Does Rust have a way to work with SIMD concurrency as opposed to just fork/join concurrency? Something along the lines of how openmp or cilk let you do a parallel for all?
You seem to have concurrency confused with parallelism. Concurrency just means working on another task before the prior one has completed. You're describing parallelism which is doing multiple tasks at the same time.
By SIMD concurrency, I meant that I was curious about a construct that actually translated into simultaneously executing code, not just a construct that denotes work that "could" be done simultaneously.
Rust supports SIMD, with some utility structs that let you do it easily. I don't know of any libraries that auto-simd things though IIRC LLVM can do this on its own sometimes.
I think the parent was referring to "lightweight task"-based concurrency like C#'s PLinq:
// C#
int sum;
Parallel.ForEach(myCollection, item => sum += item);
Which operates using a reasonably sized thread pool rather than a thread per item. Something similar in Rust (Excuse my rusty rust) would look like.
let someList = ...
parallel::for(someList.iter(), |item| {
// Do thing with each item
};
I think there is ongoing work on this topic, but it will likely only be library-level and not language-level (Just like Linq is a language level feature in C# but PLinq is a library). There are some third party crates that do this like simple_parallel.
Edit: Low-level simd exist as intrinsics and of course through llvm vectorizations.
The simplest library for this kind of data parallelism is Rayon[1]. The README provides a nice overview and links to a series of blog posts about the details.
A simple google search would have told you that there is work being done the introduce simd in Rust. There appear to be some basics there right now but not much if i understood my quick search.
An active discussion about concurrency in rust with first developers commenting is a very appropriate place to ask that question, and ultimately much more likely to yield valid and current information than Google.