MPI process

An MPI process is process of a computer program that is being executed by one or many threads and employs an implementation of the Message Passing Interface (MPI) to communicate its data with the other processes.

An example is the commonly used program OpenMPI.

In practice, the number of MPI processes on each each node is related to the number of threads you want for each MPI process. Multiplied together, we suggest that the values should equal the total number of cores in a node.

See also

• Overview of various hardware and software components

• Threading

• Example Slurm script

After allocation of resources on which one wants to run the MPI processes, you also may want to export environment variables related the implementation of the multiprocessing API.

Table 1 OpenMPI settings

Keyword arguments	Description
--enable-mpi-threads	Enable thread support in OpenMPI
--map-by socket/node	map MPI processes to socket/node
--bind-to socket/node	bind MPI processes to socket/node
--report-bindings	report bindings of launched processes
--display-allocation	display detected allocation

See also

For general details on pinning options in OpenMPI see the HPC wiki article. The Slurm documentation contains additional options for running MPI.

In addition, you can consider the number of virtual processes (Number of MPI processes x number of threads) you are using.

Number of MPI processes x threads/core	Description
Is less than number of cores	Resources may be underutilized.
Is equal to the number of cores	Resources are fully utilized (recommended for NEST)
Is greater than the number of cores	Resources are oversubscribed

In the first two scenarios, the simulation may show better performance because it will not be slowed by processes interfering with eachother (e.g., virtual memory thrashing).

Over-subscribing processes is typically used in development in testing and can help identify performance bottlenecks. But performance can be degraded in this scenario.