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PyTACC: HPC Python at the texas advanced computing center

Published: 15 November 2015 Publication History

Abstract

Python-based applications at the Texas Advanced Computing Center (TACC) consume a significant and growing fraction of our computational resources. To meet this demand, TACC has developed an approach to provide its users a robust, performant, and flexible Python ecosystem. HPC Centers such as TACC have unique concerns when supporting Python due to their complex system environments and diverse user base: maintenance and usage tracking of multiple Python versions/distributions/compiler-bases and associated packages, deployment of this software in a manner that is compatible with our systems and readily usable to our users, optimization of the software to maximize scientific throughout, and user support and education.

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"Lmod: An Environment Module System based on Lua, Reads TCL Modules, Supports a Software Hierarchy," https://github.com/TACC/Lmod, 2015, {Online; accessed 22-Sep-2015}.
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Cited By

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  • (2020)Demystifying Python Package Installation with conda-env-mod2020 IEEE/ACM International Workshop on HPC User Support Tools (HUST) and Workshop on Programming and Performance Visualization Tools (ProTools)10.1109/HUSTProtools51951.2020.00011(27-37)Online publication date: Nov-2020

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cover image ACM Conferences
PyHPC '15: Proceedings of the 5th Workshop on Python for High-Performance and Scientific Computing
November 2015
59 pages
ISBN:9781450340106
DOI:10.1145/2835857
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 15 November 2015

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PyHPC '15 Paper Acceptance Rate 7 of 7 submissions, 100%;
Overall Acceptance Rate 7 of 7 submissions, 100%

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  • (2020)Demystifying Python Package Installation with conda-env-mod2020 IEEE/ACM International Workshop on HPC User Support Tools (HUST) and Workshop on Programming and Performance Visualization Tools (ProTools)10.1109/HUSTProtools51951.2020.00011(27-37)Online publication date: Nov-2020

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