我正在 Fortran 90 中制作一个模块以在给定矩阵上运行 PARPACK。我有一个现有的 ARPACK 代码，它按预期正常运行。我尝试将其转换为 PARPACK 并遇到内存清除错误。我对编码和fortran相当陌生，请原谅我犯的任何错误。
编码：
!ARPACK module
module parpack
implicit none
contains
subroutine parp
! use mpi
include '/usr/lib/x86_64-linux-gnu/openmpi/include/mpif.h'
integer comm, myid, nprocs, rc, nloc, status(MPI_STATUS_SIZE)
integer, parameter :: pres=8
integer nev, ncv, maxn, maxnev, maxncv
parameter (maxn=10**7, maxnev=maxn-1, maxncv=maxn)
! Arrays for SNAUPD
integer iparam(11), ipntr(14)
logical, allocatable :: select(:)
real(kind=pres), allocatable :: workd(:), workl(:), worktmp1(:), worktmp2(:)
! Scalars for SNAUPD
character bmat*1, which*2
integer ido, n, info, ierr, ldv
integer i, j, ishfts, maxitr, mode1, nconv
integer(kind=pres) lworkl
real(kind=pres) tol
! Arrays for SNEUPD
real(kind=pres), allocatable :: d(:,:), resid(:), v(:,:), workev(:), z(:,:)
! Scalars for SNEUPD
logical rvec, first
real sigmar, sigmai
!==============================================
real(kind=pres), allocatable :: mat(:,:)
open (11, file = 'matrix.dat', status = 'old')
read (11,*) n
!=============================================
! Dimension of the problem
nev = n/10
ncv = nev+2
ldv = n
bmat = 'I'
which = 'LM'
! Additional environment variables
ido = 0
tol = 0.0E+0
info = 0
lworkl = 3*ncv**2+6*ncv
! Algorithm Mode specifications:
ishfts = 1
maxitr = 300
mode1 = 1
iparam(1) = ishfts
iparam(3) = maxitr
iparam(7) = mode1
! Distribution to nodes
!=============================================
! Matrix allocation
allocate (mat(n,n))
! PDNAUPD
allocate (workd(5*n))
allocate (workl(lworkl))
allocate (resid(n))
allocate (worktmp1(n))
allocate (worktmp2(n))
! PDNEUPD
allocate (d(n,3))
allocate (v(ldv,ncv))
allocate (workev(3*n))
allocate (z(ldv,ncv))
allocate (select(ncv))
!===========================================
! Read Matrix from the provided file
mat = 0
read(11,*) mat
mat = transpose(mat)
!===========================================
! MPI Calling
call MPI_INIT(ierr)
comm = MPI_COMM_WORLD
call MPI_COMM_RANK(comm, myid, ierr)
call MPI_COMM_SIZE(comm, nprocs, ierr)
nloc = n/nprocs
! if ( mod(n, nprocs) .gt. myid ) nloc = nloc + n
!===============================================
20 continue
call pdnaupd(comm, ido, bmat, nloc, which, nev, tol, resid, ncv, v, ldv, iparam, ipntr, workd, workl, lworkl, info) !Top level solver
call MPI_BARRIER(comm,ierr)
print *, ido, info, iparam(5) !for testing
!===============================================
if (ido .eq. -1 .or. ido .eq. 1) then
worktmp1 = 0
if (myid .ne. 0) then !It is slave
call MPI_SEND(workd(ipntr(1)), nloc, MPI_DOUBLE_PRECISION, 0, 0, comm, ierr)
else !It is host
worktmp1(1:nloc) = workd(ipntr(1):ipntr(1)+nloc-1)
i = nprocs
if (i .gt. 1) then
do i=1,nprocs-1
call MPI_RECV(worktmp1(i*nloc+1), nloc, MPI_DOUBLE_PRECISION, i, 0, comm, status, ierr)
end do
endif
endif
call MPI_BARRIER(comm,ierr)
if (myid .eq. 0) then !It is host
! Matrix multiplication
worktmp2 = 0
call matmultiply(n, mat, worktmp1, worktmp2)
workd(ipntr(2):ipntr(2)+nloc-1) = worktmp2(1:nloc)
i = nprocs
if (i .gt. 1) then
do i=1,nprocs-1
call MPI_SEND(worktmp2(i*nloc+1), nloc, MPI_DOUBLE_PRECISION, i, 100*i, comm, ierr)
end do
endif
else !It is slave
call MPI_RECV(workd(ipntr(2)), nloc, MPI_DOUBLE_PRECISION, 0, 100*myid, comm, status, ierr)
endif
go to 20
! call matmultiply(n, mat, workd(ipntr(1):ipntr(1)+n-1), workd(ipntr(2):ipntr(2)+n-1))
! go to 20
endif
! print *, info !for testing
!===============================================================
! Post-processing for eigenvalues
rvec = .true.
if (myid .eq. 0) then
call pdneupd ( comm, rvec, 'A', select, d, d(1,2), z, ldv, sigmar, sigmai, &
workev, bmat, n, which, nev, tol, resid, ncv, v, ldv, iparam, ipntr, &
workd, workl, lworkl, info)
endif
! print *, info !for testing
close(11)
call MPI_FINALIZE(ierr)
return
end subroutine
!==============================================================================================
! Additional Function definitions
subroutine matmultiply(n, mat, v, w)
integer n, i, j
integer, parameter :: pres=8
real(kind = pres) mat(n,n), temp(n)
real(kind = pres) v(n), w(n)
temp = 0
do j = 1,n
do i = 1,n
temp(j) = temp(j) + mat(i,j)*v(i)
end do
end do
w = temp
return
end subroutine
end module
对于大量多余的行和评论，我深表歉意，我还没有清理它以完成最终确定。
当我在单个线程上运行代码时./a.out，我得到以下输出：
Invalid MIT-MAGIC-COOKIE-1 key 1 0 1629760560
1 0 1629760560
1 0 1629760560
1 0 1629760560
.
.
. <A long chain as the code is exhausting all iterations>
.<first of the numbers is ido, which starts with 1 instead of -1 for some reason, second being
.info and third being iparam(5) which is a random number until the final iteration>
.
99 1 1
munmap_chunk(): invalid pointer
Program received signal SIGABRT: Process abort signal.
Backtrace for this error:
#0 0x7f5a863d0d01 in ???
#1 0x7f5a863cfed5 in ???
#2 0x7f5a8620420f in ???
#3 0x7f5a8620418b in ???
#4 0x7f5a861e3858 in ???
#5 0x7f5a8624e3ed in ???
#6 0x7f5a8625647b in ???
#7 0x7f5a862566cb in ???
#8 0x560f05ac1819 in ???
#9 0x560f05abd7bc in checker
at /home/srivatsank/Desktop/fortran/lap_vs_arp/ptest/ptest.f90:45
#10 0x560f05abd8d9 in main
at /home/srivatsank/Desktop/fortran/lap_vs_arp/ptest/ptest.f90:3
Aborted (core dumped)
第45行ptest是call parp
第3行ptest是use parpack(name of the module)
主要代码如下：
program checker
use parpack
use arpack
! use lapack
implicit none
!Program to test LAPACK and ARPACK
! 1. Variable definition
integer a,n,i
real, allocatable :: mat(:,:)
real t0, t1
a=2
! Loop
! do 20 a = 1,3
! Open File
open(unit=10, file = 'matrix.dat', status = 'replace')
! 2. Generate Symmetric matrices
n = 10**a
allocate (mat(n,n))
call RANDOM_NUMBER(mat)
! 3. Save symmetric matrices to r.dat
write (10,*) n
do 30 i=1,n
write(10,*) mat(i,:)
30 end do
deallocate(mat)
close(10)
! 4. Test time taken by each of the routines
! call cpu_time(t0)
! call arp
! call cpu_time(t1)
! print *, 'n:', n, 'ARPACK time taken:', t1-t0
call cpu_time(t0)
call parp
call cpu_time(t1)
print *, 'n:', n, 'PARPACK time taken:', t1-t0
!20 end do
end program checker
当邮件程序试图退出子程序时，内存错误发生在子程序的最后。我已经通过将语句打印为子例程的最后一行来验证这一点。并且在运行mpirun -np 4 a.out时，代码只是进入 pdneupd 进程并永远坐在那里。有人可以帮忙吗？