Reducing the Impact of I/O Contention in Numerical Weather Prediction Workflows at Scale Using DAOS-Reference-Cited by-同舟云学术

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Reducing the Impact of I/O Contention in Numerical Weather Prediction Workflows at Scale Using DAOS

Published:2024-06-03 Issue: Volume:7 Page:1-12
ISSN:
Container-title:Proceedings of the Platform for Advanced Scientific Computing Conference
language:
Short-container-title:

Author:

Manubens Nicolau¹²^ORCID,Smart Simon D.³^ORCID,Danovaro Emanuele³^ORCID,Quintino Tiago³^ORCID,Jackson Adrian²^ORCID

Affiliation:

1. ECMWF, Bonn, Germany

2. EPCC, Edinburgh, United Kingdom

3. ECMWF, Reading, United Kingdom

Funder

DE3100

Publisher

ACM

Reference38 articles.

1. "About Our Forecasts" 2024. https://www.ecmwf.int/en/forecasts/documentation-and-support

2. The quiet revolution of numerical weather prediction

3. "Lustre Best Practices" 2024. https://www.nas.nasa.gov/hecc/support/kb/lustre-best-practices_226.html

4. "The Open Group Base Specifications Issue 7, 2018 edition", 2024. https://pubs.opengroup.org/onlinepubs/9699919799.2018edition/

5. G. Lockwood, "What's so bad about POSIX I/O?". The Next Platform 2017. https://www.nextplatform.com/2017/09/11/whats-bad-posix-io/

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