What is Julia written in?
What Julia is used for
Julia targets scientific and numerical computing, aiming for the readability of Python with the speed of C. It is used in research, data science, and high-performance simulation.
Notable software: climate models, pharmaceutical simulations, and the Pumas pharmacometrics platform.
Quick Facts
- Designed by
- Jeff Bezanson, Alan Edelman, Stefan Karpinski, and Viral B. Shah
- First released
- 2012
- Typing
- dynamic
- Filename extension
- .jl
- Website
- julialang.org
About Julia
Julia is a high-performance dynamic programming language. It is a dynamically typed and garbage-collected language that is just-in-time compiled to machine code as it runs. It supports imperative, functional, and scientific programming. A just-in-time (JIT) compiler translates hot code paths to native machine code while the program runs, trading a slower start for faster steady-state speed.
Julia first appeared in 2012 and was designed by Jeff Bezanson, Alan Edelman, Stefan Karpinski, and Viral B. Shah. Julia keeps a steady, moderate following today.
How Julia is implemented
In the Language Lineage dataset, Julia is self-hosting, so its own compiler is written in Julia itself, its runtime is implemented in LLVM, C, and C++, and its toolchain was bootstrapped from FemtoLisp. Reaching self-hosting, where a language is mature enough to compile itself, is a milestone that proves the language can handle a large, real-world program.
Julia in the language family tree
Julia drew on ideas from Python, Fortran, Lisp, Ruby, and MATLAB.
Sources: Wikipedia · Wikidata · Official site
Frequently Asked Questions
Evidence Sources
- https://julialang.org/blog/2012/02/why-we-created-julia/
- https://github.com/JuliaLang/julia
- https://julialang.org/
- https://discourse.julialang.org/t/the-role-of-femtolisp-in-julia/
- https://en.wikipedia.org/wiki/Julia_(programming_language)
- Julia on Wikidata (Q2613697)