Forward Mode Automatic Differentiation for Julia

Statically sized arrays for Julia

Macro(s) for vectorizing loops.

Special mathematical functions in Julia

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

Calculus functions 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.

Multi-threaded BLAS-like library that provides pure Julia matrix multiplication

Reduce time-to-first-execution of Julia code

Lazy code loading for Julia

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

Bring Your Own Stack

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.

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SparseArrays.jl is a Julia stdlib

`@pack!` and `@unpack` macros

A simple shared suite of common derivative definitions

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

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

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

Library supporting the ArrayInterface.jl strided array interface.

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

Static types useful for dispatch and generated functions.

Stack-allocated pointer-based array views

Fast, LoopVectorization.jl-based summary statistics

Julia implementation of HyperDualNumbers

Naïve combined subexpression elimination in Julia

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

Vectorized uniform and normal random samplers.

Manual memory management utilities.

Interface for function inversion in Julia

Create and control multiple Julia processes remotely for distributed computing. Ships as a Julia stdlib.

Pirated SLEEF port.

Under some conditions you may need this function

Utilities for low overhead threading in Julia.

The core AbstractStrideArray type, separated from StrideArrays.jl to avoid circular dependencies.

Defines additional irrationals