Python at TACC
Chris Myers, Andrew Dolgert (original author)
Cornell Center for Advanced Computing
Revisions: 6/2023, 5/2020, 8/2018, 6/2015, 5/2011 (original)
The preceding sections have addressed topics in Python for High Performance that are generally applicable across a variety of different systems and architectures. We address here specifically how to use Python on the Frontera supercomputer at TACC. In addition, the Frontera User Guide is always a good place to go for further information, as is our companion roadmap on Getting Started on Frontera.
Objectives
After completing this topic, you should be able to:
- Understand how to access and configure Python programs on TACC systems such as Frontera
- Identify what Python packages and versions are installed on Frontera at TACC
- Describe useful approaches for configuring code for improved performance on Frontera
Prerequisites
As this topic focuses on accelerating Python programs for scientific computing, it implicitly assumes the reader has some prior experience programming in Python, as well as working knowledge of general programming concepts. The target audience is scientists and engineers who are already programming in Python, and are interested in using Python tools and packages to improve the run time performance of the programs they are developing. If additional introductory material about Python is needed, readers can consult Introduction to Python Programming as well as the documentation on the python.org website. If you wish to run python on the Frontera system at TACC, you will need an allocation to run there.