As you might know, scientific and technical computing uses a variety of programming languages. These include traditional languages such as C, C++ and Fortran, more modern alternatives such as Python with the NumPy and SciPy libraries and specialized software such as Matlab. All these languages have their advantages and disadvantages. Usually, the faster choice is the more complex one and vice versa.
Julia is a new dynamic programming language that aims to offer a high-level, high performance solution to technical computing. Its syntax is similar to Matlab while it also provides modern features such as distributed parallel execution. The main features of Julia are:
- It offers performance that matches C and C++ thanks to its JIT compiler. It beats other high-level languages in most benchmarks.
- It is designed for parallelism and cloud computing.
- It can call C functions directly.
- It is multi-paradigm, combining features of imperative, functional and object-oriented programming.
- It is free, open source and library-friendly.
Here is some example Julia code: function mandel(z) c = z maxiter = 80 for n = 1:maxiter if abs(z) > 2 return n-1 end z = z^2 + c end return maxiter end As you can see this is familiar and pretty easy to learn. Julia combines performance and ease of use. If you are interested in a new solution for technical computing, then we suggest giving the Julia language a try.