TY  - CHAP
U1  - Konferenzveröffentlichung
A1  - Keuper, Janis
A1  - Straßel, Dominik
A1  - Reusch, Philipp
T1  - Python Workflows on HPC Systems
T2  - Proceedings of PYHPC 2020: 9th Workshop on Python for High-Performance and Scientific Computing
N2  - 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 multiuser environments or parallel programming - making it quite challenging to maintain stable and secure Python workflows on a HPC system. In this paper, we analyze the key problems induced by the usage of Python on HPC clusters and sketch appropriate workarounds for efficiently maintaining multi-user Python software environments, securing and restricting resources of Python jobs and containing Python processes, while focusing on Deep Learning applications running on GPU clusters.
Y1  - 2020
SN  - 978-0-7381-1086-8 (digital)
SB  - 978-0-7381-1086-8 (digital)
SN  - 978-0-7381-1087-5 (Print on Demand)
SB  - 978-0-7381-1087-5 (Print on Demand)
U6  - https://doi.org/10.1109/PyHPC51966.2020.00009
DO  - https://doi.org/10.1109/PyHPC51966.2020.00009
SP  - 32
EP  - 40
PB  - IEEE
ER  -