Usage

MPI is based on a single program, multiple data (SPMD) model, where multiple processes are launched running independent programs, which then communicate as necessary via messages.

A script should include using MPI and MPI.Init() statements, for example

# examples/01-hello.jl
using MPI
MPI.Init()

comm = MPI.COMM_WORLD
println("Hello world, I am $(MPI.Comm_rank(comm)) of $(MPI.Comm_size(comm))")
MPI.Barrier(comm)

The program can then be launched via an MPI launch command (typically mpiexec, mpirun or srun), e.g.

$ mpiexec -n 3 julia --project examples/01-hello.jl
Hello world, I am rank 0 of 3
Hello world, I am rank 2 of 3
Hello world, I am rank 1 of 3

CUDA-aware MPI support

If your MPI implementation has been compiled with CUDA support, then CuArrays (from the CuArrays.jl package) can be passed directly as send and receive buffers for point-to-point and collective operations (they may also work with one-sided operations, but these are not often supported).

Finalizers

In order to ensure MPI routines are called in the correct order at finalization time, MPI.jl maintains a reference count. If you define an object that needs to call an MPI routine during its finalization, you should call MPI.refcount_inc() when it is initialized, and MPI.refcount_dec() in its finalizer (after the relevant MPI call).

For example

mutable struct MyObject
    ...
    function MyObject(args...)
        obj = new(args...)
        # MPI call to create object
        refcount_inc()
        finalizer(obj) do x
            # MPI call to free object
            refcount_dec()
        end
        return obj
    end
end