libfringe VS rayon

There’s a bunch of library-based implementations of coroutines for rust. I recall https://github.com/edef1c/libfringe being the most interesting one, but it is quite dated. I don’t think there’s a lot of community interest in stackfull coroutines at this point.

As we saw earlier, scheduling threads is a hard task for the operating system. To replace one thread that's being executed with another one, a lot of work needs to be done (including saving all the registers and some thread state). However, switching between Lunatic Processes does only the minimal amount of work possible. With an idea pioneered by the libfringe library and using some asm! macro magic, Lunatic lets the Rust compiler figure out the minimal number of registers to be preserved during context switches. This makes scheduling Lunatic processes zero-cost. On my machine usually 1ns, equivalent to a function call.

Do some operations with .iter() then later use rayon to parallelize. So you can show how easy is to add a dependency and how easy is to parallelize.

rayon: Async CPU runtime for parallelism.

In the quest for more efficient solutions, the ONNX runtime emerged as a beacon of performance. The decision to transition from Typescript to Rust was an unconventional yet pivotal one. Driven by Rust's robust parallel processing capabilities using Rayon and seamless integration with ONNX through the ort crate, Repo-Query unlocked a realm of unparalleled efficiency. The result? A transformation from sluggish processing to, I have to say it, blazing-fast performance.

With a lot of rayon, blood, sweat and tears I finally managed to simulate a million buildings at 60fps :) Feel free to AMA, game is Combine And Conquer

(see https://github.com/rayon-rs/rayon/tree/master/src/iter/plumbing)

I did some very basic testing with this crate : https://crates.io/crates/rayon and it seems to work :

Sequentially, generating tree-sitter AST for each file and querying for the links of each file takes around 2.3 seconds. However, I randomly remembered this crate rayon, and I decided to test it. It ended up improving the performance (just by changing 2 lines of code) to 200-300ms by parallelizing the iterators and tree-sitter queries. MAJOR.

Now if you really want to use Rust, you can rewrite only the part that are slowing down your consumer. It's easy by using Py03 and maturin. Maybe also rayon to parallelize.