The field of high-performance numerical computing lies at the crossroads of a number of disciplines and skill sets. In order to be successful at using high-performance computing today, it requires knowledge and skills of programming, data science, and applied mathematics. In addition to these, efficient implementation of the computational problems requires some understanding of processing and storage devices.

The role of computing in science has evolved to a different level in recent years. Programming languages (such as R and MATLAB) were common in academic research and scientific computing. Today, Python plays a big role in scientific computing for a good reason. The Python community has put together many efficient tools and packages that is being used not only by the research community, but also successful commercial organizations such as Yahoo, Google, Facebook, and Amazon.

There are two popular packages that are widely used in scientific...