In high performance computing, there are a variety of software packages and programming languages with which to conduct scientific research. Although each software package and each programming language has its pros and cons, Python is one that offers a great balance of performance, flexibility and ease-of-use. 

In this three-day virtual workshop, we will explore how to use Python on HPC platforms.

• On day one (April 12, 10:30 am – 12pm), we will go over the basics of HPC@Mines, and give a brief introduction to Python.
• On day two (April 13, 10:30 am – 12pm), we will focus on how to setup a Python environment on our HPC systems and compare its capability as a Matlab alternative using Numpy, Scipy, and Matplotlib with Jupyter Notebooks.
• On day three (April 14, 10:30 am – 12pm), we will explore how to use Python as a distributed-memory programming language using mpi4py and petsc4py, and as a glue for routines from lower-level languages such as C.

In this workshop series, we will use Anaconda, a python distribution which packages several Python scientific modules. As a pre-workshop assignment, you will be required to download and install Anaconda on your machine. It is supported on major platforms. 

If you have issues installing, please reach out to Nicholas Danes at ndanes@mines.edu