Julia is a high-level, high-performance, and dynamically-typed programming language that is well-suited for numerical analysis and scientific computing. Julia is currently being used in computational biology, statistics, image processing, machine learning, and physics (to name a few).
Computer scientists Jeff Bezanson, Stefan Karpinski, Viral B. Shah, and Alan Edelman started work on Julia in 2009 with the goal of creating a language that was high-level and fast. The language was launched in 2012.
Apart from being a fully dynamic programming language, Julia allows concurrent, parallel, and distributed computing. It also supports the direct calling of C, Python, and Fortran libraries. According to their official website, some of Julia’s features are:
Multiple dispatch: Provides the ability to define function behavior across many combinations of argument types.
High performance: Julia was designed for high performance. Its performance approaches that of statically-typed languages like C.
Open-source: Julia is free for everyone to use, and all source code is publicly viewable on GitHub.
C and Python functions: Julia can call C functions without any additional wrappers or API’s, and can utilize Python functions using the PyCall package.
Parallel and distributed computing: Julia is designed to be highly optimized for parallel and distributed computing.
Additional information about Julia can be found here.
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