Is this an average runtime over multiple runs?

On Nov 13, 2019, at 1:40 PM, Douglas Dommermuth via discuss <[email protected]> wrote:

Hi Giuseppe,

It took 163.1s for this case:

mpirun.mpich -bind-to user:0+1 -n 64 myprog & mpirun.mpich -bind-to user:64+1 -n 64 myprog & mpirun.mpich -bind-to user:128+1 -n 64 myprog & mpirun.mpich -bind-to user:192+1 -n 64 myprog &

Thanks, Doug. ________________________________________ From: Congiu, Giuseppe <[email protected]> Sent: Wednesday, November 13, 2019 11:10 AM To: [email protected] Cc: Douglas Dommermuth Subject: Re: [mpich-discuss] Optimizing runtime for 4 mpiexec.hydra jobs

Try binding all the ranks of a job to the same numa. See if something like this works better:

mpirun.mpich -bind-to user:0+1 -n 64 myprog & mpirun.mpich -bind-to user:64+1 -n 64 myprog & mpirun.mpich -bind-to user:128+1 -n 64 myprog & mpirun.mpich -bind-to user:192+1 -n 64 myprog &

However this might not solve completely the problem as MPI processes can still move around across different cores in the numa.

—Giuseppe

...

On Nov 13, 2019, at 1:00 PM, Douglas Dommermuth via discuss <[email protected]> wrote:

Hi Giuseppe and Joachim,

I will look into turning off hyperthreading and running two jobs with a corresponding change in the sizes of the jobs. Meanwhile, I ran the following case, which took 159.6s:

mpirun.mpich -bind-to user:0+4 -n 64 myprog & mpirun.mpich -bind-to user:1+4 -n 64 myprog & mpirun.mpich -bind-to user:2+4 -n 64 myprog & mpirun.mpich -bind-to user:3+4 -n 64 myprog &

Thank you, Doug. ________________________________________ From: Joachim Protze <[email protected]> Sent: Wednesday, November 13, 2019 9:56 AM To: [email protected] Cc: Douglas Dommermuth Subject: Re: [mpich-discuss] Optimizing runtime for 4 mpiexec.hydra jobs

Hi Doug,

in general, using hyperthreads only improves execution time, if you do not utilize the core with a single process/thread. I.e., if you see ~100% cpu utilization per process in "top" for the single job execution, doubling the execution time from 2 to 4 mpi jobs sounds reasonable. If your application is mostly calculating (as an MPI application hopefully does), the two processes/threads running on the same core share the execution time of the core and will finally end up with double execution time.

Depending on your application, additional processes/threads also might increase the pressure on the memory bus and therefore slow down the other application by making it wait for memory accesses. This might also explain the execution time increase from one to two mpi jobs. All this depends on the cpu/memory configuration of this machine.

Best Joachim

On 11/13/19 5:39 PM, Douglas Dommermuth via discuss wrote:

...

I am running Ubuntu 18.04.3 with MPICH 3.3~a2-4 and GFortran 4:7.4.0-1ubuntu2.3 and GCC 4:7.4.0-1ubuntu2.3CC on dual AMD EPYC 7742 processors with hyper threading enabled. My codes are written in MPI and Fortran. The dual AMD processors have 128 cores and 256 threads. I want to optimize the runtime for 4 mpi jobs running concurrently with 64 threads each. Some timings are provided here:

1. One mpi job with mpiexec.hydra -n 64 myprog => 57.32s 2. One mpi job with mpiexec.hydra -bind-to numa -n 64 => 50.52s 3. Two mpi jobs with mpiexec.hydra -n 64 myprog => 99.77s 4. Two mpi jobs with mpiexec.hydra -bind-to numa -n 64 => 72.23s 5. Four mpi jobs with mpiexec.hydra -bind-to numa -n 64 => 159.2s

The option "-bind-to numa" helps, but even so, running four mpi jobs concurrently with 64 threads each is considerably slower than running one mpi job with 64 threads. I can almost run four mpi jobs sequentially and match the time for running four mpi jobs concurrently. How can I improve on the result for running 4 mpi jobs concurrently? Thanks, Doug.

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-- Dipl.-Inf. Joachim Protze

IT Center Group: High Performance Computing Division: Computational Science and Engineering RWTH Aachen University Seffenter Weg 23 D 52074 Aachen (Germany) Tel: +49 241 80- 24765 Fax: +49 241 80-624765 [email protected] www.itc.rwth-aachen.de

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