GC on the other hand is very aggressive with all of the immutable data structures F# creates. GC in F# is very good, though, I think without good garbage collection you have a tough time in a functional world. Microsoft is especially interested in GC performance for .NET and they have explored memory dumps to improve GC so it performs well even under load and when used with F#.
F# inherits lots of .Net's primitives which at their core are thread pool based task scheduling with the usual optimized data structures you see from this world. While this might sound primitive, F# takes it further by providing very good functional libraries which abstract this away allowing lightweight asynchronous computations to be passed around as values (the type being Async<'a>).
Alone, this is pretty nice but it wouldn't feel as natural without computation expressions which are similar to Haskell's do-notation but with some generalizations and flexibility added in. This allows asynchronous code to look and feel first class. If you're curious I'd check out https://fsharpforfunandprofit.com/posts/concurrency-async-an... or check similar links on your search engine of choice.
Now, the story isn't complete. If you're comparing things to Erlang, there are also things like MailboxProcessor<'a> and such which allow other common patterns to be easily implemented. The type checking here is a nice bonus over some other approaches to message passing languages. The big minus of course is that it's still a traditional runtime. If you really want Erlang's isolated processes, it's hard to do that well outside of a runtime like BEAM. I also think F# could use better fault-tolerance primitives but I'm actively working on this with heavy influence from my work with Erlang.
There is also the Async monad: https://msdn.microsoft.com/en-us/visualfsharpdocs/conceptual...
Ofcourse it is also possible to use standard .net stuff like the TPL https://msdn.microsoft.com/en-us/library/dd537609(v=vs.110)....
However, both Async and IO are insufficient to represent disjunctions. To that end, another concurrency library that we use is Hopac. Hopac is an F# implementation of CML, with some differences. Hopac provides a notion of an alternative (called event in CML; think Haskel's Alternative typeclass if you relax the laws a bit) and synchronous channels (note that async channels are special cases of sync channels). Hopac's has experimental support for lawful MonadPlus as well (see transactional events in Haskell = IO + STM + CML).
Some things that we're heading towards next are generalizing STM to be a bit to be more like RCU (see relativistic Haskell). Additionally, we are experimenting with extending this to session types, but nothing in production yet.
F# also provides a MailboxProcessor, which is similar to an Erlang actor, however without explicit distribution support, so perhaps more of an "agent". We typically use this as a low-level concurrency primitive, rather than a full-blown programming model. Most of our services are compositions of various request/reply interactions, and the Async model above is a great fit for this. In fact, we've primitives centered around the notion of an arrow 'a -> Async<'b> (specialized to Async). These primitives provide support for fault tolerance, logging, tracing, etc.
All of this works well with the GC. Async does cause allocations of course, but this is a price we're more than willing to pay. We've shared some GC dumps with the designer of the .NET GC and she believes they are sensible for a functional language. Hopac took optimization to a greater extreme, reducing allocations where possible.
Another F# library of interest is MBrace. This takes the notion of Async and fits it with a scheduler that schedules across a cluster rather than an individual instance.
Hopefully this helps!
Async is similar to a Future (such as in Java), with the difference that Future produces a result once and caches it, whereas Async re-evaluates each time it is executed. It can be made to cache of course. A Future is more like a TPL Task, though IMO, Async provides a more predictable programming model.
Go has go-routines and channels. A go-routine is similar to Async. In essence, they are a notion of light-weigh thread. Note however that Hopac support for channels is far richer than that of Go.
You got it the other way around - synchronous is a special case of asynchronous, because any synchronous result or stream can be processed asynchronously, but for having guaranteed synchronous results you're adding restrictions. And going the other way, from async to sync is not possible without blocking threads, which is an error prone, platform specific hack. Take the possibility of blocking threads away and you'll notice the true nature of these models.
