Add example of Multi-GPU simulation

[rkierulf]

Feature Request

In some cases, it may be beneficial to run MRI simulations on multiple GPUs if the problem is too large for single-GPU memory. KomaMRI does not have built-in support for this, but due to the independent spin property, it would not be too hard for a programmer to manually split the simulation into parts, run each part on a different GPU, then add the results at the end.

Based on this section of the CUDA.jl documentation, here is one example I think would work without needing to update code within the package (NOTE: I have not tested this!):

using Distributed, CUDA

addprocs(length(devices()))
@everywhere using CUDA, KomaMRI

sys = Scanner()
obj = Phantom()
parts = kfoldperm(length(obj), length(devices))
seq = read_seq("SequenceFileName.seq")
signal_arr = []

asyncmap((zip(workers(), devices()))) do (p, d)
    remotecall_wait(p) do
        device!(d)
        push!(signal_arr, simulate(@view(obj[p]), seq, sys))
    end
end

signal = reduce(.+, signal_arr)

If this does work, it would be helpful to add to the examples folder of the repository and package documentation.