I am working on an Fortan code that already uses MPI.
Now, I am facing a situation, where a set of data grows very large but is same for every process, so I would prefer to store it in memory only once per node and all processes on one node access the same data.
Storing it once for every process would go beyond the available RAM.
Is it somehow possible to achieve something like that with openMP?
Data sharing per node is the only thing I would like to have, no other per node paralellisation required, because this is already done via MPI.
You don't need to implement a hybrid MPI+OpenMP code if it is only for sharing a chunk of data. What you actually have to do is:
1) Split the world communicator into groups that span the same host/node. That is really easy if your MPI library implements MPI-3.0 - all you need to do is call MPI_COMM_SPLIT_TYPE
with split_type
set to MPI_COMM_TYPE_SHARED
:
USE mpi_f08
TYPE(MPI_Comm) :: hostcomm
CALL MPI_Comm_split_type(MPI_COMM_WORLD, MPI_COMM_TYPE_SHARED, 0, &
MPI_INFO_NULL, hostcomm)
MPI-2.2 or earlier does not provide the MPI_COMM_SPLIT_TYPE
operation and one has to get somewhat creative. You could for example use my simple split-by-host implementation that can be found on Github here.
2) Now that processes that reside on the same node are part of the same communicator hostcomm
, they can create a block of shared memory and use it to exchange data. Again, MPI-3.0 provides an (relatively) easy and portable way to do that:
USE mpi_f08
USE, INTRINSIC :: ISO_C_BINDING, ONLY : C_PTR, C_F_POINTER
INTEGER :: hostrank
INTEGER(KIND=MPI_ADDRESS_KIND) :: size
INTEGER :: disp_unit
TYPE(C_PTR) :: baseptr
TYPE(MPI_Win) :: win
TYPE(MY_DATA_TYPE), POINTER :: shared_data
! We only want one process per host to allocate memory
! Set size to 0 in all processes but one
CALL MPI_Comm_rank(hostcomm, hostrank)
if (hostrank == 0) then
size = 10000000 ! Put the actual data size here
else
size = 0
end if
disp_unit = 1
CALL MPI_Win_allocate_shared(size, disp_unit, MPI_INFO_NULL, &
hostcomm, baseptr, win)
! Obtain the location of the memory segment
if (hostrank /= 0) then
CALL MPI_Win_shared_query(win, 0, size, disp_unit, baseptr)
end if
! baseptr can now be associated with a Fortran pointer
! and thus used to access the shared data
CALL C_F_POINTER(baseptr, shared_data)
! Use shared_data as if it was ALLOCATE'd
! ...
! Destroy the shared memory window
CALL MPI_Win_free(win)
The way that code works is that it uses the MPI-3.0 functionality for allocating shared memory windows. MPI_WIN_ALLOCATE_SHARED
allocates a chunk of shared memory in each process. Since you want to share one block of data, it only makes sense to allocate it in a single process and not have it spread across the processes, therefore size
is set to 0 for all but one ranks while making the call. MPI_WIN_SHARED_QUERY
is used to find out the address at which that shared memory block is mapped in the virtual address space of the calling process. One the address is known, the C pointer can be associated with a Fortran pointer using the C_F_POINTER()
subroutine and the latter can be used to access the shared memory. Once done, the shared memory has to be freed by destroying the shared memory window with MPI_WIN_FREE
.
MPI-2.2 or earlier does not provide shared memory windows. In that case one has to use the OS-dependent APIs for creation of shared memory blocks, e.g. the standard POSIX sequence shm_open()
/ ftruncate()
/ mmap()
. A utility C function callable from Fortran has to be written in order to perform those operations. See that code for some inspiration. The void *
returned by mmap()
can be passed directly to the Fortran code in a C_PTR
type variable that can be then associated with a Fortran pointer.
With this answer I want to add a complete running code example (for ifort 15 and mvapich 2.1). The MPI shared memory concept is still pretty new and in particular for Fortran there aren't many code examples out there. It is based on the answer from Hristo and a very useful email on the mvapich mailing list (http://mailman.cse.ohio-state.edu/pipermail/mvapich-discuss/2014-June/005003.html).
The code example is based on the problems I ran into and adds to Hristo's answer in the following ways:
Kudos go to Hristo and Michael Rachner.
program sharedmemtest
USE, INTRINSIC :: ISO_C_BINDING, ONLY : C_PTR, C_F_POINTER
use mpi
implicit none
integer, parameter :: dp = selected_real_kind(14,200)
integer :: win,win2,hostcomm,hostrank
INTEGER(KIND=MPI_ADDRESS_KIND) :: windowsize
INTEGER :: disp_unit,my_rank,ierr,total
TYPE(C_PTR) :: baseptr,baseptr2
real(dp), POINTER :: matrix_elementsy(:,:,:,:)
integer,allocatable :: arrayshape(:)
call MPI_INIT( ierr )
call MPI_COMM_RANK(MPI_COMM_WORLD,MY_RANK,IERR) !GET THE RANK OF ONE PROCESS
call MPI_COMM_SIZE(MPI_COMM_WORLD,Total,IERR) !GET THE TOTAL PROCESSES OF THE COMM
CALL MPI_Comm_split_type(MPI_COMM_WORLD, MPI_COMM_TYPE_SHARED, 0, MPI_INFO_NULL, hostcomm,ierr)
CALL MPI_Comm_rank(hostcomm, hostrank,ierr)
! Gratefully based on: http://stackoverflow.com/questions/24797298/mpi-fortran-code-how-to-share-data-on-node-via-openmp
! and https://gcc.gnu.org/onlinedocs/gfortran/C_005fF_005fPOINTER.html
! We only want one process per host to allocate memory
! Set size to 0 in all processes but one
allocate(arrayshape(4))
arrayshape=(/ 10,10,10,10 /)
if (hostrank == 0) then
windowsize = int(10**4,MPI_ADDRESS_KIND)*8_MPI_ADDRESS_KIND !*8 for double ! Put the actual data size here
else
windowsize = 0_MPI_ADDRESS_KIND
end if
disp_unit = 1
CALL MPI_Win_allocate_shared(windowsize, disp_unit, MPI_INFO_NULL, hostcomm, baseptr, win, ierr)
! Obtain the location of the memory segment
if (hostrank /= 0) then
CALL MPI_Win_shared_query(win, 0, windowsize, disp_unit, baseptr, ierr)
end if
! baseptr can now be associated with a Fortran pointer
! and thus used to access the shared data
CALL C_F_POINTER(baseptr, matrix_elementsy,arrayshape)
!!! your code here!
!!! sample below
if (hostrank == 0) then
matrix_elementsy=0.0_dp
matrix_elementsy(1,2,3,4)=1.0_dp
end if
CALL MPI_WIN_FENCE(0, win, ierr)
print *,"my_rank=",my_rank,matrix_elementsy(1,2,3,4),matrix_elementsy(1,2,3,5)
!!! end sample code
call MPI_WIN_FENCE(0, win, ierr)
call MPI_BARRIER(MPI_COMM_WORLD,ierr)
call MPI_Win_free(win,ierr)
call MPI_FINALIZE(IERR)
end program
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