[mpich-discuss] MPI_Allreduce is slow for 7 processes or more

[Junchao Zhang]

I don't see you measure MPI_Allreduce. Basically you only measured some
random numbers across processes.
See osu_allreduce in OSU microbenchmark (
http://mvapich.cse.ohio-state.edu/benchmarks/)  for a MPI_Allreduce
benchmark.

--Junchao Zhang

On Mon, May 4, 2015 at 2:35 AM, David Froger <david.froger.ml at mailoo.org>
wrote:

> Hello,
>
> I've written a little MPI_Allreduce benchmarks [0].
>
> The results with MPICH 1.4.1 [1] and Open MPI 1.8.4 [2] (1 column for the
> number of processors, and 1 columns for the corresponding wall clock time)
> show
> that clock time is half with twice processors.
>
> But with `MPICH 3.1.4`, the wall clock time increase for 7, 8 or more
> processes [3].
>
> In my real code and for all of the 3 above MPI implementation, I observe
> the
> same problem for 7, 8 or more processes, while I expect my code to be
> scallable
> to at least 8 or 16 processes.
>
> So I'm trying to understand what could happen with the little benchmark and
> MPICH 3.1.4?
>
> Thanks for reading.
>
> Best regards,
> David
>
> [0]
> https://github.com/dfroger/issue/blob/8b8bdd8e4b2b5e265c25fc2ba7077f6a108bb34a/mpi/bench_mpi.cxx
> [1]
> https://github.com/dfroger/issue/blob/8b8bdd8e4b2b5e265c25fc2ba7077f6a108bb34a/mpi/carla/conda-default.mpich2.1.4.1p1.txt
> [2]
> https://github.com/dfroger/issue/blob/8b8bdd8e4b2b5e265c25fc2ba7077f6a108bb34a/mpi/carla/conda-mpi4py-channel.openmpi.1.8.4.txt
> [3]
> https://github.com/dfroger/issue/blob/8b8bdd8e4b2b5e265c25fc2ba7077f6a108bb34a/mpi/carla/conda-mpi4py-channel.mpich.3.1.4.txt
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