[elbasti]

The BEAM is pretty high level, and it's REALLY good at managing distributed compute at the thread or device level.

If you have a parallelizeable workflow, it's very easy to make it (properly!) parallel locally, where by "properly" I mean having supervision trees, sane restart behavior, etc.

And once you have that you can extend that parallelism to different nodes in a network (with the same sanity around supervision and discovery) basically for free. Like, one-line-of-code for free.

Nonetheless, it's all message-passing, and so pretty high level. AFAIK it's not designed for parallelizing compute at GPU scale.

That being said, if you have multiple GPUs and multiple machines that have to coordinate between them, Elixir/Erlang is pretty much perfect.

[throwawaymaths]

If you have a multistage workflow with concurrent and possibly heterogenous requests that hit all the time you can very easily batch and distribute the workflow among compute resources in "the most natural way possible" easily, without having to resort to grace periods, etc. which introduce latency. I think that would be much harder to accomplish with java.

[inawarminister]

I think Numerical Elixir (NX) allows for GPU programming. It uses XLA for scheduling computation?