My reason for using MPI is simply that I'm used to MPI, and t is very easy for me to adapt existing Octave code that uses MPI to use Julia instead of Octave. For code such as these Monte Carlo examples, I doubt that it would make much difference if one were to use pmap, for example, instead of MPI. For more complicated code that uses multiple sends and receives, the ability to adapt existing MPI code is more important. I haven't done any performance comparisons. So far, I find that Julia with MPI works very nicely with MPI, though.
On Sunday, June 14, 2015 at 11:59:46 AM UTC+2, Viral Shah wrote: > > Unless you really need to use some MPI functionality, why not use the > built-in parallel processing capabilities? Does using MPI give a major > performance benefit in your case? > > -viral > > On Friday, June 12, 2015 at 3:38:34 AM UTC-4, [email protected] > <javascript:> wrote: >> >> https://github.com/mcreel/JuliaMPIMonteCarlo has code for doing Monte >> Carlo using the MPI package (https://github.com/JuliaParallel/MPI.jl). A >> note addressed to primarily to economists gives some discussion. The >> intention is to get beginners started, but there is also a more complex >> example. Embedded in that example, there is code for local linear >> nonparametric regression. >> >
