在CentOS中进行Fortran程序的分布式计算,通常有两种主要的方法: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。以下是一个简单的Fortran程序示例,展示了如何使用OpenMP对循环进行并行化:
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."
! OpenMP并行 do
!$omp parallel do private(thread_id, i) shared(num_threads)
do i = 1, n
thread_id = omp_get_thread_num()
result(i) = array(i) * 2.0
end do
!$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
编译和运行使用OpenMP的程序:
gfortran -fopenmp -o openmp_example openmp_example.f90
./openmp_example
MPI(Message Passing Interface)是一种用于分布式内存系统的并行编程接口,常用于大规模并行计算。以下是一个简单的Fortran程序示例,展示了如何使用MPI进行数组求和:
program mpi_sum
use mpi
implicit none
integer :: ierr, rank, size, i, n, local_n
real, allocatable :: a(:), local_a(:)
real :: local_sum, total_sum
call MPI_Init(ierr)
call MPI_Comm_rank(MPI_COMM_WORLD, rank, ierr)
call MPI_Comm_size(MPI_COMM_WORLD, size, ierr)
n = 1000000
local_n = n / size
allocate(local_a(local_n))
if (rank == 0) allocate(a(n))
! 初始化数组
if (rank == 0) then
do i = 1, n
a(i) = real(i)
end do
end if
! 分发数据
call MPI_Scatter(a, local_n, MPI_REAL, local_a, local_n, MPI_REAL, 0, MPI_COMM_WORLD, ierr)
! 计算局部和
local_sum = sum(local_a)
! 汇总结果
call MPI_Reduce(local_sum, total_sum, 1, MPI_REAL, MPI_SUM, 0, MPI_COMM_WORLD, ierr)
if (rank == 0) then
print *, 'Total sum:' , total_sum
end if
call MPI_Finalize(ierr)
if (rank == 0) deallocate(a)
deallocate(local_a)
end program mpi_sum
编译和运行使用MPI的程序:
mpif90 -o mpi_sum mpi_sum.f90
mpirun -np 4 ./mpi_sum
请注意,具体的安装步骤和命令可能会因CentOS版本和具体需求而有所不同。建议参考最新的官方文档或教程以获取最准确的信息。