Julia language , a new language introduced to the technical computing. It is a high level, high performance dynamic programming language. It has the syntax familiar to the user of the other technical computing language.
It has an extensive mathematical functional library, it provides numerical accuracy, sophisticated amplifier and a distributive parallel execution.
The library is been written in Julia but has active C and FORTRAN libraries for linear algebra, random number generation and string processing.
Julia programs are set up around defining functions and overloading them for different combination of user-defined arguments types.
JIT compiler with high performance
Julia’s Just-In-Time compiler combined with the language’s design allow it to improve the run time performance and often match upto the performance of C/C++.
To prove the point let us take the example of numerical and scientific computing. There are some set of micro benchmark have been given in variety of language. Here you can skim the code to know how easy or difficult the codes are.
Julia’s Low-Level-Virtual-Machine(LLVM) JIT code has somehow beaten C++ by 25% on pi summation . This benchmark, being precise, do analyse the compiler performance on a range of common code pattern like string parsing, function calls, sorting and numerical loops, random numbers generation and array operation.
The code written in Julia in matrix statistics , however been beaten by C++, is much more simpler the C++ implementation. However,the improvisation in the codes and the compilation would meet up the gap in future.
To see the difference let us see the examples of some codes written in Julia.
Design for Parallelism and Cloud Computing
Julia provides a number of key building blocks for distributed computation making it more flexible to support several styles of parallelism.
At its very early stage Julia supports cloud computing mode. Here is the screenshot of based interactive Julia Session.
There will have the full support of cloud computing operations like sharing and editing, including data management, data exploration and visualization. This allow users to work big data type without getting worried about the administration of managing data.
Free, Open Source And Library Friendly
The core is been licensed under MIT license. Various Libraries used by Julia have their own license such as GPL LGPL and BSD.
User can easily combine Julia with their C/FORTRAN codes as the core functionality in a shared library.
Source : julialang.org
You can read the complete manual here : Julia manual