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Home/ Questions/Q 9160337
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Editorial Team
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Editorial Team
Asked: June 17, 20262026-06-17T13:42:54+00:00 2026-06-17T13:42:54+00:00

I think this question is irrelavant to ask here. But could n’t help myself.

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I think this question is irrelavant to ask here. But could n’t help myself.
Suppose I have a cluster with 100 nodes with each node having 16 cores.
I have an mpi application whose communication pattern is already known and I also know the cluster topology(i.e hop distance between nodes).
Now I know the processes to node mapping that reduces the contention on the network. For example: process to node mappings are 10->20,30->90.
How do I map the process with rank 10 to the node-20?
Please help me in this.

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1 Answer

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  1. Editorial Team
    Editorial Team
    2026-06-17T13:42:56+00:00Added an answer on June 17, 2026 at 1:42 pm

    If you are not constrained with any kind of a queueing system you can control the rank to node mapping by creating your own machinefile.

    For instance if the file my_machine_file has the following 1600 lines

       node001
       node002
       node003
       ....
       node100
       node001
       node002
       node003
       ....
       node100
       ...
       [repeat 13 more times]
       ...
       node001
       node002
       node003
       ....
       node100
    

    it would correspond to the mapping

      0-> node001, 1 -> node002, ... 99 -> node100, 100 -> node001, ...
    

    you should run your application with

      mpirun -machinefile my_machine_file -n 1600 my_app
    

    When your application needs less than 1600 processes you can edit your machinefile accordingly.

    Please remember though that the cluster admin has probably numbered the nodes respecting the topology of the interconnect. Yet there are reports of sensible increase (order of 10%-20%) in performance through careful exploitation of the cluster topology. (References to follow).

    Note: Starting an MPI program with mpirun is neither standardized nor portable. However here the question is clearly related to a specific compute cluster and a specific implementation (OpenMPI) and does not request a portable solution.

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