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psyrk.cu
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psyrk.cu
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/*
* Copyright 2023 NVIDIA Corporation. All rights reserved.
*
* NOTICE TO LICENSEE:
*
* This source code and/or documentation ("Licensed Deliverables") are
* subject to NVIDIA intellectual property rights under U.S. and
* international Copyright laws.
*
* These Licensed Deliverables contained herein is PROPRIETARY and
* CONFIDENTIAL to NVIDIA and is being provided under the terms and
* conditions of a form of NVIDIA software license agreement by and
* between NVIDIA and Licensee ("License Agreement") or electronically
* accepted by Licensee. Notwithstanding any terms or conditions to
* the contrary in the License Agreement, reproduction or disclosure
* of the Licensed Deliverables to any third party without the express
* written consent of NVIDIA is prohibited.
*
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
* LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
* SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE. IT IS
* PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
* NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
* DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
* NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
* LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
* SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
* DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
* WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
* ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
* OF THESE LICENSED DELIVERABLES.
*
* U.S. Government End Users. These Licensed Deliverables are a
* "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
* 1995), consisting of "commercial computer software" and "commercial
* computer software documentation" as such terms are used in 48
* C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
* only as a commercial end item. Consistent with 48 C.F.R.12.212 and
* 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
* U.S. Government End Users acquire the Licensed Deliverables with
* only those rights set forth herein.
*
* Any use of the Licensed Deliverables in individual and commercial
* software must include, in the user documentation and internal
* comments to the code, the above Disclaimer and U.S. Government End
* Users Notice.
*/
#include <assert.h>
#include <math.h>
#include <mpi.h>
#include <omp.h>
#include <stdio.h>
#include <stdlib.h>
#include <time.h>
#include <vector>
#ifdef USE_CAL_MPI
#include <cal_mpi.h>
#endif
#include <cublasmp.h>
#include "helpers.h"
#include "matrix_generator.hxx"
int main(int argc, char* argv[])
{
Options opts = { .m = 10,
.n = 10,
.k = 10,
.mbA = 2,
.nbA = 2,
.mbB = 2,
.nbB = 2,
.mbC = 2,
.nbC = 2,
.ia = 3,
.ja = 3,
.ib = 3,
.jb = 1,
.ic = 1,
.jc = 1,
.p = 2,
.q = 1,
.grid_layout = 'c',
.verbose = false };
opts.parse(argc, argv);
opts.validate();
opts.print();
MPI_Init(nullptr, nullptr);
const int64_t n = opts.n;
const int64_t k = opts.k;
const int64_t ia = opts.ia;
const int64_t ja = opts.ja;
const int64_t ic = opts.ic;
const int64_t jc = opts.jc;
const int64_t mbA = opts.mbA;
const int64_t nbA = opts.nbA;
const int64_t mbC = opts.mbC;
const int64_t nbC = opts.nbC;
const int nprow = opts.p;
const int npcol = opts.q;
int rank, nranks;
MPI_Comm_size(MPI_COMM_WORLD, &nranks);
MPI_Comm_rank(MPI_COMM_WORLD, &rank);
const int myprow = (opts.grid_layout == 'c' ? rank % nprow : rank / npcol);
const int mypcol = (opts.grid_layout == 'c' ? rank / nprow : rank % npcol);
const int local_device = getLocalDevice();
CUDA_CHECK(cudaSetDevice(local_device));
CUDA_CHECK(cudaFree(nullptr));
cal_comm_t cal_comm = nullptr;
#ifdef USE_CAL_MPI
CAL_CHECK(cal_comm_create_mpi(MPI_COMM_WORLD, rank, nranks, local_device, &cal_comm));
#else
cal_comm_create_params_t params;
params.allgather = allgather;
params.req_test = request_test;
params.req_free = request_free;
params.data = (void*)(MPI_COMM_WORLD);
params.rank = rank;
params.nranks = nranks;
params.local_device = local_device;
CAL_CHECK(cal_comm_create(params, &cal_comm));
#endif
cudaStream_t stream = nullptr;
CUDA_CHECK(cudaStreamCreate(&stream));
cublasMpHandle_t handle = nullptr;
CUBLASMP_CHECK(cublasMpCreate(&handle, stream));
cublasMpGrid_t grid = nullptr;
cublasMpMatrixDescriptor_t descA = nullptr;
cublasMpMatrixDescriptor_t descC = nullptr;
double* d_A = nullptr;
double* d_C = nullptr;
double* d_work = nullptr;
double alpha = 1.0;
double beta = 1.0;
size_t workspaceInBytesOnDevice = 0;
size_t workspaceInBytesOnHost = 0;
const int64_t global_m_a = (ia - 1) + n;
const int64_t global_n_a = (ja - 1) + k;
const int64_t global_m_c = (ic - 1) + n;
const int64_t global_n_c = (jc - 1) + n;
const int64_t llda = cublasMpNumroc(global_m_a, mbA, myprow, 0, nprow);
const int64_t loc_n_a = cublasMpNumroc(global_n_a, nbA, mypcol, 0, npcol);
const int64_t lldc = cublasMpNumroc(global_m_c, mbC, myprow, 0, nprow);
const int64_t loc_n_c = cublasMpNumroc(global_n_c, nbC, mypcol, 0, npcol);
std::vector<double> h_A(llda * loc_n_a, 0);
std::vector<double> h_C(lldc * loc_n_c, 0);
generate_random_matrix(n, k, h_A.data(), mbA, nbA, ia, ja, llda, nprow, npcol, myprow, mypcol);
generate_random_matrix(n, n, h_C.data(), mbC, nbC, ic, jc, lldc, nprow, npcol, myprow, mypcol);
CUDA_CHECK(cudaMallocAsync(&d_A, llda * loc_n_a * sizeof(double), stream));
CUDA_CHECK(cudaMallocAsync(&d_C, lldc * loc_n_c * sizeof(double), stream));
CUDA_CHECK(cudaMemcpyAsync(d_A, h_A.data(), llda * loc_n_a * sizeof(double), cudaMemcpyHostToDevice, stream));
CUDA_CHECK(cudaMemcpyAsync(d_C, h_C.data(), lldc * loc_n_c * sizeof(double), cudaMemcpyHostToDevice, stream));
CUBLASMP_CHECK(cublasMpGridCreate(
nprow,
npcol,
opts.grid_layout == 'c' ? CUBLASMP_GRID_LAYOUT_COL_MAJOR : CUBLASMP_GRID_LAYOUT_ROW_MAJOR,
cal_comm,
&grid));
CUBLASMP_CHECK(
cublasMpMatrixDescriptorCreate(global_m_a, global_n_a, mbA, nbA, 0, 0, llda, CUDA_R_64F, grid, &descA));
CUBLASMP_CHECK(
cublasMpMatrixDescriptorCreate(global_m_c, global_n_c, mbC, nbC, 0, 0, lldc, CUDA_R_64F, grid, &descC));
CUBLASMP_CHECK(cublasMpSyrk_bufferSize(
handle,
CUBLAS_FILL_MODE_LOWER,
CUBLAS_OP_N,
n,
k,
&alpha,
d_A,
ia,
ja,
descA,
&beta,
d_C,
ic,
jc,
descC,
CUBLAS_COMPUTE_64F,
&workspaceInBytesOnDevice,
&workspaceInBytesOnHost));
CUDA_CHECK(cudaMallocAsync(&d_work, workspaceInBytesOnDevice, stream));
std::vector<int8_t> h_work(workspaceInBytesOnHost);
CAL_CHECK(cal_stream_sync(cal_comm, stream));
CAL_CHECK(cal_comm_barrier(cal_comm, stream));
const double begin = MPI_Wtime();
CUBLASMP_CHECK(cublasMpSyrk(
handle,
CUBLAS_FILL_MODE_LOWER,
CUBLAS_OP_N,
n,
k,
&alpha,
d_A,
ia,
ja,
descA,
&beta,
d_C,
ic,
jc,
descC,
CUBLAS_COMPUTE_64F,
d_work,
workspaceInBytesOnDevice,
h_work.data(),
workspaceInBytesOnHost));
CAL_CHECK(cal_stream_sync(cal_comm, stream));
CAL_CHECK(cal_comm_barrier(cal_comm, stream));
const double end = MPI_Wtime();
if (rank == 0)
{
printf("Duration: %lf GFlops: %lf\n", end - begin, (n * n * k * 1e-9) / (end - begin));
}
CUBLASMP_CHECK(cublasMpMatrixDescriptorDestroy(descA));
CUBLASMP_CHECK(cublasMpMatrixDescriptorDestroy(descC));
CUBLASMP_CHECK(cublasMpGridDestroy(grid));
CUBLASMP_CHECK(cublasMpDestroy(handle));
CUDA_CHECK(cudaFreeAsync(d_A, stream));
CUDA_CHECK(cudaFreeAsync(d_C, stream));
CUDA_CHECK(cudaFreeAsync(d_work, stream));
CAL_CHECK(cal_comm_barrier(cal_comm, stream));
CAL_CHECK(cal_comm_destroy(cal_comm));
CUDA_CHECK(cudaStreamDestroy(stream));
MPI_Barrier(MPI_COMM_WORLD);
MPI_Finalize();
if (rank == 0)
{
printf("[SUCCEEDED]\n");
}
return 0;
};