To use MPI from Julia, use the MPI.jl package <https://github.com/lcw/MPI.jl> (`Pkg.add("MPI")`). There are also examples in this package.
Similar to Python, this MPI wrapper has two API levels: a lower level that feels much like C, and a higher level where arbitrary Julia objects can be sent and received. The MPI wrapper is not complete; if you need an MPI function that isn't wrapped, please speak up. -erik On Sun, Nov 23, 2014 at 11:32 PM, Gabriel Mihalache <[email protected]> wrote: >> 1) It's pretty easy to use MPI from Julia. For some use cases it may make >> more sense than Julia's built-in approach to parallelism, especially if >> you're already comfortable with MPI. Though if you're well served by pmap, >> that's much simpler. > > > Do you mean I should be able to broadcast and allgather memory managed by > Julia? That sounds scary. Luckily for me these models should be amenable to > pmap. Is there an example of MPI-from-Julia, just in case? > >> >> 2) It looks like the subproblem you're solving is a 1d optimization. I >> wouldn't be surprised if you could get a significant speedup by tweaking the >> optimization algorithm (e.g., using a derivative-based method) and making >> the function evaluations more efficient (e.g., avoiding temporary >> allocations). > > > Yes, thank you! This is a toy example for which we have an analytic solution > to check against. The project I'm working on involves a few more discrete > and continuous controls and states. I only hope that NLOpt.jl will run in > reasonable time compared to the C version. > > > Thank you for your reply! > Gabriel -- Erik Schnetter <[email protected]> http://www.perimeterinstitute.ca/personal/eschnetter/
