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Flatten subprojects into a single base monorepo
2026-09-02 16:34:47 -07:00

260 lines
11 KiB
C++

// Copyright (C) 2024 - 2026 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 "../../shared/accuracy_test.h"
#include "../../shared/fft_enums.h"
#include "../../shared/params_gen.h"
#include "../hipfft_params.h"
#include <algorithm>
#include <gtest/gtest.h>
#include <hip/hip_runtime_api.h>
#include <optional>
extern fft_params::fft_mp_lib mp_lib;
extern int mp_ranks;
static const std::vector<std::vector<size_t>> multi_gpu_sizes = {
{128, 256},
{192, 768},
{64, 128, 256},
{96, 160, 192},
};
static const std::vector<size_t> multi_gpu_batch_range = {4, 1};
static std::vector<std::vector<size_t>> ioffset_range_zero = {{0, 0}};
static std::vector<std::vector<size_t>> ooffset_range_zero = {{0, 0}};
enum SplitType
{
// split both input and output on slow FFT dimension
SLOW_INOUT,
// split only input on slow FFT dimension, output is not split
SLOW_IN,
// split only output on slow FFT dimension, input is not split
SLOW_OUT,
// split input on slow FFT dimension, and output on fast FFT dimension
SLOW_IN_FAST_OUT,
// 3D pencil decomposition - one dimension is contiguous on input
// and another dimension contiguous on output, remaining dims are
// both split
PENCIL_3D,
};
std::vector<fft_params> param_generator_multi_gpu(const std::optional<SplitType> type,
fft_auto_allocation auto_alloc_setting
= fft_auto_allocation_default)
{
int localDeviceCount = 0;
(void)hipGetDeviceCount(&localDeviceCount);
// if we have an explicit split of data on the user side, we need
// to use the multiprocessing API
if(type)
{
if(mp_lib == fft_params::fft_mp_lib_none)
return {};
}
// data is not explicitly split up, that means the library is
// asked to do the split. We need multiple GPUs to do this.
else if(localDeviceCount < 2)
return {};
static const std::vector<std::vector<size_t>> stride_range = {{1}};
// gather cases to test as single-device params, then distribute
// to multiple GPUs
std::vector<fft_params> params_single;
// function pointer callbacks need -fgpu-rdc, but that causes build
// nondeterminism in kpack
auto multi_device_callbacks = {fft_callback_type_none, /*fft_callback_type_funcptr, */};
{
auto params = param_generator_complex(test_prob,
multi_gpu_sizes,
precision_range_sp_dp,
multi_gpu_batch_range,
stride_generator(stride_range),
stride_generator(stride_range),
ioffset_range_zero,
ooffset_range_zero,
{fft_placement_inplace, fft_placement_notinplace},
false,
multi_device_callbacks,
auto_alloc_setting);
std::copy(params.begin(), params.end(), std::back_inserter(params_single));
params = param_generator_real(test_prob,
multi_gpu_sizes,
precision_range_sp_dp,
multi_gpu_batch_range,
stride_generator(stride_range),
stride_generator(stride_range),
ioffset_range_zero,
ooffset_range_zero,
{fft_placement_notinplace},
false,
multi_device_callbacks,
auto_alloc_setting);
std::copy(params.begin(), params.end(), std::back_inserter(params_single));
}
std::vector<fft_params> all_params;
auto distribute_params = [=, &all_params](const std::vector<fft_params>& params) {
for(auto& p : params)
{
// test library splitting
if(!type)
{
auto param_multi = p;
// for single-batch, cuFFT only allows in-place
if(p.nbatch == 1 && p.placement == fft_placement_notinplace)
continue;
param_multi.multiGPU = std::min(static_cast<int>(p.nbatch), localDeviceCount);
all_params.emplace_back(std::move(param_multi));
}
else
{
// the API only allows for batch-1 multi-process FFTs
if(p.nbatch > 1)
continue;
// user-specified split
int brickCount = mp_ranks;
// start with all-ones in grids
std::vector<unsigned int> input_grid(p.length.size() + 1, 1);
std::vector<unsigned int> output_grid(p.length.size() + 1, 1);
auto p_dist = p;
switch(*type)
{
case SLOW_INOUT:
input_grid[1] = brickCount;
output_grid[1] = brickCount;
break;
case SLOW_IN:
// this type only specifies input field and no output
// field, but multi-process transforms require both
// fields.
if(mp_lib != fft_params::fft_mp_lib_none)
continue;
input_grid[1] = brickCount;
break;
case SLOW_OUT:
// this type only specifies output field and no input
// field, but multi-process transforms require both
// fields.
if(mp_lib != fft_params::fft_mp_lib_none)
continue;
output_grid[1] = brickCount;
break;
case SLOW_IN_FAST_OUT:
// requires at least rank-2 FFT
if(p.length.size() < 2)
continue;
input_grid[1] = brickCount;
output_grid.back() = brickCount;
break;
case PENCIL_3D:
// need at least 2 bricks per split dimension, or 4 devices.
// also needs to be a 3D problem.
if(brickCount < 4 || p.length.size() != 3)
continue;
// make fast dimension contiguous on input
input_grid[1] = static_cast<unsigned int>(sqrt(brickCount));
input_grid[2] = brickCount / input_grid[1];
// make middle dimension contiguous on output
output_grid[1] = input_grid[1];
output_grid[3] = input_grid[2];
break;
}
p_dist.mp_lib = mp_lib;
p_dist.distribute_field<fft_io::fft_io_in>(localDeviceCount, input_grid);
p_dist.distribute_field<fft_io::fft_io_out>(localDeviceCount, output_grid);
// "placement" flag is meaningless if exactly one of
// input+output is a field. So just add those cases if
// the flag is "out-of-place", since "in-place" is
// exactly the same test case.
if(p_dist.placement == fft_placement_inplace
&& p_dist.ifields.empty() != p_dist.ofields.empty())
continue;
// in-place transforms require identical input/output layouts
if(p.placement == fft_placement_inplace && input_grid != output_grid)
continue;
all_params.push_back(std::move(p_dist));
}
}
};
distribute_params(params_single);
return all_params;
}
// split both input and output on slowest FFT dim
INSTANTIATE_TEST_SUITE_P(multi_gpu_slowest_dim,
accuracy_test,
::testing::ValuesIn(param_generator_multi_gpu(SLOW_INOUT)),
accuracy_test::TestName);
// split slowest FFT dim only on input, or only on output
INSTANTIATE_TEST_SUITE_P(multi_gpu_slowest_input_dim,
accuracy_test,
::testing::ValuesIn(param_generator_multi_gpu(SLOW_IN)),
accuracy_test::TestName);
INSTANTIATE_TEST_SUITE_P(multi_gpu_slowest_output_dim,
accuracy_test,
::testing::ValuesIn(param_generator_multi_gpu(SLOW_OUT)),
accuracy_test::TestName);
// split input on slowest FFT and output on fastest, to minimize data
// movement (only makes sense for rank-2 and higher FFTs)
INSTANTIATE_TEST_SUITE_P(multi_gpu_slowin_fastout,
accuracy_test,
::testing::ValuesIn(param_generator_multi_gpu(SLOW_IN_FAST_OUT)),
accuracy_test::TestName);
// 3D pencil decompositions
INSTANTIATE_TEST_SUITE_P(multi_gpu_3d_pencils,
accuracy_test,
::testing::ValuesIn(param_generator_multi_gpu(PENCIL_3D)),
accuracy_test::TestName);
// library-decided splits
INSTANTIATE_TEST_SUITE_P(multi_gpu,
accuracy_test,
::testing::ValuesIn(param_generator_multi_gpu({})),
accuracy_test::TestName);
// Note: disabled for now due to implementation issues and
// unimplemented features in hipFFT (to fix first)
INSTANTIATE_TEST_SUITE_P(DISABLED_various_multi_gpu,
accuracy_test,
::testing::ValuesIn(param_generator_multi_gpu({},
fft_auto_allocation_off)),
accuracy_test::TestName);