Forward Mode Automatic Differentiation for Julia

Statically sized arrays for Julia

Macro(s) for vectorizing loops.

Julia implementation of Data structures

Basic statistics for Julia

Special mathematical functions in Julia

MacroTools provides a library of tools for working with Julia code and expressions.

An interface for tables in 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.

The cheapest threads you can find!

Reduce time-to-first-execution of Julia code

Lazy code loading for Julia

Fortran-like arrays with arbitrary, zero or negative starting indices.

Compatibility across Julia versions

Designs for new Base array interface primitives, used widely through scientific machine learning (SciML) and other organizations

Project Preferences Package

Extensions for Julia's docsystem.

Julia implementation of associative containers that preserve insertion order

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SparseArrays.jl is a Julia stdlib

`@pack!` and `@unpack` macros

A simple shared suite of common derivative definitions

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Julia package for various special functions based on `log` and `exp`.

Missing value support for Julia

Base library providing vectorization-tools (ie, SIMD) that other libraries are built off of.

Calculate with error-free, faithful, and compensated transforms and extended significands.

Ask the CPU for cache sizes, SIMD feature support, a running hypervisor, and more.

Julia math built-ins which return NaN and accumulator functions which ignore NaN

Extra sorting algorithms extending Julia's sorting API

Static types useful for dispatch and generated functions.

Naïve combined subexpression elimination in Julia

A package which provides an API for querying differentiation results at multiple orders simultaneously

A data-focused namespace for packages to share functions

Manual memory management utilities.

Interface for function inversion in Julia

Pirated SLEEF port.

Sum and cumulative sum using the Kahan-Babuska-Neumaier algorithm

Under some conditions you may need this function

Utilities for low overhead threading in Julia.