Fortran comprises a huge body of software in high-performance computing. We look at Fortran’s evolution into a modern HPC language.

The Joblib Python Library handles frequent problems – like parallelization, memorization, and saving and loading objects – in almost no time, giving programmers more freedom to push on with their core tasks.

The Python Data Analysis Library, or Pandas, is built on top of the fast math library NumPy and makes analysis of large volumes of data an easy and efficient experience.

The Julia language is a very powerful parallel computing model that works across multiple cores and cluster nodes.

Can this new language deliver on bold claims of fast, easy, and parallel?