This action builds a Julia package.

LinearSolve.jl: High-Performance Unified Interface for Linear Solvers in Julia. Easily switch between factorization and Krylov methods, add preconditioners, and all in one interface.

High level plotting on the GPU.

A modeling framework for automatically parallelized scientific machine learning (SciML) in Julia. A computer algebra system for integrated symbolics for physics-informed machine learning and automa…

Functions generated at runtime without world-age issues or overhead

High-performance and differentiation-enabled nonlinear solvers (Newton methods), bracketed rootfinding (bisection, Falsi), with sparsity and Newton-Krylov support.

Symbolic expressions, rewriting and simplification

Serving JS to the browser

A library of useful callbacks for hybrid scientific machine learning (SciML) with augmented differential equation solvers

Fast operator-overloading Jacobian & Hessian sparsity detection.

The official registry of general Julia packages

CUDA programming in Julia.

A megapack of themes for GNU Emacs.

Reusable compiler infrastructure for Julia GPU backends.

A general interface for symbolic indexing of SciML objects used in conjunction with Domain-Specific Languages

Modeling language for Mathematical Optimization (linear, mixed-integer, conic, semidefinite, nonlinear)

Tools for building non-allocating pre-cached functions in Julia, allowing for GC-free usage of automatic differentiation in complex codes

Package for dynamical modeling of power grids

The Julia Programming Language