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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.
The library, largely written in Julia itself, also integrates mature, best-of-breed C and
Fortran libraries for linear algebra, random number generation, signal processing, and string processing.
+In addition, the Julia developer community is contributing a number of external packages through
+Julia's built-in package manager at a rapid pace.
+
+IJulia, a collaboration between the IPython and Julia communities, provides a powerful browser-based
+graphical notebook interface to Julia.
+
+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.
+
+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