The Effect of System Utilization on Application Performance Variability-Reference-Cited by-同舟云学术

The Effect of System Utilization on Application Performance Variability

Published:2019 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 9th International Workshop on Runtime and Operating Systems for Supercomputers - ROSS '19
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Author:

Li Boyang¹,Chunduri Sudheer²,Harms Kevin²,Fan Yuping¹,Lan Zhiling¹

Affiliation:

1. Illinois Institute of Technology, Chicago, IL, USA

2. Argonne National Laboratory, Lemont, IL, USA

Funder

US National Science Foundation

U.S. Department of Energy

Publisher

ACM Press

Reference21 articles.

1. William Allcock, Paul Rich, Yuping Fan, and Zhiling Lan. 2017. Experience and Practice of Batch Scheduling on Leadership Supercomputers at Argonne. In Workshop on Job Scheduling Strategies for Parallel Processing (JSSPP) .

2. Abhinav Bhatele, Nikhil Jain, Yarden Livnat, Valerio Pascucci, and Peer-Timo Bremer. 2016. Analyzing network health and congestion in dragonfly-based supercomputers. In Parallel and Distributed Processing Symposium, 2016 IEEE International. IEEE, 93--102.

3. Abhinav Bhatele, Kathryn Mohror, Steven~H Langer, and Katherine~E Isaacs. 2013. There goes the neighborhood: performance degradation due to nearby jobs. In Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis. ACM, 41.

4. Sudheer Chunduri, Kevin Harms, Scott Parker, Vitali Morozov, Samuel Oshin, Naveen Cherukuri, and Kalyan Kumaran. 2017. Run-to-run variability on Xeon Phi based Cray XC systems. In Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis. ACM, 52.

5. Wayne W Daniel and Chad L Cross. 2012. Biostatistics: a Foundation for Analysis in the health sciences .Wiley Global Education.

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