salsa VS ocaml-multicore

There are some excellent crates already in the Rust ecosystem (notably Salsa) for performing incremental computation, although they generally have different goals to Depends.

The content of that "Core Concepts" page sounds a lot like https://github.com/salsa-rs/salsa

I know of salsa, but I don't know if it can persist changes to disk (and my guess from looking at this issue is that it can't).

- the practical approach to this is to split workload into work units (aka tasks/queries/etc.) and then force information flow through centralized "request"/"query" APIs that automatically track dependencies - see https://github.com/salsa-rs/salsa for more information

This, and as pointed Salsa.

These guys might be of interest for you, they think a lot about incremental parsers. https://github.com/salsa-rs/salsa

salsa-rs authored by niko matsakis and other top rust devs

Some optimizations are not easy with Go. For example caching like in Rust Analyser Salsa Framework

How would this differ from salsa (https://github.com/salsa-rs/salsa) and the query-driven approach used by rustc?

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