Julia + MPI¶

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MPI.jl provides wrappers for the system MPI libraries. And the MPIClusterManagers.jl package lets you control MPI workflows within Julia

In [1]:
# to import MPIManager
using MPIClusterManagers

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

# specify, number of mpi workers, launch cmd, etc.
manager=MPIManager(np=4)

# start mpi workers and add them as julia workers too.
addprocs(manager)
Out[1]:
4-element Vector{Int64}:
 2
 3
 4
 5
In [2]:
@mpi_do manager begin
    using MPI: MPI, Comm, Win, free
    comm = MPI.COMM_WORLD
    rank = MPI.Comm_rank(comm)
    size = MPI.Comm_size(comm)
    println("Hello world, I am $(rank) of $(size)")
end

      From worker 3:	Hello world, I am 1 of 4
      From worker 5:	Hello world, I am 3 of 4
      From worker 2:	Hello world, I am 0 of 4
      From worker 4:	Hello world, I am 2 of 4
In [3]:
@mpi_do manager begin
    using SharedArrays
    a = SharedArray{Int64}(4)
end
In [4]:
@mpi_do manager begin
    a[rank + 1] = rank
    println("$(rank): $(a)")
end

      From worker 2:	0: [0, 0, 0, 0]
      From worker 4:	2: [0, 0, 2, 0]
      From worker 5:	3: [0, 0, 0, 3]
      From worker 3:	1: [0, 1, 0, 0]
In [5]:
@mpi_do manager begin
    index = (rank+2)%4 + 1
    println("$(rank): $(a[index])")
end

      From worker 4:	2: 0
      From worker 2:	0: 0
      From worker 3:	1: 0
      From worker 5:	3: 0