Python Workflows on HPC Systems

The recent successes and wide spread application of compute intensive machine learning and data analytics methods have been boosting the usage of the Python programming language on HPC systems. While Python provides many advantages for the users, it has not been designed with a focus on multi-user e...

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Veröffentlicht in:	2020 IEEE/ACM 9th Workshop on Python for High-Performance and Scientific Computing (PyHPC) S. 32 - 40
Hauptverfasser:	Strasel, Dominik, Reusch, Philipp, Keuper, Janis
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 01.11.2020
Schlagworte:	compute intensive machine learning data analysis data analytics data analytics methods data structures deep learning Deep Learning applications Graphics processing units high performance computing HPC clusters HPC system Kernel learning (artificial intelligence) Linux Machine learning multiuser environments multiuser Python software environments parallel processing parallel programming Python Python jobs Python programming language recent successes secure Python workflows Software software performance evaluation stable Python workflows wide spread application
Online-Zugang:	Volltext
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