Python: High Performance or Not? You Might Be Surprised


The concept of an "accelerated Python" is relatively new, and it's made Python worth another look for Big Data and High Performance Computing (HPC) applications. Thanks to some Python aficionados at Intel, who have utilized the well-known Intel Math Kernel Library (MKL) under the covers, we can all use an accelerated Python that yields big returns for Python performance without requiring that we change our Python code! But Python is relatively slow because it's an interpreted (not a compiled) language. We can learn and explore interactively--including doing a "Hello, World!" program interactively: The reason an "accelerated Python" can be so effective comes from a combination of three factors: Python has mature and widely used packages and libraries: These libraries can be accelerated, without needing to change our Python code at all. All we have to do is install an accelerated Python.