The focus of this category is on the Julia programming language, which was designed by Alan Edelman, Stefan Karpinski, Jeff Bezanson, and Viral Shaw.
Work began on Julia in 2009, the goal being to produce an open-source language that was powerful and fast. The language was released in 2012 under the MIT (core) and General Public License, and it wasn't long before a strong developer community grew up around it. Julia has received contributions from hundreds of developers worldwide, and funding has come from the MIT Lincoln Laboratory, the Gordon and Betty Moore Foundation, the Alfred P. Sloan Foundation, Intel, and DARPA, FAA, NASA, NIH, and NSF. Julia Computing was founded in 2015 by the chief designers of the language, as well as Deepak Vinchhi and Keno Fischer.
Julia is particularly suited for the computation of intensive tasks, as it is a compiled language that runs nearly as fast as Fortran or C, and much faster than Python.
It is free and open-source, easy to learn, elegant, clear, dynamic, and interactive. Once compiled, programs produced by Julia have high computational power and speed. The language has metaprogramming and macro capabilities, as well as built-in concurrent and parallel capabilities. It can be run in a terminal application known as the REPL (read, execute, print, loop) mode, which is helpful in checking code syntax. Many programmers like the fact that Jula indexes arrays beginning with one rather than zero, as several other languages do.
It is also a general-purpose programming language. With Julia, no other programming language is needed in order to produce high-performance code. Julia is, however, interoperable with several other languages, and has packages supporting markup languages like BSON, HTML, JSON, XML, and for databases and web use in general.
Julia has an extended standard library, with several third-party packages available.
Topics relating to the programming language, any of its extensions, compilers, IDEs, editors, or other tool created for the purpose of being used with the language, are appropriate for this category, as are Julia user groups, forums, tutorials, or related resources.
Recommended Resources
A product of Julia Computing, Julia Box allows programmers to run Julia in their browser, offering a free level of access and two paid options, based on a monthly subscription. Featuring the Jupyter Notebook Interface, curated Julia packages, multi-node deployment capabilities, parallel computing capability, and other features, the three plans are compared side-by-side, including their monthly rates. Added memory, storage, nodes, and enterprise support may be purchased.
https://www.juliabox.com/
Founded by the chief designers of the Julia programming language, the company provides products, training, and consulting services designed to make Julia successful to client organizations. Operating out of Boson, London, and Bangalore, the company has customers worldwide. Well-known Julia users, partners, and employers hiring Julia programmers are highlighted, and its products, services, training programs, case studies, and a blog are included.
https://juliacomputing.com/
Julia is a programming language released publicly in 2012. Julia language research and development at the Massachusetts Institute of Technology (MIT) collaborates with a variety of researchers on real-world problems and applications, while simultaneously working on core language development and its ecosystem. Its research programs, past and current, are highlighted, along with its publications, conference schedules, current members, alumni, and sponsors.
https://julia.mit.edu/
Packages and utilities for the Julia programming language are highlighted here. Sorted by default with the most frequently downloaded packages at the top, they can be optionally sorted by the date of release or alphabetically. Packages are also sorted into several topical categories, such as open data science, machine learning, graphics, file i/o, optimization, statistics, graph theory, hardware, graphics, mathematics, supercomputing, programming paradigms, and so on.
https://juliaobserver.com/
JuliaBerry is a developer organization that brings together resources for using the Julia programming language with the Raspberry Pi. Instructions as to which version of Julia can be installed on a Raspberry Pi device are put forth. An older version of Julia is available in Raspbian, and JuliaBerry hopes to update it to the most recent version soon. Other Raspberry P-specific packages include PiGPIO.jl, PiCaft.jl, and SenseHat.jl. Questions and issues are answered.
https://juliaberry.github.io/
Organized by a committee of volunteers, the annual conference is focused on promoting and advancing the use and technologies of the Julia programming language. Although its topic schedules may change from year to year, the conference includes networking opportunities among programmers, developers, vendors, and sponsors, as well as talks from experts in the language, and workshops on various topics related to the Julia language. Schedules and registration data are included.
https://juliacon.org/
The JuliaDB leverages the just-in-time (JIT) compiler of the Julia programming language so that table operations are fast. It also allows users to process data in parallel, or even calculate statistical models through integration, and to store any data type. Written completely in Julia, user-defined functions are JIT-compiled. Open-source, under an MIT License, JuliaDB may be downloaded for free. Its benchmarks and features are highlighted, and it is compared with other time series packages.
https://juliadb.org/
The JuliaOpt GitHub organization has created or is home to a number of optimization-related packages written in the Julia programming language. The purpose of the group is to facilitate collaboration among developers of a tightly integrated set of packages for mathematical organization. Workshops and presentations sponsored by the group are set forth, including schedules and other details, and links to other sites offering resources for the Julia language.
http://www.juliaopt.org/
Juno is a flexible integrated development environment (IDE) for the Julia programming language. Available as a free download from The Julia Programming Language site, Windows, macOS, and Linux platforms are supported. Installation instructions, as well as the basic usage, common problems, debugging, and developer documentation are included, as well as the source code. A user support forum posts development announcements and offers support services.
https://junolab.org/
Written in Julia, maintained by William Tart, Tommy Hofmann, Claus Fieker, and Fredrik Johansson, and licensed under the BSD License, Nemo is a computer algebra package for the Julia programming language. Nemo makes use of GPL and LGPL C/C++ libraries, such as Antic, Arb, Flint, GMP/MPIR, MPFR, and Singular. Its features and benchmarks are listed, along with development notes, author acknowledgments, references, and documentation.
http://www.nemocas.org/
The Julia Programming Language
Designed for high performance, Julia programs compile to efficient native code for multiple platforms via LLVM. The official site for the language lists and defines the major features of the language, and its download page includes packages for Windows, macOS, Linux for x86, Linux for ARM, and FreeBSD for x86, as well as other resources, and links to editors and IDEs that are designed for use with the language. Documentation, tutorials, books, and research on Julia are included.
https://julialang.org/
