在CentOS下使用Fortran进行分布式计算,通常有两种主要方法:使用OpenMP进行多线程并行计算,以及使用MPI进行分布式内存并行计算。以下是具体实现步骤和示例代码:
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OpenMP示例,展示如何在Fortran中使用OpenMP进行并行计算:
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))
! 初始化数组 array
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, result)
end program openmp_example
编译与运行:
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并行计算的标准。以下是一个简单的MPI示例,展示如何在Fortran中使用MPI进行并行计算:
program mpi_example
use mpi
implicit none
integer :: ierr, rank, size, n, i
real :: local_sum, global_sum
real, allocatable :: array(:)
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(rank + 1) = 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, 0, MPI_COMM_WORLD, ierr)
if (rank == 0) then
print *, 'Global sum:', global_sum
end if
deallocate(array)
call MPI_Finalize(ierr)
end program mpi_example
编译与运行:
mpif90 -o mpi_example mpi_example.f90
mpirun -np 4 ./mpi_example
通过上述方法,可以在CentOS上利用Fortran实现高效的并行计算,从而显著提升科学计算和工程应用的性能。