Julia bindings for the Enzyme automatic differentiator

Basic Geometry Types

Large-scale, distributed, sparse linear algebra in Julia.

Update immutable data

Common functional iterator patterns

Calculating contour curves for 2D scalar fields in Julia

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.

Simple, consistent interfaces for any codec.

The Base interface of the SciML ecosystem

Powerful convenience for Julia visualizations and data analysis

Primitives for construction of objects

MPI wrappers for Julia

High performance nearest neighbor data structures (KDTree and BallTree) and algorithms for Julia.

HDF5-compatible file format in pure Julia

AD-backend agnostic system defining custom forward and reverse mode rules. This is the light weight core to allow you to define rules for your functions in your packages, without depending on any particular AD system.

Forward Mode Automatic Differentiation for Julia

SciMLOperators.jl: Matrix-Free Operators for the SciML Scientific Machine Learning Common Interface in Julia

Convert julia objects to LaTeX equations, arrays or other environments.

Julia implementation of Data structures

A structure interface for SciML to give queryable properties from user data and parameters

Julia macro for re-exporting one module from another

Julia bindings to the FFTW library for fast Fourier transforms

Julia wrapper for the LLVM C API

Formatted output of timed sections in Julia

Iterative algorithms for solving linear systems, eigensystems, and singular value problems

Julia functional programming infrastructures and metaprogramming facilities

Direct solution of large sparse systems of linear algebraic equations in pure Julia

An optimized graphs package for the Julia programming language

Abstract julia interfaces for working with trees

Basic statistics for Julia

A common solve function for scientific machine learning (SciML) and beyond

Repository for automatic differentiation backend types

A Julia package to provide C and Python-like formatting support

BlockArrays for Julia

Colorschemes, colormaps, gradients, and palettes

Fixed point types for julia

Grid-based approximation of partial differential equations in Julia

Algebraic Multigrid in Julia

Reusable compiler infrastructure for Julia GPU backends.

Physical quantities with arbitrary units