eioio VS ocaml-multicore

the actual project (Readme has some code samples): https://github.com/ocaml-multicore/eio

For 5.0+ you might want to look at https://github.com/ocaml-multicore/eio for how effects can make async much more pleasant

Great post! I would love to see this extended to OCaml 5 (with eio) and Haskell

Second, effects enable a new style of concurrency libraries like eio that forgoes the need to wrap every asynchronous computation in a monad.

> This is realllly unidiomatic in real world Haskell.

Whether idiomatic or not does not matter. It proves my point:

IO won't save you, and even very mundane effects are not part of the game…

Idris is the "better Haskell" sure, but the effect tracking is still part of the uncanny valley (still IO monad based).

Koka is a toy, and Frank mostly "only a paper" (even there is some code out there).

The "Frank concept" is to some degree implemented in the Unison language, though:

https://www.unison-lang.org/learn/fundamentals/abilities/

Having a notion of co-effects (or however you please to call them) is imho actually much more important than talking about effects (as effects are in fact neither values nor types—something that all the IO kludges get wrong).

I think the first practicable approach in the mainstream about this topic will be what gets researched and developed for Scala. The main take away is that you need to look at things form the co-effects side first and foremost!

In case anybody is interested in what happens in Scala land in this regard:

https://www.slideshare.net/slideshow/embed_code/key/aLE9M37d...

https://docs.scala-lang.org/scala3/reference/experimental/cc...

But also the development in OCaml seems interesting:

https://github.com/ocaml-multicore/eio#design-note-capabilit...

Look mom, "effects", but without the monad headache!

To enable access to all these features, an exciting new library called Eio is being developed. It uses a new paradigm of direct-style concurrent I/O programming, without the need for monads or async/await, thus avoiding the function colour problem.

1. Domains are the unit of parallelism. A domain is essentially an OS thread with a bunch of extra runtime book-keeping data. You can use Domain.spawn (https://github.com/ocaml-multicore/ocaml-multicore/blob/5.00...) to spawn off a new domain which will run the supplied function and terminate when it finishes. This is heavyweight though, domains are expected to be long-running.

2. Domainslib is the library developed alongside multicore to aid users in exploiting parallelism. It supports nested parallelism and is pretty highly optimised (https://github.com/ocaml-multicore/domainslib/pull/29 for some graphs/numbers). The domainslib repo has some good examples: https://github.com/ocaml-multicore/domainslib/tree/master/te...

3. We've not tested against other forms of parallelism. There isn't anything stopping you exploiting SIMD in addition to parallelism from domains.

4. No, we've not compared performance by OS.

5. No plans for the multicore team to look at accelerator integration at the moment.

For Algebraic Effects and Multicore OCaml specifically, I have this intro saved and they've been publishing regular updates here's October's. They have a paper linked from their repo's README but I don't remember the contents offhand.

Until recently Multicore OCaml was focused on deep handlers. The people working on the formalization of effects (either for program proofs or typed effects) were quite keen to have shallow handler integrated however. Thus, the effect module of the OCaml 5 preview contains both (see https://github.com/ocaml-multicore/ocaml-multicore/blob/5.00...) since September. I fear that non-academic literature has not followed this change (on the academic side, see https://dl.acm.org/doi/10.1145/3434314 for a program proofs point of view).

Yes, it's announcing that the next but one version, 5.0, will support multicore and effect handlers.

For what it's worth you can actually start using Multicore OCaml today, there are installation instructions on the wiki: https://github.com/ocaml-multicore/ocaml-multicore

ocaml-multicore/ocaml-multicore

Could you explain (in simple terms if possible) how the Multicore OCaml achieves a memory model which is much simpler on more efficient than in Java or C (mentioned at https://github.com/ocaml-multicore/ocaml-multicore/wiki)?

Didn't see any mentions of critical sections (mutexes) with C++ examples in the documentation ("Bounding Data Races in Space and Time"). I'm not sure I understand the comparisons the writers are presenting.

There are getting started instructions up on https://github.com/ocaml-multicore/ocaml-multicore