rand VS rayon

Making compatibility promises for distributions means they cannot take advantage of potential advancements in the field.

Defining an error type that is meaningful, portable, and compatible with no-std isn't straightforward. If the std lib's getrandom requires std, then just like that, rand and many other crates won't use it anyway. Using io::Result seems to me to face this challenge.

Some wasm targets can’t generate random numbers at all but in the case of the book because you are using wasm in a browser you can use JS to generate random numbers. I believe there’s a way to get the rand crate to use JS as the backend for generating rand but its a bit more convoluted than the easy one-liner that the book suggests.

rand

This uses rand and xcomplex to handle the mathematics, png to write image files, and dialoguer and indicatif for some pretty prompts and progress bars.

You can often achieve this without any unsafe by putting an assert!() on the length before the hot loop. For example, I got rid of some unsafe in rand that way.

This is a widely used method to map random integers to floating point numbers, but it has the disadvantage of wasting 1 bit of float mantissa precision.

On modern CPUs, its computational advantage over full-precision mapping methods, such as multiplication by a float, is not always clear [1].

[1] https://github.com/rust-random/rand/issues/416

In fact, there are a lot of crates in Rust where in other programming languages, it would be included in the standard library. Examples are regex, random number generators, additional iterator methods, macros for other collections, num traits, loggers, HTTP libraries, error handling, async runtimes, serialization and deserialization, date and time, and many more.

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.

Maybe rayon could make some loops there and there faster if needed.