Principles for Automated and Reproducible Benchmarking-Reference-Cited by-同舟云学术

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Principles for Automated and Reproducible Benchmarking

Published:2023-11-12 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the SC '23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis
language:
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Author:

Koskela Tuomas¹^ORCID,Christidi Ilektra¹^ORCID,Giordano Mosè¹^ORCID,Dubrovska Emily¹^ORCID,Quinn Jamie¹^ORCID,Maynard Christopher²^ORCID,Case Dave³^ORCID,Olgu Kaan⁴^ORCID,Deakin Tom⁴^ORCID

Affiliation:

1. Advanced Research Computing, University College London, United Kingdom

2. University of Reading, United Kingdom and Met Office, UK, United Kingdom

3. National Centre for Atmospheric Science (NCAS), UK, United Kingdom and University of Reading, United Kingdom

4. University of Bristol, United Kingdom

Funder

UK Research and Innovation

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3624062.3624133

Reference26 articles.

1. LFRic: Meeting the challenges of scalability and performance portability in Weather and Climate models

2. Twelve ways to fool the masses when giving performance results on parallel computers;Bailey H.;Supercomputing Review,1991

3. Bokeh Development Team . 2018 . Bokeh: Python library for interactive visualization. Bokeh Contributors. https://bokeh.pydata.org/en/latest/ Bokeh Development Team. 2018. Bokeh: Python library for interactive visualization. Bokeh Contributors. https://bokeh.pydata.org/en/latest/

4. First Experiences in Performance Benchmarking with the New SPEChpc 2021 Suites

5. Performance Portability across Diverse Computer Architectures

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