PyTACC:得克萨斯高级计算中心的HPC Python

R. T. Evans, A. Gómez-Iglesias, W. C. Proctor
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引用次数: 2

摘要

德克萨斯高级计算中心(Texas Advanced Computing Center, TACC)基于python的应用程序消耗了我们的计算资源中相当大且不断增长的一部分。为了满足这种需求,TACC开发了一种方法,为用户提供一个健壮、高性能和灵活的Python生态系统。由于其复杂的系统环境和多样化的用户基础,诸如TACC这样的高性能计算中心在支持Python时具有独特的关注点:维护和跟踪多个Python版本/发行版/编译器库和相关软件包的使用情况,以与我们的系统兼容并易于用户使用的方式部署该软件,优化软件以最大化科学贯穿,以及用户支持和教育。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PyTACC: HPC Python at the texas advanced computing center
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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