For those sorts of scientific simulations, you probably want to use the MPI.jl package rather than the built-in parallelism – at least that’s the conclusion I came to when I started the fluids code I’m currently working on. MPI.jl is a thin wrapper around the C interface so you end up writing your programs pretty much the same way as in C/Fortran. This type of MPI support is still a bit rough around the edges but it works, and our code runs as fast as the Fortran code it is based on (we usually scale to ~1000 cores). You get the advantage of working with a very nice, modern language, but it is pretty easy to accidentally do things that are very expensive and killing your performance, such as allocating memory inside a hot loop.

A bit more specifically: IIRC it defaults to trying to use MPI when you launch distributed jobs. It can also fall back to using SSH, for "extremely limited cases" and quite frankly it's not inappropriate to use SSH if you are certain that communication is not going to be a bottleneck.