{"title":"PyTACC: HPC Python at the texas advanced computing center","authors":"R. T. Evans, A. Gómez-Iglesias, W. C. Proctor","doi":"10.1145/2835857.2835861","DOIUrl":null,"url":null,"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.","PeriodicalId":171838,"journal":{"name":"Workshop on Python for High-Performance and Scientific Computing","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Workshop on Python for High-Performance and Scientific Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2835857.2835861","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
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.
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。