在CentOS下實現Fortran并行計算,通常有兩種主要方法:使用OpenMP進行多線程并行計算,以及使用MPI進行分布式內存并行計算。以下是具體實現步驟和示例代碼:
OpenMP是一種支持多平臺共享內存并行編程的API。以下是一個簡單的OpenMP示例,展示如何在Fortran中使用OpenMP進行并行計算:
program openmp_example
use omp_lib
implicit none
integer :: i, n
real, allocatable :: array(:), result(:)
integer :: num_threads, thread_id
n = 1000000
allocate(array(n), result(n))
! 初始化數組
array = 1.0
! 設置并行區域
num_threads = omp_get_max_threads()
print *, "Using", num_threads, "threads for parallel computation."
!omp parallel do private(thread_id, i)
do i = 1, n
thread_id = omp_get_thread_num()
result(i) = array(i) * 2.0
end do
!omp end parallel do
! 驗證結果
if (all(result == 2.0)) then
print *, "Parallel computation successful."
else
print *, "Error in parallel computation."
end if
deallocate(array, result)
end program openmp_example
MPI是一種用于分布式內存系統并行計算的標準。以下是一個簡單的MPI示例,展示如何在Fortran中使用MPI進行并行計算:
program mpi_example
use mpi
implicit none
integer :: ierr, rank, size, n, i
real, allocatable :: array(:), local_sum, global_sum
integer, parameter :: root = 0
call MPI_Init(ierr)
call MPI_Comm_rank(MPI_COMM_WORLD, rank, ierr)
call MPI_Comm_size(MPI_COMM_WORLD, size, ierr)
n = 1000000 / size
allocate(array(n))
array = real(rank) * 1.0
! 每個進程計算部分和
local_sum = 0.0
do i = 1, n
local_sum = local_sum + array(i)
end do
! 所有部分和相加得到全局和
call MPI_Reduce(local_sum, global_sum, 1, MPI_REAL, MPI_SUM, root, MPI_COMM_WORLD, ierr)
if (rank == root) then
print *, "Global sum:", global_sum
end if
deallocate(array)
call MPI_Finalize(ierr)
end program mpi_example
gfortran -fopenmp -o openmp_example openmp_example.f90
./openmp_example
mpif90 -o mpi_example mpi_example.f90
mpirun -np <core-count> ./mpi_example
通過上述步驟和示例代碼,您可以在CentOS系統下使用Fortran實現并行計算。根據具體需求選擇OpenMP或MPI,并進行相應的編譯和運行。