Julia

A high-performance language for technical computing.

Julia is a JIT-compiled, dynamically typed language designed for numerical and scientific computing. It pairs the conveniences of a high-level dynamic language (REPL workflow, dynamic typing, multiple dispatch as the central programming model, package manager, easy plotting) with type-stable code that LLVM can compile to machine code on the fly, which often matches Fortran or C performance on tight numerical loops.

The language was started in 2009 at MIT by Jeff Bezanson, Stefan Karpinski, Viral Shah, and Alan Edelman, who wanted "the speed of C with the dynamism of Ruby". Public release came in 2012, the 1.0 stable release in 2018, and JuliaHub (the spin-out company that employs many core developers) in 2020. The package ecosystem covers differential equations, optimisation, machine learning, geosciences, and many other domains, often outperforming equivalent Python+NumPy code on the same hardware.

Julia is used at Lawrence Livermore National Laboratory, the Federal Reserve Board (their FRBNY DSGE model is implemented in Julia), the Climate Modeling Alliance, the Federal Aviation Administration, and across academic research labs that need performance without dropping to C++ or Fortran. The Pumas pharmacology platform and Beacon Biosignals' EEG analysis tooling are well-known industry users.

License: MIT

Category: Language

Website: https://julialang.org/

Install

Download the official binary from https://julialang.org/downloads/
Or:
  Debian/Ubuntu: sudo apt install julia
  Arch:          sudo pacman -S julia
  macOS:         brew install julia

Authors

Jeff Bezanson, Stefan Karpinski, Viral Shah, Alan Edelman (creators)
Julia community and JuliaHub

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