The Julia Language

The Julia Language

''Julia is a high-level, high-performance dynamic programming language for technical computing, with syntax that is familiar to users of other technical computing environments. It provides a sophisticated compiler, distributed parallel execution, numerical accuracy, and an extensive mathematical function library.

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Julia programs are organized around multiple dispatch; by defining functions and overloading them for different combinations of argument types, which can also be user-defined. ''





And more:

''A Summary of Features

• Multiple dispatch: providing ability to define function behavior across many combinations of argument types
• Dynamic type system: types for documentation, optimization, and dispatch
• Good performance, approaching that of statically-compiled languages like C
• Built-in package manager
• Lisp-like macros and other metaprogramming facilities
• Call Python functions: use the PyCall package
• Call C functions directly: no wrappers or special APIs
• Powerful shell-like capabilities for managing other processes
• Designed for parallelism and distributed computation
• Coroutines: lightweight “green” threading
• User-defined types are as fast and compact as built-ins
• Automatic generation of efficient, specialized code for different argument types
• Elegant and extensible conversions and promotions for numeric and other types
• Efficient support for Unicode, including but not limited to UTF-8
• MIT licensed: free and open source''

''Partly because of run-time type inference (augmented by optional type annotations), and partly because of a strong focus on performance from the inception of the project, Julia’s computational efficiency exceeds that of other dynamic languages, and even rivals that of statically-compiled languages. '' [source]

A presentation/introduction: http://julialang.org/blog/2013/03/julia-tutorial-MIT/

And "learn Julia in minutes": http://learnxinyminutes.com/docs/julia/