nalgebra VS faer-rs

Ok, so this uses https://rapier.rs/ which is very cool

Rapier, alongside https://nalgebra.org/ (which it uses underneath) has seriously good documentation and some advanced features like cross-platform determinism (something made hard by the way floating point differs between platforms)

> Some GA libraries[1][2] define types for the different kind of objects (grades)

That's nice!

This reminds of me things like, linear algebra libraries that will type-check matrices so that a 2x2 matrix can't be added to a 2x3 matrix (but then you can have a dynamic matrix that will error only in runtime), like https://nalgebra.org/ and others.

Maybe start by looking at https://nalgebra.org/ to see what rust math libraries might look like

And Nalgebra, while better, also seems to have slowed down on commits and responses to issues and PRs. I have a PR there for a relatively simple wrapper type for row vectors which was explicitly requested by a maintainer, which hasn't even gotten a comment since for two weeks.

nalgebra (similar to Eigen in cpp)

nalgebra

nalgebra is for linear algebra.

Take a look into math libraries, like glam, nalgebra, and cgmath. I've only used these through game engines, though, so I can't offer per-basis reviews/advice.

If you do not need GPU then I would recommend looking into Eigen in C++, nalgebra in Rust (with a BLAS in both cases for improved performance) or one of the above options (Julia / Python+JAX).

On the contrary, it seemingly can be used to make a BLAS implementation (example in a PR: https://github.com/sarah-ek/faer-rs/pull/37)

see the official website and the docs.rs documentation for code examples and usage instructions.

`faer` is a collection of crates that implement linear algebra routines in pure Rust. the aim is to eventually provide a fully featured library for linear algebra with focus on portability, correctness, and performance.

see the [official website](https://faer-rs.github.io) and the docs.rs documentation for code examples and usage instructions.

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this release implements the initial design of the high level api (see https://docs.rs/faer/0.11.0/faer/), which should allow users to get started with writing easy to read code without having to deal with managing memory or multithreading settings on their own.

i also added a thin compatibility layer with ndarray and nalgebra. this way users are able to mix and match libraries if they wish to do so, or to help with migration to different libraries

Faer is comparable to Eigen in most of their benchmarks, so they are getting closer.

performance compared to openblas is shown in the benchmarks on the repository, and on the website. (ndarray is using openblas)

currently working on a very efficient linear algebra library https://github.com/sarah-ek/faer-rs