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MPI and Julia parallel constructs together

In order for MPI calls to be made from a Julia cluster, it requires the use of MPIManager, a cluster manager that will start the julia workers using mpirun

It has three modes of operation

  • Only worker processes execute MPI code. The Julia master process executes outside of and is not part of the MPI cluster. Free bi-directional TCP/IP connectivity is required between all processes

  • All processes (including Julia master) are part of both the MPI as well as Julia cluster. Free bi-directional TCP/IP connectivity is required between all processes.

  • All processes are part of both the MPI as well as Julia cluster. MPI is used as the transport for julia messages. This is useful on environments which do not allow TCP/IP connectivity between worker processes Note: This capability works with Julia 1.0, 1.1 and 1.2 and releases after 1.4.2. It is broken for Julia 1.3, 1.4.0, and 1.4.1.

MPIManager: only workers execute MPI code

An example is provided in examples/juliacman.jl. The julia master process is NOT part of the MPI cluster. The main script should be launched directly, MPIManager internally calls mpirun to launch julia/MPI workers. All the workers started via MPIManager will be part of the MPI cluster.

MPIManager(;np=Sys.CPU_THREADS, mpi_cmd=false, launch_timeout=60.0)

If not specified, mpi_cmd defaults to mpirun -np $np stdout from the launched workers is redirected back to the julia session calling addprocs via a TCP connection. Thus the workers must be able to freely connect via TCP to the host session. The following lines will be typically required on the julia master process to support both julia and MPI:

# to import MPIManager
using MPIClusterManagers

# need to also import Distributed to use addprocs()
using Distributed

# specify, number of mpi workers, launch cmd, etc.

# start mpi workers and add them as julia workers too.

To execute code with MPI calls on all workers, use @mpi_do.

@mpi_do manager expr executes expr on all processes that are part of manager.

For example:

@mpi_do manager begin
  using MPI
  println("Hello world, I am $(MPI.Comm_rank(comm)) of $(MPI.Comm_size(comm))")

executes on all MPI workers belonging to manager only

examples/juliacman.jl is a simple example of calling MPI functions on all workers interspersed with Julia parallel methods.

This should be run without mpirun:

julia juliacman.jl

A single instation of MPIManager can be used only once to launch MPI workers (via addprocs). To create multiple sets of MPI clusters, use separate, distinct MPIManager objects.

procs(manager::MPIManager) returns a list of julia pids belonging to manager mpiprocs(manager::MPIManager) returns a list of MPI ranks belonging to manager

Fields j2mpi and mpi2j of MPIManager are associative collections mapping julia pids to MPI ranks and vice-versa.

MPIManager: TCP/IP transport - all processes execute MPI code

Useful on environments which do not allow TCP connections outside of the cluster

An example is in examples/cman-transport.jl:

mpirun -np 5 julia cman-transport.jl TCP

This launches a total of 5 processes, mpi rank 0 is the julia pid 1. mpi rank 1 is julia pid 2 and so on.

The program must call MPIClusterManagers.start_main_loop(TCP_TRANSPORT_ALL) with argument TCP_TRANSPORT_ALL. On mpi rank 0, it returns a manager which can be used with @mpi_do On other processes (i.e., the workers) the function does not return

MPIManager: MPI transport - all processes execute MPI code

MPIClusterManagers.start_main_loop must be called with option MPI_TRANSPORT_ALL to use MPI as transport.

mpirun -np 5 julia cman-transport.jl MPI

will run the example using MPI as transport.

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