Optimization of Software on High Performance Computing Platforms for the LUX-ZEPLIN Dark Matter Experiment

Venkitesh Ayyar; Wahid Bhimji; Maria Elena Monzani; Andrew Naylor; Simon Patton; Craig E. Tull

doi:10.1051/epjconf/202024505012

Optimization of Software on High Performance Computing Platforms for the LUX-ZEPLIN Dark Matter Experiment

Computational Physics 2020-12-08 v1 High Energy Physics - Experiment

Authors: Venkitesh Ayyar , Wahid Bhimji , Maria Elena Monzani , Andrew Naylor , Simon Patton , Craig E. Tull

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Abstract

High Energy Physics experiments like the LUX-ZEPLIN dark matter experiment face unique challenges when running their computation on High Performance Computing resources. In this paper, we describe some strategies to optimize memory usage of simulation codes with the help of profiling tools. We employed this approach and achieved memory reduction of 10-30\%. While this has been performed in the context of the LZ experiment, it has wider applicability to other HEP experimental codes that face these challenges on modern computer architectures.

Keywords

graphics processing unit computing computational physics software computational optimization

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@article{arxiv.2002.06304,
  title  = {Optimization of Software on High Performance Computing Platforms for the LUX-ZEPLIN Dark Matter Experiment},
  author = {Venkitesh Ayyar and Wahid Bhimji and Maria Elena Monzani and Andrew Naylor and Simon Patton and Craig E. Tull},
  journal= {arXiv preprint arXiv:2002.06304},
  year   = {2020}
}

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Contribution to Proceedings of CHEP 2019, Nov 4-8, Adelaide, Australia

Optimization of Software on High Performance Computing Platforms for the LUX-ZEPLIN Dark Matter Experiment

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