This seems to be crying out for MPI_Reduce.

Also in the previous solution given, I think you should do the MPI_Sends
first.  Doing the MPI_Receives first forces serialization.

Regards,
Charles

On Wed, May 2, 2018 at 7:56 AM, Peter Kjellström <c...@nsc.liu.se> wrote:

> On Wed, 2 May 2018 11:15:09 +0200
> Pierre Gubernatis <pierre.guberna...@gmail.com> wrote:
>
> > Hello all...
> >
> > I am using a *cartesian grid* of processors which represents a spatial
> > domain (a cubic geometrical domain split into several smaller
> > cubes...), and I have communicators to address the procs, as for
> > example a comm along each of the 3 axes I,J,K, or along a plane
> > IK,JK,IJ, etc..).
> >
> > *I need to cumulate a scalar value (SCAL) through the procs which
> > belong to a given axis* (let's say the K axis, defined by I=J=0).
> >
> > Precisely, the origin proc 0-0-0 has a given value for SCAL (say
> > SCAL000). I need to update the 'following' proc (0-0-1) by doing SCAL
> > = SCAL + SCAL000, and I need to *propagate* this updating along the K
> > axis. At the end, the last proc of the axis should have the total sum
> > of SCAL over the axis. (and of course, at a given rank k along the
> > axis, the SCAL value = sum over 0,1,   K of SCAL)
> >
> > Please, do you see a way to do this ? I have tried many things (with
> > MPI_SENDRECV and by looping over the procs of the axis, but I get
> > deadlocks that prove I don't handle this correctly...)
> > Thank you in any case.
>
> Why did you try SENDRECV? As far as I understand your description above
> data only flows one direction (along K)?
>
> There is no MPI collective to support the kind of reduction you
> describe but it should not be hard to do using normal SEND and RECV.
> Something like (simplified psuedo code):
>
> if (not_first_along_K)
>  MPI_RECV(SCAL_tmp, previous)
>  SCAL += SCAL_tmp
>
> if (not_last_along_K)
>  MPI_SEND(SCAL, next)
>
> /Peter K
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