Download Julia Language (64-bit) Download (2021 Latest) Free

Julia Language 64 bit dynamically typed, looks like scripting language, and has good support for interactive use. Yuliya has a rich language of descriptive data types, and type declarations can be used to clarify and harden programs. Programs are compiled to efficient native code for multiple platforms via LLVM.

Yuliya uses plural dispatch as a paradigm, making it easy to express many object-oriented and functional programming patterns. The standard library provides asynchronous I / O, process control, logging, profiling, package manager, and more. It has a high level syntax making it accessible to programmers of all skill levels and experience. Julia Tongue

free for everyone, and all source code is available for public viewing at Github…

It has been downloaded over 10 million times and the community has registered over 2,000 packages for the community to use. These include various math libraries, data tools, and general-purpose computation packages. In addition to these, you can easily use libraries from Python, R, C / Fortran, C ++ and Java.

Features and features

Data visualization and charting
Data visualization has a complex history. Printing software makes a trade-off between function and simplicity, speed and beauty, and static and dynamic interface. Some packages do a mapping and never change it, while others do real-time updates.

Build, deploy or embed your code
The application allows you to write user interfaces, statically compile your code, or even deploy it to a web server. It also has powerful shell-like capabilities for managing other processes. It provides Lisp-like macros and other metaprogramming facilities.

Interact with your data
The data ecosystem allows you to quickly load multidimensional datasets, perform aggregation, merge, and preprocessing operations in parallel, and save them to disk in efficient formats. You can also do online computations for streaming with OnlineStats.jl. Are you looking for convenient and familiar DataFrames or a new approach with JuliaDB. It provides you with a wide variety of tools. Queryverse provides query, file I / O and rendering functionality. In addition to working with tabular data, Yuliya packages make it easier to work with combinatorial data.

Scalable machine learning
It provides powerful tools for deep learning (Flux.jl and Knet.jl), machine learning, and artificial intelligence. Julie’s mathematical syntax makes it the perfect way to express algorithms as written in articles, build trainable models with automatic differentiation, GPU acceleration, and terabyte data support with JuliaDB…

A rich ecosystem for scientific computing
Julia was designed from the ground up to be very good at numerical and scientific computing. This is evident from the abundance of scientific tools written in the application, such as the modern ecosystem of differential equations (DifferentialEquations.jl), optimization tools (JuMP.jl and Optim.jl), iterative linear solvers (IterativeSolvers.jl), a robust framework for Fourier transforms ( AbstractFFTs.jl), a general purpose quantum modeling framework (Yao.jl), and many others that can manage all of your simulations.

Parallel and heterogeneous computing
The language is designed for parallelism and provides built-in primitives for parallel computing at all levels: instruction-level parallelism, multithreading, and distributed computing. As part of the Celeste.jl project, the performance of the Cori supercomputer at NERSC was 1.5 Petaflops / s using 650,000 cores. The compiler can also generate native code for various hardware accelerators such as GPUs and Xeon Phis. Packages such as DistributedArrays.jl and Dagger.jl provide a higher level of abstraction for concurrency.