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    <p>So determining the right IO strategy depends on a lot of factors. If you are just sending back a handful of eigenvalues, and you're stuck writing out ASCII, you might be best off just sending all the data back to process 0 to write. This is <em>not</em> normally a winning strategy, as it obviously doesn't scale; but if the amount of data is very small, it could well be better than the contention involved in trying to write out to a shared file (which is, again, harder with ASCII). </p> <p>Some code is below which will schlep the amount of data back to proc 0, assuming everyone has the same amount of data.</p> <p>Another approach would just be to have everyone write out their own ks and eigenvalues, and then as a postprocessing step once the program is finished, cat them all together. That avoids the MPI step, and (with the right filesystem) can scale up quite a ways, and is easy; whether that's better is fairly easily testable, and will depend on the amount of data, number of processors, and underlying file system.</p> <pre><code> program testio use mpi implicit none integer, parameter :: atom_count = 5 integer, parameter :: kpertask = 2 integer, parameter :: fileunit = 7 integer, parameter :: io_master = 0 double precision, parameter :: pi = 3.14159 integer :: totalk integer :: ierr integer :: rank, nprocs integer :: handle integer(kind=MPI_OFFSET_KIND) :: offset integer :: filetype integer :: j,k double precision, dimension(atom_count, kpertask) :: eigenvalues double precision, dimension(kpertask) :: ks double precision, allocatable, dimension(:,:):: alleigenvals double precision, allocatable, dimension(:) :: allks call MPI_INIT(ierr) call MPI_COMM_SIZE(MPI_COMM_WORLD, nprocs, ierr) call MPI_COMM_RANK(MPI_COMM_WORLD, rank, ierr) totalk = nprocs*kpertask !! setup test data do k=1,kpertask ks(k) = (rank*kpertask+k)*1.d-4*PI do j=1,atom_count eigenvalues(j,k) = rank*100+j enddo enddo !! Everyone sends proc 0 their data if (rank == 0) then allocate(allks(totalk)) allocate(alleigenvals(atom_count, totalk)) endif call MPI_GATHER(ks, kpertask, MPI_DOUBLE_PRECISION, &amp; allks, kpertask, MPI_DOUBLE_PRECISION, &amp; io_master, MPI_COMM_WORLD, ierr) call MPI_GATHER(eigenvalues, kpertask*atom_count, MPI_DOUBLE_PRECISION, &amp; alleigenvals, kpertask*atom_count, MPI_DOUBLE_PRECISION, &amp; io_master, MPI_COMM_WORLD, ierr) if (rank == 0) then open(unit=fileunit, file='output.txt') do k=1,totalk WRITE(fileunit, *) allks(k), (alleigenvals(j,k), j = 1, atom_count) enddo close(unit=fileunit) deallocate(allks) deallocate(alleigenvals) endif call MPI_FINALIZE(ierr) end program testio </code></pre>
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    1. USJonathan Dursi
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    1. COThanks for the example. I guess I didn't mention, this is in a loop of K (0 to 1000) and EIGENVALUES can have a lot of elements (500 is normal), so every iteration of the loop EIGENVALUES are lost - so sending them back isn't feasible. However, saving to different files on different processors is possible, and might help as an easy solution for now :)
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      1. USRichard Taylor
    2. COI went for a separate file for each process, and stitching them together. I have to keep the formatting for gnuplot, so it seems using MPI to write directly would be a pain. This works good for now, thanks
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