Several crates have populated the scientific computing space, including linear algebra and matrix operations, numerical optimization, and more.
Given the value of iterative analysis in scientific computing, it's worth checking out Evcxr REPL. There is also a Jupyter backend for Rust.
Also, check out some of these resources:
General-purpose linear algebra library with transformations and statically-sized or dynamically-sized matrices.
General matrix multiplication for f32 and f64 matrices. Operates on matrices with general layout (they can use arbitrary row and column stride). Detects and uses AVX or SSE2 on x86 platforms transparently for higher performance. Uses a microkernel strategy, so that the implementation is easy to parallelize and optimize. Supports multithreading.
Geometry primitives
Statistical computing library for Rust
A linear algebra and mathematics library for computer graphics.
Statistical routines for ArrayBase, the n-dimensional array data structure provided by ndarray.
Mathematical optimization in pure Rust
A sparse matrix library
Linear algebra package for rust-ndarray using LAPACK
A bioinformatics library for Rust. This library provides implementations of many algorithms and data structures that are useful for bioinformatics, but also in other fields.
A linear algebra library.
A rust binding for the GSL (the GNU scientific library)
Machine Learning in Rust.
The package provides wrappers for LAPACK (Fortran).
Rust comprehensive scientific computation library contains linear algebra, numerical analysis, statistics and machine learning tools with farmiliar syntax
Simple k-means clustering to find dominant colors in images. Backed by a generic k-means implementation offered as a standalone library.
CUDA Driver API Wrapper
The package provides wrappers for BLAS (Fortran).
Scientific computing in Rust
Performs regression for generalized linear models using IRLS on data stored in arrays.
A low-level modular, extensible GPGPU compute library with cross-platform support
Tensors and dynamic neural networks.
Newton based methods for root finding
high-performance computation on any hardware
Clarabel Conic Interior Point Solver for Rust / Python
high-performance computation on any hardware
Flexible and modular single or multi-objective solver for contiguous and discrete problems
A macro for executing a subset of Rust with OpenCL
A numerical computations library for Rust
Linear Algebra package with rust-ndarray interface
A scientific computing library
Open Source, High Performance & Hardware Accelerated, Quantum Computer Simulation in Rust
A high-performance computing (HPC) framework
Are we learning yet?
