SrcBuffer and DstBuffer are DynamicBuffer
// 3. src_slice_origin and dst_slice_origin are not known at compile-time,
template <typename SrcData,
typename DstData,
typename SrcDesc,
typename DstDesc,
typename ElementwiseOperation,
typename SliceLengths,
typename DimAccessOrder,
index_t VectorDim,
index_t ScalarPerVector,
InMemoryDataOperationEnum_t DstInMemOp,
bool SrcResetCoordinateAfterRun,
bool DstResetCoordinateAfterRun>
struct ThreadwiseTensorSliceTransfer_v6r1
{
static constexpr index_t nDim = SliceLengths::Size();
using Index = MultiIndex<nDim>;
using SrcCoord = decltype(make_tensor_coordinate(SrcDesc{}, Index{}));
using DstCoord = decltype(make_tensor_coordinate(DstDesc{}, Index{}));
static constexpr auto I0 = Number<0>{};
__device__ constexpr ThreadwiseTensorSliceTransfer_v6r1(const SrcDesc& src_desc,
const Index& src_slice_origin,
const DstDesc& dst_desc,
const Index& dst_slice_origin,
const ElementwiseOperation& element_op)
: src_coord_(make_tensor_coordinate(src_desc, src_slice_origin)),
dst_coord_(make_tensor_coordinate(dst_desc, dst_slice_origin)),
element_op_(element_op)
{
static_assert(SliceLengths::At(Number<VectorDim>{}) % ScalarPerVector == 0,
"wrong! cannot evenly divide");
}
__device__ void SetSrcSliceOrigin(const SrcDesc& src_desc, const Index& src_slice_origin_idx)
{
src_coord_ = make_tensor_coordinate(src_desc, src_slice_origin_idx);
}
__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 SrcBuffer, typename DstBuffer>
__device__ void Run(const SrcDesc& src_desc,
const SrcBuffer& src_buf,
const DstDesc& dst_desc,
DstBuffer& dst_buf)
{
// scalar per access on each dim
// TODO: don't use lambda_scalar_per_access
constexpr auto scalar_per_access = generate_sequence(
detail::lambda_scalar_per_access<VectorDim, ScalarPerVector>{}, Number<nDim>{});
using SpaceFillingCurve = SpaceFillingCurve<SliceLengths,
DimAccessOrder,
remove_cv_t<decltype(scalar_per_access)>>;
// loop over space-filling curve
constexpr auto num_accesses = SpaceFillingCurve::GetNumOfAccess();
static_for<0, num_accesses, 1>{}([&](auto idx_1d) {
using src_vector_type = vector_type_maker_t<SrcData, ScalarPerVector>;
using src_vector_t = typename src_vector_type::type;
using dst_vector_type = vector_type_maker_t<DstData, ScalarPerVector>;
using dst_vector_t = typename dst_vector_type::type;
const bool is_src_valid =
coordinate_has_valid_offset_assuming_visible_index_is_valid(src_desc, src_coord_);
// copy data from src_buf into src_vector_container
auto src_vector_container = src_vector_type{
src_buf.template Get<src_vector_t>(src_coord_.GetOffset(), is_src_valid)};
auto dst_vector_container = dst_vector_type{};
// apply pointwise operation
static_for<0, ScalarPerVector, 1>{}([&](auto i) {
element_op_(dst_vector_container.template AsType<DstData>()(i),
src_vector_container.template AsType<SrcData>()[i]);
});
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
dst_buf.template Transfer<DstInMemOp, dst_vector_t>(
dst_coord_.GetOffset(),
is_dst_valid,
dst_vector_container.template AsType<dst_vector_t>()[I0]);
// move coordinate
if constexpr(idx_1d.value != num_accesses - 1)
{
constexpr auto forward_step = SpaceFillingCurve::GetForwardStep(idx_1d);
move_tensor_coordinate(
src_desc, src_coord_, make_tensor_coordinate_step(src_desc, forward_step));
move_tensor_coordinate(
dst_desc, dst_coord_, make_tensor_coordinate_step(dst_desc, forward_step));
}
});
// move coordinate back to slice origin (or not)
if constexpr(SrcResetCoordinateAfterRun)
{
const auto src_reset_step =
make_tensor_coordinate_step(src_desc, GetCoordinateResetStep());
move_tensor_coordinate(src_desc, src_coord_, src_reset_step);
}
if constexpr(DstResetCoordinateAfterRun)
{
const auto dst_reset_step =
make_tensor_coordinate_step(dst_desc, GetCoordinateResetStep());
move_tensor_coordinate(dst_desc, dst_coord_, dst_reset_step);
}
}
__device__ static constexpr auto GetCoordinateResetStep()
{
constexpr auto scalar_per_access = generate_sequence(
detail::lambda_scalar_per_access<VectorDim, ScalarPerVector>{}, Number<nDim>{});
using SpaceFillingCurve = SpaceFillingCurve<SliceLengths,
DimAccessOrder,
remove_cv_t<decltype(scalar_per_access)>>;
constexpr auto num_accesses = SpaceFillingCurve::GetNumOfAccess();
constexpr auto reset_step =
SpaceFillingCurve::GetStepBetween(Number<num_accesses - 1>{}, Number<0>{});
return reset_step;
}
// src_slice_origin_step_idx need to be known at compile-time, for performance reason
__device__ void MoveSrcSliceWindow(const SrcDesc& src_desc,
const Index& src_slice_origin_step_idx)
{
// if src coord was not reset by RunRead(), then need to adjust the step here
const auto adjusted_step_idx = SrcResetCoordinateAfterRun
? src_slice_origin_step_idx
: src_slice_origin_step_idx + GetCoordinateResetStep();
// is it OK to construct a new step every time?
const auto adjusted_step = make_tensor_coordinate_step(src_desc, adjusted_step_idx);
move_tensor_coordinate(src_desc, src_coord_, adjusted_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 + GetCoordinateResetStep();
// 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:
SrcCoord src_coord_;
DstCoord dst_coord_;
const ElementwiseOperation element_op_;
}; // namespace ck
} // namespace ck
#endif
composable_kernel/include/tensor_operation/threadwise_tensor_slice_transfer_v6r2.hpp
View file @ b0ebfb40
#ifndef CK_THREADWISE_TENSOR_SLICE_TRANSFER_V6R2_HPP #ifndef CK_THREADWISE_TENSOR_SLICE_TRANSFER_V6R2_SFCURVE_HPP
#define CK_THREADWISE_TENSOR_SLICE_TRANSFER_V6R2_HPP #define CK_THREADWISE_TENSOR_SLICE_TRANSFER_V6R2_SFCURVE_HPP
#include "common_header.hpp" #include "common_header.hpp"
#include "tensor_descriptor.hpp" #include "tensor_descriptor.hpp"
#include "tensor_descriptor_helper.hpp" #include "tensor_descriptor_helper.hpp"
#include "tensor_space_filling_curve.hpp"
namespace ck { namespace ck {
...@@ -44,10 +45,6 @@ struct ThreadwiseTensorSliceTransfer_v6r2 ...@@ -44,10 +45,6 @@ struct ThreadwiseTensorSliceTransfer_v6r2
using Src1Coord = decltype(make_tensor_coordinate(Src1Desc{}, Index{})); using Src1Coord = decltype(make_tensor_coordinate(Src1Desc{}, Index{}));
using DstCoord = decltype(make_tensor_coordinate(DstDesc{}, Index{})); using DstCoord = decltype(make_tensor_coordinate(DstDesc{}, Index{}));
using Src0CoordStep = decltype(make_tensor_coordinate_step(Src0Desc{}, Index{}));
using Src1CoordStep = decltype(make_tensor_coordinate_step(Src1Desc{}, Index{}));
using DstCoordStep = decltype(make_tensor_coordinate_step(DstDesc{}, Index{}));
static constexpr auto I0 = Number<0>{}; static constexpr auto I0 = Number<0>{};
__device__ constexpr ThreadwiseTensorSliceTransfer_v6r2(const Src0Desc& src0_desc, __device__ constexpr ThreadwiseTensorSliceTransfer_v6r2(const Src0Desc& src0_desc,
...@@ -96,72 +93,14 @@ struct ThreadwiseTensorSliceTransfer_v6r2 ...@@ -96,72 +93,14 @@ struct ThreadwiseTensorSliceTransfer_v6r2
constexpr auto scalar_per_access = generate_sequence( constexpr auto scalar_per_access = generate_sequence(
detail::lambda_scalar_per_access<VectorDim, ScalarPerVector>{}, Number<nDim>{}); detail::lambda_scalar_per_access<VectorDim, ScalarPerVector>{}, Number<nDim>{});
constexpr auto access_lengths = SliceLengths{} / scalar_per_access; using SpaceFillingCurve = SpaceFillingCurve<SliceLengths,
DimAccessOrder,
constexpr auto dim_access_order = DimAccessOrder{}; remove_cv_t<decltype(scalar_per_access)>>;
constexpr auto ordered_access_lengths =
container_reorder_given_new2old(access_lengths, dim_access_order);
auto make_forward_steps = [&](auto desc) {
return generate_tuple(
[&](auto i) {
Index forward_step_idx;
static_for<0, nDim, 1>{}([&](auto j) {
forward_step_idx(j) = (i.value == j.value) ? scalar_per_access[i] : 0;
});
return make_tensor_coordinate_step(desc, forward_step_idx);
},
Number<nDim>{});
};
auto make_backward_steps = [&](auto desc) {
return generate_tuple(
[&](auto i) {
Index backward_step_idx;
static_for<0, nDim, 1>{}([&](auto j) {
backward_step_idx(j) = (i.value == j.value) ? -scalar_per_access[i] : 0;
});
return make_tensor_coordinate_step(desc, backward_step_idx);
},
Number<nDim>{});
};
// make forward steps
const auto src0_forward_steps = make_forward_steps(src0_desc);
const auto src1_forward_steps = make_forward_steps(src1_desc);
const auto dst_forward_steps = make_forward_steps(dst_desc);
// make backward steps
const auto src0_backward_steps = make_backward_steps(src0_desc);
const auto src1_backward_steps = make_backward_steps(src1_desc);
const auto dst_backward_steps = make_backward_steps(dst_desc);
// loop over slice window constexpr auto num_accesses = SpaceFillingCurve::GetNumOfAccess();
static_ford<decltype(ordered_access_lengths)>{}([&](auto ordered_access_idx) {
// judge move forward or move backward
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_idx[I0];
static_for<1, i, 1>{}([&](auto j) {
tmp = tmp * ordered_access_lengths[j] + ordered_access_idx[j];
});
forward_sweep_(i) = tmp % 2 == 0;
});
return forward_sweep_;
}();
// loop over space-filling curve
static_for<0, num_accesses, 1>{}([&](auto idx_1d) {
using src0_vector_type = vector_type_maker_t<Src0Data, ScalarPerVector>; using src0_vector_type = vector_type_maker_t<Src0Data, ScalarPerVector>;
using src0_vector_t = typename src0_vector_type::type; using src0_vector_t = typename src0_vector_type::type;
...@@ -197,65 +136,22 @@ struct ThreadwiseTensorSliceTransfer_v6r2 ...@@ -197,65 +136,22 @@ struct ThreadwiseTensorSliceTransfer_v6r2
coordinate_has_valid_offset_assuming_visible_index_is_valid(dst_desc, dst_coord_); coordinate_has_valid_offset_assuming_visible_index_is_valid(dst_desc, dst_coord_);
// copy data from dst_vector into dst_buf // copy data from dst_vector into dst_buf
if constexpr(DstInMemOp == InMemoryDataOperationEnum_t::Set) dst_buf.template Update<DstInMemOp, dst_vector_t>(
{ dst_coord_.GetOffset(),
dst_buf.template Set<dst_vector_t>( is_dst_valid,
dst_coord_.GetOffset(), dst_vector_container.template AsType<dst_vector_t>()[I0]);
is_dst_valid,
dst_vector_container.template AsType<dst_vector_t>()[I0]);
}
else if constexpr(DstInMemOp == InMemoryDataOperationEnum_t::AtomicAdd)
{
dst_buf.template AtomicAdd<dst_vector_t>(
dst_coord_.GetOffset(),
is_dst_valid,
dst_vector_container.template AsType<dst_vector_t>()[I0]);
}
constexpr auto move_on_dim = [&]() constexpr // move coordinate
if constexpr(idx_1d.value != num_accesses - 1)
{ {
StaticallyIndexedArray<bool, nDim> move_on_dim_; constexpr auto forward_step = SpaceFillingCurve::GetForwardStep(idx_1d);
move_tensor_coordinate(
static_for<0, nDim, 1>{}([&](auto i) { src0_desc, src0_coord_, make_tensor_coordinate_step(src0_desc, forward_step));
move_on_dim_(i) = ordered_access_idx[i] < ordered_access_lengths[i] - 1; move_tensor_coordinate(
src1_desc, src1_coord_, make_tensor_coordinate_step(src1_desc, forward_step));
static_for<i + 1, nDim, 1>{}([&](auto j) { move_tensor_coordinate(
move_on_dim_(i) &= ordered_access_idx[j] == ordered_access_lengths[j] - 1; dst_desc, dst_coord_, make_tensor_coordinate_step(dst_desc, forward_step));
});
});
return move_on_dim_;
} }
();
// move coordinate
static_for<0, nDim, 1>{}([&](auto i) {
if constexpr(move_on_dim[i])
{
if constexpr(forward_sweep[i])
{
move_tensor_coordinate(
src0_desc, src0_coord_, src0_forward_steps[dim_access_order[i]]);
move_tensor_coordinate(
src1_desc, src1_coord_, src1_forward_steps[dim_access_order[i]]);
move_tensor_coordinate(
dst_desc, dst_coord_, dst_forward_steps[dim_access_order[i]]);
}
else
{
move_tensor_coordinate(
src0_desc, src0_coord_, src0_backward_steps[dim_access_order[i]]);
move_tensor_coordinate(
src1_desc, src1_coord_, src1_backward_steps[dim_access_order[i]]);
move_tensor_coordinate(
dst_desc, dst_coord_, dst_backward_steps[dim_access_order[i]]);
}
}
});
}); });
// move coordinate back to slice origin (or not) // move coordinate back to slice origin (or not)
...@@ -286,59 +182,18 @@ struct ThreadwiseTensorSliceTransfer_v6r2 ...@@ -286,59 +182,18 @@ struct ThreadwiseTensorSliceTransfer_v6r2
__device__ static constexpr auto GetCoordinateResetStep() __device__ static constexpr auto GetCoordinateResetStep()
{ {
// scalar per access on each dim
// TODO: don't use lambda_scalar_per_access
constexpr auto scalar_per_access = generate_sequence( constexpr auto scalar_per_access = generate_sequence(
detail::lambda_scalar_per_access<VectorDim, ScalarPerVector>{}, Number<nDim>{}); detail::lambda_scalar_per_access<VectorDim, ScalarPerVector>{}, Number<nDim>{});
constexpr auto access_lengths = SliceLengths{} / scalar_per_access; using SpaceFillingCurve = SpaceFillingCurve<SliceLengths,
DimAccessOrder,
constexpr auto dim_access_order = DimAccessOrder{}; remove_cv_t<decltype(scalar_per_access)>>;
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 data index after last iteration in Run(), if it has not being reset
constexpr auto 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) *
scalar_per_access;
}();
//
constexpr auto reset_data_step = [&]() {
Index reset_data_step_;
static_for<0, nDim, 1>{}([&](auto i) { reset_data_step_(i) = -data_idx[i]; });
return reset_data_step_; constexpr auto num_accesses = SpaceFillingCurve::GetNumOfAccess();
}(); constexpr auto reset_step =
SpaceFillingCurve::GetStepBetween(Number<num_accesses - 1>{}, Number<0>{});
return reset_data_step; return reset_step;
} }
// src_slice_origin_step_idx need to be known at compile-time, for performance reason // src_slice_origin_step_idx need to be known at compile-time, for performance reason
......
composable_kernel/include/tensor_operation/threadwise_tensor_slice_transfer_v6r2_sfcurve.hpp deleted 100644 → 0
View file @ d5d3788f
#ifndef CK_THREADWISE_TENSOR_SLICE_TRANSFER_V6R2_SFCURVE_HPP
#define CK_THREADWISE_TENSOR_SLICE_TRANSFER_V6R2_SFCURVE_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
// Assume:
// 1. src0_desc and dst_desc are not known at compile-time
// 2. SrcBuffer and DstBuffer are DynamicBuffer
// 3. src_slice_origin and dst_slice_origin are not known at compile-time,
template <typename Src0Data,
typename Src1Data,
typename DstData,
typename Src0Desc,
typename Src1Desc,
typename DstDesc,
typename ElementwiseOperation,
typename SliceLengths,
typename DimAccessOrder,
index_t VectorDim,
index_t ScalarPerVector,
InMemoryDataOperationEnum_t DstInMemOp,
bool Src0ResetCoordinateAfterRun,
bool Src1ResetCoordinateAfterRun,
bool DstResetCoordinateAfterRun>
struct ThreadwiseTensorSliceTransfer_v6r2
{
static constexpr index_t nDim = SliceLengths::Size();
using Index = MultiIndex<nDim>;
using Src0Coord = decltype(make_tensor_coordinate(Src0Desc{}, Index{}));
using Src1Coord = decltype(make_tensor_coordinate(Src1Desc{}, Index{}));
using DstCoord = decltype(make_tensor_coordinate(DstDesc{}, Index{}));
static constexpr auto I0 = Number<0>{};
__device__ constexpr ThreadwiseTensorSliceTransfer_v6r2(const Src0Desc& src0_desc,
const Index& src0_slice_origin,
const Src1Desc& src1_desc,
const Index& src1_slice_origin,
const DstDesc& dst_desc,
const Index& dst_slice_origin,
const ElementwiseOperation& element_op)
: src0_coord_(make_tensor_coordinate(src0_desc, src0_slice_origin)),
src1_coord_(make_tensor_coordinate(src1_desc, src1_slice_origin)),
dst_coord_(make_tensor_coordinate(dst_desc, dst_slice_origin)),
element_op_(element_op)
{
static_assert(SliceLengths::At(Number<VectorDim>{}) % ScalarPerVector == 0,
"wrong! cannot evenly divide");
}
__device__ void SetSrc0SliceOrigin(const Src0Desc& src0_desc,
const Index& src0_slice_origin_idx)
{
src0_coord_ = make_tensor_coordinate(src0_desc, src0_slice_origin_idx);
}
__device__ void SetSrc1SliceOrigin(const Src1Desc& src1_desc,
const Index& src1_slice_origin_idx)
{
src1_coord_ = make_tensor_coordinate(src1_desc, src1_slice_origin_idx);
}
__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 Src0Buffer, typename Src1Buffer, typename DstBuffer>
__device__ void Run(const Src0Desc& src0_desc,
const Src0Buffer& src0_buf,
const Src1Desc& src1_desc,
const Src1Buffer& src1_buf,
const DstDesc& dst_desc,
DstBuffer& dst_buf)
{
// scalar per access on each dim
// TODO: don't use lambda_scalar_per_access
constexpr auto scalar_per_access = generate_sequence(
detail::lambda_scalar_per_access<VectorDim, ScalarPerVector>{}, Number<nDim>{});
using SpaceFillingCurve = SpaceFillingCurve<SliceLengths,
DimAccessOrder,
remove_cv_t<decltype(scalar_per_access)>>;
constexpr auto num_accesses = SpaceFillingCurve::GetNumOfAccess();
// loop over space-filling curve
static_for<0, num_accesses, 1>{}([&](auto idx_1d) {
using src0_vector_type = vector_type_maker_t<Src0Data, ScalarPerVector>;
using src0_vector_t = typename src0_vector_type::type;
using src1_vector_type = vector_type_maker_t<Src1Data, ScalarPerVector>;
using src1_vector_t = typename src1_vector_type::type;
using dst_vector_type = vector_type_maker_t<DstData, ScalarPerVector>;
using dst_vector_t = typename dst_vector_type::type;
const bool is_src0_valid =
coordinate_has_valid_offset_assuming_visible_index_is_valid(src0_desc, src0_coord_);
const bool is_src1_valid =
coordinate_has_valid_offset_assuming_visible_index_is_valid(src1_desc, src1_coord_);
// copy data from src0_buf into src0_vector_container
auto src0_vector_container = src0_vector_type{
src0_buf.template Get<src0_vector_t>(src0_coord_.GetOffset(), is_src0_valid)};
auto src1_vector_container = src1_vector_type{
src1_buf.template Get<src1_vector_t>(src1_coord_.GetOffset(), is_src1_valid)};
auto dst_vector_container = dst_vector_type{};
// apply pointwise operation
static_for<0, ScalarPerVector, 1>{}([&](auto i) {
element_op_(dst_vector_container.template AsType<DstData>()(i),
src0_vector_container.template AsType<Src0Data>()[i],
src1_vector_container.template AsType<Src1Data>()[i]);
});
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
dst_buf.template Transfer<DstInMemOp, dst_vector_t>(
dst_coord_.GetOffset(),
is_dst_valid,
dst_vector_container.template AsType<dst_vector_t>()[I0]);
// move coordinate
if constexpr(idx_1d.value != num_accesses - 1)
{
constexpr auto forward_step = SpaceFillingCurve::GetForwardStep(idx_1d);
move_tensor_coordinate(
src0_desc, src0_coord_, make_tensor_coordinate_step(src0_desc, forward_step));
move_tensor_coordinate(
src1_desc, src1_coord_, make_tensor_coordinate_step(src1_desc, forward_step));
move_tensor_coordinate(
dst_desc, dst_coord_, make_tensor_coordinate_step(dst_desc, forward_step));
}
});
// move coordinate back to slice origin (or not)
if constexpr(Src0ResetCoordinateAfterRun)
{
const auto src0_reset_step =
make_tensor_coordinate_step(src0_desc, GetCoordinateResetStep());
move_tensor_coordinate(src0_desc, src0_coord_, src0_reset_step);
}
if constexpr(Src1ResetCoordinateAfterRun)
{
const auto src1_reset_step =
make_tensor_coordinate_step(src1_desc, GetCoordinateResetStep());
move_tensor_coordinate(src1_desc, src1_coord_, src1_reset_step);
}
if constexpr(DstResetCoordinateAfterRun)
{
const auto dst_reset_step =
make_tensor_coordinate_step(dst_desc, GetCoordinateResetStep());
move_tensor_coordinate(dst_desc, dst_coord_, dst_reset_step);
}
}
__device__ static constexpr auto GetCoordinateResetStep()
{
constexpr auto scalar_per_access = generate_sequence(
detail::lambda_scalar_per_access<VectorDim, ScalarPerVector>{}, Number<nDim>{});
using SpaceFillingCurve = SpaceFillingCurve<SliceLengths,
DimAccessOrder,
remove_cv_t<decltype(scalar_per_access)>>;
constexpr auto num_accesses = SpaceFillingCurve::GetNumOfAccess();
constexpr auto reset_step =
SpaceFillingCurve::GetStepBetween(Number<num_accesses - 1>{}, Number<0>{});
return reset_step;
}
// src_slice_origin_step_idx need to be known at compile-time, for performance reason
__device__ void MoveSrc0SliceWindow(const Src0Desc& src0_desc,
const Index& src0_slice_origin_step_idx)
{
// if src coord was not reset by RunRead(), then need to adjust the step here
const auto adjusted_step_idx = Src0ResetCoordinateAfterRun
? src0_slice_origin_step_idx
: src0_slice_origin_step_idx + GetCoordinateResetStep();
// is it OK to construct a new step every time?
const auto adjusted_step = make_tensor_coordinate_step(src0_desc, adjusted_step_idx);
move_tensor_coordinate(src0_desc, src0_coord_, adjusted_step);
}
// src_slice_origin_step_idx need to be known at compile-time, for performance reason
__device__ void MoveSrc1SliceWindow(const Src1Desc& src1_desc,
const Index& src1_slice_origin_step_idx)
{
// if src coord was not reset by RunRead(), then need to adjust the step here
const auto adjusted_step_idx = Src1ResetCoordinateAfterRun
? src1_slice_origin_step_idx
: src1_slice_origin_step_idx + GetCoordinateResetStep();
// is it OK to construct a new step every time?
const auto adjusted_step = make_tensor_coordinate_step(src1_desc, adjusted_step_idx);
move_tensor_coordinate(src1_desc, src1_coord_, adjusted_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 + GetCoordinateResetStep();
// 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:
Src0Coord src0_coord_;
Src1Coord src1_coord_;
DstCoord dst_coord_;
const ElementwiseOperation element_op_;
};
} // namespace ck
#endif
composable_kernel/include/tensor_operation/threadwise_tensor_slice_transfer_v6r3.hpp
View file @ b0ebfb40
#ifndef CK_THREADWISE_TENSOR_SLICE_TRANSFER_V6R3_HPP #ifndef CK_THREADWISE_TENSOR_SLICE_TRANSFER_V6R3_SPCURVE_HPP
#define CK_THREADWISE_TENSOR_SLICE_TRANSFER_V6R3_HPP #define CK_THREADWISE_TENSOR_SLICE_TRANSFER_V6R3_SPCURVE_HPP
#include "common_header.hpp" #include "common_header.hpp"
#include "tensor_descriptor.hpp" #include "tensor_descriptor.hpp"
#include "tensor_descriptor_helper.hpp" #include "tensor_descriptor_helper.hpp"
#include "tensor_space_filling_curve.hpp"
namespace ck { namespace ck {
...@@ -48,11 +49,6 @@ struct ThreadwiseTensorSliceTransfer_v6r3 ...@@ -48,11 +49,6 @@ struct ThreadwiseTensorSliceTransfer_v6r3
using Src2Coord = decltype(make_tensor_coordinate(Src2Desc{}, Index{})); using Src2Coord = decltype(make_tensor_coordinate(Src2Desc{}, Index{}));
using DstCoord = decltype(make_tensor_coordinate(DstDesc{}, Index{})); using DstCoord = decltype(make_tensor_coordinate(DstDesc{}, Index{}));
using Src0CoordStep = decltype(make_tensor_coordinate_step(Src0Desc{}, Index{}));
using Src1CoordStep = decltype(make_tensor_coordinate_step(Src1Desc{}, Index{}));
using Src2CoordStep = decltype(make_tensor_coordinate_step(Src2Desc{}, Index{}));
using DstCoordStep = decltype(make_tensor_coordinate_step(DstDesc{}, Index{}));
static constexpr auto I0 = Number<0>{}; static constexpr auto I0 = Number<0>{};
__device__ constexpr ThreadwiseTensorSliceTransfer_v6r3(const Src0Desc& src0_desc, __device__ constexpr ThreadwiseTensorSliceTransfer_v6r3(const Src0Desc& src0_desc,
...@@ -112,74 +108,14 @@ struct ThreadwiseTensorSliceTransfer_v6r3 ...@@ -112,74 +108,14 @@ struct ThreadwiseTensorSliceTransfer_v6r3
constexpr auto scalar_per_access = generate_sequence( constexpr auto scalar_per_access = generate_sequence(
detail::lambda_scalar_per_access<VectorDim, ScalarPerVector>{}, Number<nDim>{}); detail::lambda_scalar_per_access<VectorDim, ScalarPerVector>{}, Number<nDim>{});
constexpr auto access_lengths = SliceLengths{} / scalar_per_access; using SpaceFillingCurve = SpaceFillingCurve<SliceLengths,
DimAccessOrder,
constexpr auto dim_access_order = DimAccessOrder{}; remove_cv_t<decltype(scalar_per_access)>>;
constexpr auto ordered_access_lengths =
container_reorder_given_new2old(access_lengths, dim_access_order);
auto make_forward_steps = [&](auto desc) {
return generate_tuple(
[&](auto i) {
Index forward_step_idx;
static_for<0, nDim, 1>{}([&](auto j) {
forward_step_idx(j) = (i.value == j.value) ? scalar_per_access[i] : 0;
});
return make_tensor_coordinate_step(desc, forward_step_idx);
},
Number<nDim>{});
};
auto make_backward_steps = [&](auto desc) {
return generate_tuple(
[&](auto i) {
Index backward_step_idx;
static_for<0, nDim, 1>{}([&](auto j) {
backward_step_idx(j) = (i.value == j.value) ? -scalar_per_access[i] : 0;
});
return make_tensor_coordinate_step(desc, backward_step_idx);
},
Number<nDim>{});
};
// make forward steps
const auto src0_forward_steps = make_forward_steps(src0_desc);
const auto src1_forward_steps = make_forward_steps(src1_desc);
const auto src2_forward_steps = make_forward_steps(src2_desc);
const auto dst_forward_steps = make_forward_steps(dst_desc);
// make backward steps
const auto src0_backward_steps = make_backward_steps(src0_desc);
const auto src1_backward_steps = make_backward_steps(src1_desc);
const auto src2_backward_steps = make_backward_steps(src2_desc);
const auto dst_backward_steps = make_backward_steps(dst_desc);
// loop over slice window constexpr auto num_accesses = SpaceFillingCurve::GetNumOfAccess();
static_ford<decltype(ordered_access_lengths)>{}([&](auto ordered_access_idx) {
// judge move forward or move backward
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_idx[I0];
static_for<1, i, 1>{}([&](auto j) {
tmp = tmp * ordered_access_lengths[j] + ordered_access_idx[j];
});
forward_sweep_(i) = tmp % 2 == 0;
});
return forward_sweep_;
}();
// loop over space-filling curve
static_for<0, num_accesses, 1>{}([&](auto idx_1d) {
using src0_vector_type = vector_type_maker_t<Src0Data, ScalarPerVector>; using src0_vector_type = vector_type_maker_t<Src0Data, ScalarPerVector>;
using src0_vector_t = typename src0_vector_type::type; using src0_vector_t = typename src0_vector_type::type;
...@@ -224,72 +160,24 @@ struct ThreadwiseTensorSliceTransfer_v6r3 ...@@ -224,72 +160,24 @@ struct ThreadwiseTensorSliceTransfer_v6r3
const bool is_dst_valid = const bool is_dst_valid =
coordinate_has_valid_offset_assuming_visible_index_is_valid(dst_desc, dst_coord_); coordinate_has_valid_offset_assuming_visible_index_is_valid(dst_desc, dst_coord_);
// copy data from dst_vector into dst_buf dst_buf.template Update<DstInMemOp, dst_vector_t>(
if constexpr(DstInMemOp == InMemoryDataOperationEnum_t::Set) dst_coord_.GetOffset(),
{ is_dst_valid,
dst_buf.template Set<dst_vector_t>( dst_vector_container.template AsType<dst_vector_t>()[I0]);
dst_coord_.GetOffset(),
is_dst_valid,
dst_vector_container.template AsType<dst_vector_t>()[I0]);
}
else if constexpr(DstInMemOp == InMemoryDataOperationEnum_t::AtomicAdd)
{
dst_buf.template AtomicAdd<dst_vector_t>(
dst_coord_.GetOffset(),
is_dst_valid,
dst_vector_container.template AsType<dst_vector_t>()[I0]);
}
constexpr auto move_on_dim = [&]() constexpr // move coordinate
if constexpr(idx_1d.value != num_accesses - 1)
{ {
StaticallyIndexedArray<bool, nDim> move_on_dim_; constexpr auto forward_step = SpaceFillingCurve::GetForwardStep(idx_1d);
move_tensor_coordinate(
static_for<0, nDim, 1>{}([&](auto i) { src0_desc, src0_coord_, make_tensor_coordinate_step(src0_desc, forward_step));
move_on_dim_(i) = ordered_access_idx[i] < ordered_access_lengths[i] - 1; move_tensor_coordinate(
src1_desc, src1_coord_, make_tensor_coordinate_step(src1_desc, forward_step));
static_for<i + 1, nDim, 1>{}([&](auto j) { move_tensor_coordinate(
move_on_dim_(i) &= ordered_access_idx[j] == ordered_access_lengths[j] - 1; src2_desc, src2_coord_, make_tensor_coordinate_step(src1_desc, forward_step));
}); move_tensor_coordinate(
}); dst_desc, dst_coord_, make_tensor_coordinate_step(dst_desc, forward_step));
return move_on_dim_;
} }
();
// move coordinate
static_for<0, nDim, 1>{}([&](auto i) {
if constexpr(move_on_dim[i])
{
if constexpr(forward_sweep[i])
{
move_tensor_coordinate(
src0_desc, src0_coord_, src0_forward_steps[dim_access_order[i]]);
move_tensor_coordinate(
src1_desc, src1_coord_, src1_forward_steps[dim_access_order[i]]);
move_tensor_coordinate(
src2_desc, src2_coord_, src2_forward_steps[dim_access_order[i]]);
move_tensor_coordinate(
dst_desc, dst_coord_, dst_forward_steps[dim_access_order[i]]);
}
else
{
move_tensor_coordinate(
src0_desc, src0_coord_, src0_backward_steps[dim_access_order[i]]);
move_tensor_coordinate(
src1_desc, src1_coord_, src1_backward_steps[dim_access_order[i]]);
move_tensor_coordinate(
src2_desc, src2_coord_, src2_backward_steps[dim_access_order[i]]);
move_tensor_coordinate(
dst_desc, dst_coord_, dst_backward_steps[dim_access_order[i]]);
}
}
});
}); });
// move coordinate back to slice origin (or not) // move coordinate back to slice origin (or not)
...@@ -328,59 +216,18 @@ struct ThreadwiseTensorSliceTransfer_v6r3 ...@@ -328,59 +216,18 @@ struct ThreadwiseTensorSliceTransfer_v6r3
__device__ static constexpr auto GetCoordinateResetStep() __device__ static constexpr auto GetCoordinateResetStep()
{ {
// scalar per access on each dim
// TODO: don't use lambda_scalar_per_access
constexpr auto scalar_per_access = generate_sequence( constexpr auto scalar_per_access = generate_sequence(
detail::lambda_scalar_per_access<VectorDim, ScalarPerVector>{}, Number<nDim>{}); detail::lambda_scalar_per_access<VectorDim, ScalarPerVector>{}, Number<nDim>{});
constexpr auto access_lengths = SliceLengths{} / scalar_per_access; using SpaceFillingCurve = SpaceFillingCurve<SliceLengths,
DimAccessOrder,
constexpr auto dim_access_order = DimAccessOrder{}; remove_cv_t<decltype(scalar_per_access)>>;
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 data index after last iteration in Run(), if it has not being reset
constexpr auto 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) *
scalar_per_access;
}();
//
constexpr auto reset_data_step = [&]() {
Index reset_data_step_;
static_for<0, nDim, 1>{}([&](auto i) { reset_data_step_(i) = -data_idx[i]; });
return reset_data_step_; constexpr auto num_accesses = SpaceFillingCurve::GetNumOfAccess();
}(); constexpr auto reset_step =
SpaceFillingCurve::GetStepBetween(Number<num_accesses - 1>{}, Number<0>{});
return reset_data_step; return reset_step;
} }
// src_slice_origin_step_idx need to be known at compile-time, for performance reason // src_slice_origin_step_idx need to be known at compile-time, for performance reason
......
composable_kernel/include/tensor_operation/threadwise_tensor_slice_transfer_v6r3_sfcurve.hpp deleted 100644 → 0
View file @ d5d3788f
#ifndef CK_THREADWISE_TENSOR_SLICE_TRANSFER_V6R3_SPCURVE_HPP
#define CK_THREADWISE_TENSOR_SLICE_TRANSFER_V6R3_SPCURVE_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
// Assume:
// 1. src0_desc and dst_desc are not known at compile-time
// 2. SrcBuffer and DstBuffer are DynamicBuffer
// 3. src_slice_origin and dst_slice_origin are not known at compile-time,
template <typename Src0Data,
typename Src1Data,
typename Src2Data,
typename DstData,
typename Src0Desc,
typename Src1Desc,
typename Src2Desc,
typename DstDesc,
typename ElementwiseOperation,
typename SliceLengths,
typename DimAccessOrder,
index_t VectorDim,
index_t ScalarPerVector,
InMemoryDataOperationEnum_t DstInMemOp,
bool Src0ResetCoordinateAfterRun,
bool Src1ResetCoordinateAfterRun,
bool Src2ResetCoordinateAfterRun,
bool DstResetCoordinateAfterRun>
struct ThreadwiseTensorSliceTransfer_v6r3
{
static constexpr index_t nDim = SliceLengths::Size();
using Index = MultiIndex<nDim>;
using Src0Coord = decltype(make_tensor_coordinate(Src0Desc{}, Index{}));
using Src1Coord = decltype(make_tensor_coordinate(Src1Desc{}, Index{}));
using Src2Coord = decltype(make_tensor_coordinate(Src2Desc{}, Index{}));
using DstCoord = decltype(make_tensor_coordinate(DstDesc{}, Index{}));
static constexpr auto I0 = Number<0>{};
__device__ constexpr ThreadwiseTensorSliceTransfer_v6r3(const Src0Desc& src0_desc,
const Index& src0_slice_origin,
const Src1Desc& src1_desc,
const Index& src1_slice_origin,
const Src2Desc& src2_desc,
const Index& src2_slice_origin,
const DstDesc& dst_desc,
const Index& dst_slice_origin,
const ElementwiseOperation& element_op)
: src0_coord_(make_tensor_coordinate(src0_desc, src0_slice_origin)),
src1_coord_(make_tensor_coordinate(src1_desc, src1_slice_origin)),
src2_coord_(make_tensor_coordinate(src2_desc, src2_slice_origin)),
dst_coord_(make_tensor_coordinate(dst_desc, dst_slice_origin)),
element_op_(element_op)
{
static_assert(SliceLengths::At(Number<VectorDim>{}) % ScalarPerVector == 0,
"wrong! cannot evenly divide");
}
__device__ void SetSrc0SliceOrigin(const Src0Desc& src0_desc,
const Index& src0_slice_origin_idx)
{
src0_coord_ = make_tensor_coordinate(src0_desc, src0_slice_origin_idx);
}
__device__ void SetSrc1SliceOrigin(const Src1Desc& src1_desc,
const Index& src1_slice_origin_idx)
{
src1_coord_ = make_tensor_coordinate(src1_desc, src1_slice_origin_idx);
}
__device__ void SetSrc2SliceOrigin(const Src2Desc& src2_desc,
const Index& src2_slice_origin_idx)
{
src2_coord_ = make_tensor_coordinate(src2_desc, src2_slice_origin_idx);
}
__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 Src0Buffer, typename Src1Buffer, typename Src2Buffer, typename DstBuffer>
__device__ void Run(const Src0Desc& src0_desc,
const Src0Buffer& src0_buf,
const Src1Desc& src1_desc,
const Src1Buffer& src1_buf,
const Src2Desc& src2_desc,
const Src2Buffer& src2_buf,
const DstDesc& dst_desc,
DstBuffer& dst_buf)
{
// scalar per access on each dim
// TODO: don't use lambda_scalar_per_access
constexpr auto scalar_per_access = generate_sequence(
detail::lambda_scalar_per_access<VectorDim, ScalarPerVector>{}, Number<nDim>{});
using SpaceFillingCurve = SpaceFillingCurve<SliceLengths,
DimAccessOrder,
remove_cv_t<decltype(scalar_per_access)>>;
constexpr auto num_accesses = SpaceFillingCurve::GetNumOfAccess();
// loop over space-filling curve
static_for<0, num_accesses, 1>{}([&](auto idx_1d) {
using src0_vector_type = vector_type_maker_t<Src0Data, ScalarPerVector>;
using src0_vector_t = typename src0_vector_type::type;
using src1_vector_type = vector_type_maker_t<Src1Data, ScalarPerVector>;
using src1_vector_t = typename src1_vector_type::type;
using src2_vector_type = vector_type_maker_t<Src2Data, ScalarPerVector>;
using src2_vector_t = typename src2_vector_type::type;
using dst_vector_type = vector_type_maker_t<DstData, ScalarPerVector>;
using dst_vector_t = typename dst_vector_type::type;
const bool is_src0_valid =
coordinate_has_valid_offset_assuming_visible_index_is_valid(src0_desc, src0_coord_);
const bool is_src1_valid =
coordinate_has_valid_offset_assuming_visible_index_is_valid(src1_desc, src1_coord_);
const bool is_src2_valid =
coordinate_has_valid_offset_assuming_visible_index_is_valid(src2_desc, src2_coord_);
// copy data from src0_buf into src0_vector_container
auto src0_vector_container = src0_vector_type{
src0_buf.template Get<src0_vector_t>(src0_coord_.GetOffset(), is_src0_valid)};
auto src1_vector_container = src1_vector_type{
src1_buf.template Get<src1_vector_t>(src1_coord_.GetOffset(), is_src1_valid)};
auto src2_vector_container = src2_vector_type{
src2_buf.template Get<src2_vector_t>(src2_coord_.GetOffset(), is_src2_valid)};
auto dst_vector_container = dst_vector_type{};
// apply pointwise operation
static_for<0, ScalarPerVector, 1>{}([&](auto i) {
element_op_(dst_vector_container.template AsType<DstData>()(i),
src0_vector_container.template AsType<Src0Data>()[i],
src1_vector_container.template AsType<Src1Data>()[i],
src2_vector_container.template AsType<Src2Data>()[i]);
});
const bool is_dst_valid =
coordinate_has_valid_offset_assuming_visible_index_is_valid(dst_desc, dst_coord_);
dst_buf.template Transfer<DstInMemOp, dst_vector_t>(
dst_coord_.GetOffset(),
is_dst_valid,
dst_vector_container.template AsType<dst_vector_t>()[I0]);
// move coordinate
if constexpr(idx_1d.value != num_accesses - 1)
{
constexpr auto forward_step = SpaceFillingCurve::GetForwardStep(idx_1d);
move_tensor_coordinate(
src0_desc, src0_coord_, make_tensor_coordinate_step(src0_desc, forward_step));
move_tensor_coordinate(
src1_desc, src1_coord_, make_tensor_coordinate_step(src1_desc, forward_step));
move_tensor_coordinate(
src2_desc, src2_coord_, make_tensor_coordinate_step(src1_desc, forward_step));
move_tensor_coordinate(
dst_desc, dst_coord_, make_tensor_coordinate_step(dst_desc, forward_step));
}
});
// move coordinate back to slice origin (or not)
if constexpr(Src0ResetCoordinateAfterRun)
{
const auto src0_reset_step =
make_tensor_coordinate_step(src0_desc, GetCoordinateResetStep());
move_tensor_coordinate(src0_desc, src0_coord_, src0_reset_step);
}
if constexpr(Src1ResetCoordinateAfterRun)
{
const auto src1_reset_step =
make_tensor_coordinate_step(src1_desc, GetCoordinateResetStep());
move_tensor_coordinate(src1_desc, src1_coord_, src1_reset_step);
}
if constexpr(Src2ResetCoordinateAfterRun)
{
const auto src2_reset_step =
make_tensor_coordinate_step(src2_desc, GetCoordinateResetStep());
move_tensor_coordinate(src2_desc, src2_coord_, src2_reset_step);
}
if constexpr(DstResetCoordinateAfterRun)
{
const auto dst_reset_step =
make_tensor_coordinate_step(dst_desc, GetCoordinateResetStep());
move_tensor_coordinate(dst_desc, dst_coord_, dst_reset_step);
}
}
__device__ static constexpr auto GetCoordinateResetStep()
{
constexpr auto scalar_per_access = generate_sequence(
detail::lambda_scalar_per_access<VectorDim, ScalarPerVector>{}, Number<nDim>{});
using SpaceFillingCurve = SpaceFillingCurve<SliceLengths,
DimAccessOrder,
remove_cv_t<decltype(scalar_per_access)>>;
constexpr auto num_accesses = SpaceFillingCurve::GetNumOfAccess();
constexpr auto reset_step =
SpaceFillingCurve::GetStepBetween(Number<num_accesses - 1>{}, Number<0>{});
return reset_step;
}
// src_slice_origin_step_idx need to be known at compile-time, for performance reason
__device__ void MoveSrc0SliceWindow(const Src0Desc& src0_desc,
const Index& src0_slice_origin_step_idx)
{
// if src coord was not reset by RunRead(), then need to adjust the step here
const auto adjusted_step_idx = Src0ResetCoordinateAfterRun
? src0_slice_origin_step_idx
: src0_slice_origin_step_idx + GetCoordinateResetStep();
// is it OK to construct a new step every time?
const auto adjusted_step = make_tensor_coordinate_step(src0_desc, adjusted_step_idx);
move_tensor_coordinate(src0_desc, src0_coord_, adjusted_step);
}
// src_slice_origin_step_idx need to be known at compile-time, for performance reason
__device__ void MoveSrc1SliceWindow(const Src1Desc& src1_desc,
const Index& src1_slice_origin_step_idx)
{
// if src coord was not reset by RunRead(), then need to adjust the step here
const auto adjusted_step_idx = Src1ResetCoordinateAfterRun
? src1_slice_origin_step_idx
: src1_slice_origin_step_idx + GetCoordinateResetStep();
// is it OK to construct a new step every time?
const auto adjusted_step = make_tensor_coordinate_step(src1_desc, adjusted_step_idx);
move_tensor_coordinate(src1_desc, src1_coord_, adjusted_step);
}
// src_slice_origin_step_idx need to be known at compile-time, for performance reason
__device__ void MoveSrc2SliceWindow(const Src2Desc& src2_desc,
const Index& src2_slice_origin_step_idx)
{
// if src coord was not reset by RunRead(), then need to adjust the step here
const auto adjusted_step_idx = Src2ResetCoordinateAfterRun
? src2_slice_origin_step_idx
: src2_slice_origin_step_idx + GetCoordinateResetStep();
// is it OK to construct a new step every time?
const auto adjusted_step = make_tensor_coordinate_step(src2_desc, adjusted_step_idx);
move_tensor_coordinate(src2_desc, src2_coord_, adjusted_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 + GetCoordinateResetStep();
// 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:
Src0Coord src0_coord_;
Src1Coord src1_coord_;
Src2Coord src2_coord_;
DstCoord dst_coord_;
const ElementwiseOperation element_op_;
};
} // namespace ck
#endif
composable_kernel/include/utility/dynamic_buffer.hpp
View file @ b0ebfb40
...@@ -114,7 +114,7 @@ struct DynamicBuffer ...@@ -114,7 +114,7 @@ struct DynamicBuffer
typename enable_if<is_same<typename scalar_type<remove_cvref_t<X>>::type, typename enable_if<is_same<typename scalar_type<remove_cvref_t<X>>::type,
typename scalar_type<remove_cvref_t<T>>::type>::value, typename scalar_type<remove_cvref_t<T>>::type>::value,
bool>::type = false> bool>::type = false>
__host__ __device__ void Transfer(index_t i, bool is_valid_element, const X& x) __host__ __device__ void Update(index_t i, bool is_valid_element, const X& x)
{ {
if constexpr(Op == InMemoryDataOperationEnum_t::Set) if constexpr(Op == InMemoryDataOperationEnum_t::Set)
{ {
......
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