Hit send before I finished. If each proc along the axis needs the partial sum (ie proc j gets sum for i = 0 -> j-1 SCAL[j]) then MPI_Scan will do that.
> On May 2, 2018, at 6:29 AM, Nathan Hjelm <hje...@me.com> wrote: > > MPI_Reduce would do this. I would use MPI_Comm_split to make an axis comm > then use reduce with the root being the last rank in the axis comm. > >> On May 2, 2018, at 6:11 AM, John Hearns via users <users@lists.open-mpi.org> >> wrote: >> >> Also my inner voice is shouting that there must be an easy way to express >> this in Julia >> https://discourse.julialang.org/t/apply-reduction-along-specific-axes/3301/16 >> >> OK, these are not the same stepwise cumulative operatiosn that you want, but >> the idea is close. >> >> >> ps. Note to self - stop listening to the voices. >> >> >>> On 2 May 2018 at 14:08, John Hearns <hear...@googlemail.com> wrote: >>> Peter, how large are your models, ie how many cells in each direction? >>> Something inside of me is shouting that if the models are small enough then >>> MPI is not the way here. >>> Assuming use of a Xeon processor there should be some AVX instructions >>> which can do this. >>> >>> This is rather out of date, but is it helpful? >>> ttps://www.quora.com/Is-there-an-SIMD-architecture-that-supports-horizontal-cumulative-sum-Prefix-sum-as-a-single-instruction >>> >>> https://software.intel.com/sites/landingpage/IntrinsicsGuide/ >>> >>> >>>> On 2 May 2018 at 13:56, 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 >>>> _______________________________________________ >>>> users mailing list >>>> users@lists.open-mpi.org >>>> https://lists.open-mpi.org/mailman/listinfo/users >>> >> >> _______________________________________________ >> users mailing list >> users@lists.open-mpi.org >> https://lists.open-mpi.org/mailman/listinfo/users
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