arXiv Open Access 2020

Analyzing Performance Properties Collected by the PerSyst Scalable HPC Monitoring Tool

David Brayford Christoph Bernau Wolfram Hesse Carla Guillen

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Abstrak

The ability to understand how a scientific application is executed on a large HPC system is of great importance in allocating resources within the HPC data center. In this paper, we describe how we used system performance data to identify: execution patterns, possible code optimizations and improvements to the system monitoring. We also identify candidates for employing machine learning techniques to predict the performance of similar scientific codes.

Topik & Kata Kunci

cs.DC

Penulis (4)

David Brayford

Christoph Bernau

Wolfram Hesse

Carla Guillen

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APA MLA BibTeX

Brayford, D., Bernau, C., Hesse, W., Guillen, C. (2020). Analyzing Performance Properties Collected by the PerSyst Scalable HPC Monitoring Tool. https://arxiv.org/abs/2009.06061

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Informasi Jurnal

Tahun Terbit: 2020
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓