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// Copyright (C) 2022-2024 Advanced Micro Devices, Inc. All rights reserved.
//
// Permission is hereby granted, free of charge, to any person obtaining a copy
// of this software and associated documentation files (the "Software"), to deal
// in the Software without restriction, including without limitation the rights
// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
// copies of the Software, and to permit persons to whom the Software is
// furnished to do so, subject to the following conditions:
//
// The above copyright notice and this permission notice shall be included in
// all copies or substantial portions of the Software.
//
// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
// THE SOFTWARE.
#include "rtc_transpose_gen.h"
#include "../../shared/array_predicate.h"
#include "device/generator/generator.h"
#include "rtc_test_harness.h"
#include "device/kernel-generator-embed.h"
// generate name for RTC transpose kernel
std::string transpose_rtc_kernel_name(const TransposeSpecs& specs)
{
std::string kernel_name = "transpose_rtc";
kernel_name += "_tile";
kernel_name += std::to_string(specs.tileX);
kernel_name += "x";
kernel_name += std::to_string(specs.tileY);
// 2D + 3D kernels are specialized to omit loops
switch(specs.dim)
{
case 2:
kernel_name += "_dim2";
break;
case 3:
kernel_name += "_dim3";
break;
default:
break;
}
kernel_name += rtc_precision_name(specs.precision);
kernel_name += rtc_array_type_name(specs.inArrayType);
kernel_name += rtc_array_type_name(specs.outArrayType);
if(specs.largeTwdSteps)
{
kernel_name += "_twd";
kernel_name += std::to_string(specs.largeTwdSteps);
kernel_name += "step";
if(specs.largeTwdDirection == -1)
kernel_name += "_fwd";
else
kernel_name += "_back";
}
if(specs.diagonal)
kernel_name += "_diag";
if(specs.tileAligned)
kernel_name += "_aligned";
kernel_name += load_store_name_suffix(specs.loadOps, specs.storeOps);
kernel_name += rtc_cbtype_name(specs.cbtype);
if(!specs.grid3D)
kernel_name += "_grid1D";
return kernel_name;
}
// generate source for RTC transpose kernel.
std::string transpose_rtc(const std::string& kernel_name, const TransposeSpecs& specs)
{
std::string src;
// includes and declarations
src += rocfft_complex_h;
src += common_h;
src += callback_h;
src += rtc_precision_type_decl(specs.precision, array_type_is_complex(specs.inArrayType));
src += rtc_const_cbtype_decl(specs.cbtype);
// twiddle code assumes scalar type is named T
src += "typedef scalar_type T;\n";
// arguments to transpose kernel
Variable input_var{"input", "scalar_type", true, true};
Variable output_var{"output", "scalar_type", true, true};
Variable twiddles_large_var{"twiddles_large", "const scalar_type", true, true};
Variable dim_var{"dim", "unsigned int"};
Variable length0_var{"length0", "unsigned int"};
Variable length1_var{"length1", "unsigned int"};
Variable length2_var{"length2", "unsigned int"};
Variable lengths_var{"lengths", "const size_t", true, true};
Variable stride_in0_var{"stride_in0", "unsigned int"};
Variable stride_in1_var{"stride_in1", "unsigned int"};
Variable stride_in2_var{"stride_in2", "unsigned int"};
Variable stride_in_var{"stride_in", "const size_t", true, true};
Variable idist_var{"idist", "unsigned int"};
Variable stride_out0_var{"stride_out0", "unsigned int"};
Variable stride_out1_var{"stride_out1", "unsigned int"};
Variable stride_out2_var{"stride_out2", "unsigned int"};
Variable stride_out_var{"stride_out", "const size_t", true, true};
Variable odist_var{"odist", "unsigned int"};
Variable gridX{"gridX", "const unsigned int"};
Variable gridY{"gridY", "const unsigned int"};
Variable gridZ{"gridZ", "const unsigned int"};
Function func(kernel_name);
func.launch_bounds = specs.tileX * specs.tileY;
func.qualifier = "extern \"C\" __global__";
func.arguments.append(input_var);
func.arguments.append(output_var);
func.arguments.append(twiddles_large_var);
func.arguments.append(dim_var);
func.arguments.append(length0_var);
func.arguments.append(length1_var);
func.arguments.append(length2_var);
func.arguments.append(lengths_var);
func.arguments.append(stride_in0_var);
func.arguments.append(stride_in1_var);
func.arguments.append(stride_in2_var);
func.arguments.append(stride_in_var);
func.arguments.append(idist_var);
func.arguments.append(stride_out0_var);
func.arguments.append(stride_out1_var);
func.arguments.append(stride_out2_var);
func.arguments.append(stride_out_var);
func.arguments.append(odist_var);
func.arguments.append(gridX);
func.arguments.append(gridY);
func.arguments.append(gridZ);
for(const auto& arg : get_callback_args().arguments)
func.arguments.append(arg);
// we use tileX*tileX tiles - tileY must evenly divide into
// tileX, so that elems_per_thread is integral
if(specs.tileX % specs.tileY != 0)
throw std::runtime_error("non-integral transpose ELEMS_PER_THREAD");
auto elems_per_thread = specs.tileX / specs.tileY;
if(elems_per_thread == 0)
throw std::runtime_error("zero transpose ELEMS_PER_THREAD");
// lds is a 2D array
Variable lds{"lds", "__shared__ scalar_type", false, false, specs.tileX};
lds.size2D = Literal{specs.tileX};
func.body += Declaration{lds};
// recover a 3D GPU grid layout
func.body += CommentLines{"since gridDim is passed as {gridX, 1, 1}, use the",
"following variables to recover block indices in a 3-D fashion:"};
Variable old_blockIdx_x{"old_blockIdx_x", "unsigned int"};
Variable old_blockIdx_y{"old_blockIdx_y", "unsigned int"};
Variable old_blockIdx_z{"old_blockIdx_z", "unsigned int"};
Variable tileBlockIdx_y{"tileBlockIdx_y", "unsigned int"};
Variable tileBlockIdx_x{"tileBlockIdx_x", "unsigned int"};
Variable remaining{"remaining", "unsigned int"};
// if a 1-D grid was provided because creating a natural 3-D grid exceeded allowed limits, then remap it to a 3-D grid.
if(!specs.grid3D)
{
func.body += Declaration{old_blockIdx_x, Literal{"blockIdx.x"} / (gridY * gridZ)};
func.body += Declaration{remaining, Literal{"blockIdx.x"} % (gridY * gridZ)};
func.body += Declaration{old_blockIdx_y, (remaining / gridZ)};
func.body += Declaration{old_blockIdx_z, Literal{"blockIdx.x"} % gridZ};
func.body += Declaration{tileBlockIdx_y, "old_blockIdx_y"};
func.body += Declaration{tileBlockIdx_x, "old_blockIdx_x"};
}
else
{
func.body += Declaration{tileBlockIdx_y, "blockIdx.y"};
func.body += Declaration{tileBlockIdx_x, "blockIdx.x"};
}
func.body += LineBreak{};
if(specs.diagonal)
{
Variable bid{"bid", "auto"};
if(specs.grid3D)
{
func.body += Declaration{bid, "blockIdx.x + gridDim.x * blockIdx.y"};
func.body += Assign{tileBlockIdx_y, bid % Variable{"gridDim.y", ""}};
func.body += Assign{tileBlockIdx_x,
(bid / Variable{"gridDim.y", ""} + tileBlockIdx_y)
% Variable{"gridDim.x", ""}};
}
else
{
func.body += Declaration{bid, "old_blockIdx_x + gridX * old_blockIdx_y"};
func.body += Assign{tileBlockIdx_y, bid % Variable{"gridY", ""}};
func.body
+= Assign{tileBlockIdx_x,
(bid / Variable{"gridY", ""} + tileBlockIdx_y) % Variable{"gridX", ""}};
}
}
if(specs.dim == 2)
{
func.body += CommentLines{"only using 2 dimensions, pretend length2 is 1 so the",
"compiler can optimize out comparisons against it"};
func.body += Assign{length2_var, 1};
}
Variable tile_x_index{"tile_x_index", "unsigned int"};
Variable tile_y_index{"tile_y_index", "unsigned int"};
func.body += Declaration{tile_x_index, "threadIdx.x"};
func.body += Declaration{tile_y_index, "threadIdx.y"};
func.body += CommentLines{"work out offset for dimensions after the first 3"};
Variable offset_in{"offset_in", "unsigned int"};
Variable offset_out{"offset_out", "unsigned int"};
if(specs.grid3D)
{
func.body += Declaration{remaining, "blockIdx.z"};
}
else
{
func.body += Assign{remaining, "old_blockIdx_z"};
}
func.body += Declaration{offset_in, 0};
func.body += Declaration{offset_out, 0};
// use specified dim to avoid loops if possible
if(specs.dim > 3)
{
Variable d{"d", "unsigned int"};
For offset_loop{
d,
3,
d < dim_var,
1,
};
Variable index_along_d{"index_along_d", "auto"};
offset_loop.body += Declaration{index_along_d, remaining % lengths_var[d]};
offset_loop.body += Assign{remaining, remaining / lengths_var[d]};
offset_loop.body += Assign{offset_in, offset_in + index_along_d * stride_in_var[d]};
offset_loop.body += Assign{offset_out, offset_out + index_along_d * stride_out_var[d]};
func.body += offset_loop;
}
func.body += CommentLines{"remaining is now the batch"};
func.body += AddAssign(offset_in, remaining * idist_var);
func.body += AddAssign(offset_out, remaining * odist_var);
func.body += CallbackLoadDeclaration("scalar_type", "cbtype");
func.body += CallbackStoreDeclaration("scalar_type", "cbtype");
// loop variables for reading/writing
Variable i{"i", "unsigned int"};
Variable logical_row{"logical_row", "auto"};
Variable logical_col{"logical_col", "auto"};
Variable idx0{"idx0", "auto"};
Variable idx1{"idx1", "auto"};
Variable idx2{"idx2", "auto"};
Variable global_read_idx{"global_read_idx", "auto"};
Variable global_write_idx{"global_write_idx", "auto"};
Variable elem{"elem", "scalar_type"};
Variable twl_idx{"twl_idx", "auto"};
For read_loop{i, 0, i < elems_per_thread, 1};
read_loop.pragma_unroll = true;
read_loop.body
+= Declaration{logical_row, specs.tileX * tileBlockIdx_y + tile_y_index + i * specs.tileY};
read_loop.body += Declaration{idx0, specs.tileX * tileBlockIdx_x + tile_x_index};
read_loop.body += Declaration{idx1, logical_row};
if(specs.dim != 2)
read_loop.body += ModulusAssign(idx1, length1_var);
if(specs.dim == 2)
read_loop.body += Declaration{idx2, 0};
else
read_loop.body += Declaration{idx2, logical_row / length1_var};
if(!specs.tileAligned)
{
read_loop.body
+= If{Or{Or{idx0 >= length0_var, idx1 >= length1_var}, idx2 >= length2_var}, {Break{}}};
}
read_loop.body += Declaration{global_read_idx,
idx0 * stride_in0_var + idx1 * stride_in1_var
+ idx2 * stride_in2_var + offset_in};
read_loop.body += Declaration{elem};
read_loop.body += Assign{elem, LoadGlobal{input_var, global_read_idx}};
if(specs.largeTwdSteps)
{
auto twiddle_mul_macro
= specs.largeTwdDirection == -1 ? "TWIDDLE_STEP_MUL_FWD" : "TWIDDLE_STEP_MUL_INV";
std::string twiddle_step_func = "TWLstep" + std::to_string(specs.largeTwdSteps);
read_loop.body += Declaration{twl_idx, idx0 * idx1};
read_loop.body
+= Call{twiddle_mul_macro, {twiddle_step_func, twiddles_large_var, twl_idx, elem}};
}
read_loop.body += Assign{lds.at(tile_x_index, i * specs.tileY + tile_y_index), elem};
func.body += read_loop;
func.body += SyncThreads{};
Variable val{"val", "scalar_type", false, false, elems_per_thread};
func.body += Declaration{val};
func.body += CommentLines{"reallocate threads to write along fastest dim (length1) and",
"read transposed from LDS"};
func.body += Assign{tile_x_index, "threadIdx.y"};
func.body += Assign{tile_y_index, "threadIdx.x"};
For transpose_loop{i,
0,
i < elems_per_thread,
1,
{Assign{val[i], lds.at(tile_x_index + i * specs.tileY, tile_y_index)}}};
transpose_loop.pragma_unroll = true;
func.body += transpose_loop;
For write_loop{i, 0, i < elems_per_thread, 1};
write_loop.pragma_unroll = true;
write_loop.body
+= Declaration{logical_col, specs.tileX * tileBlockIdx_x + tile_x_index + i * specs.tileY};
write_loop.body += Declaration{logical_row, specs.tileX * tileBlockIdx_y + tile_y_index};
write_loop.body += Declaration{idx0, logical_col};
write_loop.body += Declaration{idx1, logical_row};
if(specs.dim != 2)
{
write_loop.body += ModulusAssign(idx1, length1_var);
}
if(specs.dim == 2)
write_loop.body += Declaration{idx2, 0};
else
write_loop.body += Declaration{idx2, logical_row / length1_var};
if(!specs.tileAligned)
{
write_loop.body
+= If{Or{Or{idx0 >= length0_var, idx1 >= length1_var}, idx2 >= length2_var}, {Break{}}};
}
write_loop.body += Declaration{global_write_idx,
idx0 * stride_out0_var + idx1 * stride_out1_var
+ idx2 * stride_out2_var + offset_out};
write_loop.body += StoreGlobal{output_var, global_write_idx, val[i]};
func.body += write_loop;
make_load_store_ops(func, specs.loadOps, specs.storeOps);
if(array_type_is_planar(specs.inArrayType))
func = make_planar(func, "input");
if(array_type_is_planar(specs.outArrayType))
func = make_planar(func, "output");
func = make_callback_realcomplex(func, specs.cbtype);
src += func.render();
write_standalone_test_harness(func, src);
return src;
}
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