在CentOS上实现Fortran并行计算主要有两种方法:使用OpenMP进行多核并行计算,以及使用MPI进行分布式并行计算。以下是具体实现方式:
OpenMP是一种支持多平台共享内存并行编程的API。通过使用OpenMP,可以在Fortran程序中方便地实现多核并行计算。以下是一个简单的OpenMP示例:
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))
allocate(result(n))
! 初始化数组
array = 1.0
! 设置并行区域
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
! 验证结果
if (all(result == 2.0)) then
print *, "Parallel computation successful."
else
print *, "Error in parallel computation."
end if
deallocate(array)
deallocate(result)
end program openmp_example
MPI(Message Passing Interface)是一种用于分布式内存系统并行计算的标准。以下是一个简单的MPI示例:
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
! 每个进程计算部分和
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
使用gfortran和ifort编译器:
gfortran -fopenmp -o openmp_example openmp_example.f90
mpif90 -o mpi_example mpi_example.f90
运行命令:
./openmp_example
mpirun -np <core-count> ./mpi_example
通过上述方法,可以在CentOS上利用Fortran进行并行计算,从而提高计算效率和性能。