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Practical Monitoring of Resource Utilization for HPC Applications

Authors:

Antonio Gómez-Iglesias,

Carlos Rosales,

Todd EvansAuthors Info & Claims

XSEDE16: Proceedings of the XSEDE16 Conference on Diversity, Big Data, and Science at Scale

Article No.: 49, Pages 1 - 8

https://doi.org/10.1145/2949550.2949643

Published: 17 July 2016 Publication History

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Abstract

HPC centers run a diverse set of applications from a variety of scientific domains. Every application has different resource requirements, but it is difficult for domain experts to find out what these requirements are and how they impact performance. In particular, the utilization of shared resources such as parallel file systems may influence application performance in significant ways that are not always obvious to the user. We present a tool designed to provide the information that is most critical for running an application efficiently on HPC systems. The information provided forms a complete view of the application's interaction with the system resources, which is typically missing from other profiling and analysis tools. The tool is designed to be scalable and have minimal impact on application performance, and includes support for different accelerators.

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Cited By

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Aggarwal DJoshi HDutta S(2024)Advancements in High Performance Computing Cluster Resource Utilization through a Comprehensive Monitoring Dashboard2024 11th International Conference on Computing for Sustainable Global Development (INDIACom)10.23919/INDIACom61295.2024.10498826(158-165)Online publication date: 28-Feb-2024
https://doi.org/10.23919/INDIACom61295.2024.10498826
Lu CMilfeld K(2023)REMORA Resource Monitor: Usability, Performance and User Interface ImprovementsProceedings of the SC '23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis10.1145/3624062.3624141(663-672)Online publication date: 12-Nov-2023
https://dl.acm.org/doi/10.1145/3624062.3624141
Jiang XBaigalmaa TNguyen LAkiyoshi DRamthun EParajuli NPeck C(2018)High Performance Cluster Monitoring System2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)10.23919/APSIPA.2018.8659536(1188-1193)Online publication date: Nov-2018
https://doi.org/10.23919/APSIPA.2018.8659536

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Published In

XSEDE16: Proceedings of the XSEDE16 Conference on Diversity, Big Data, and Science at Scale

July 2016

405 pages

ISBN:9781450347556

DOI:10.1145/2949550

General Chair:
Kelly Gaither
Texas Advanced Computing Center

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

In-Cooperation

SIGAPP: ACM Special Interest Group on Applied Computing
Xsede: Xsede
San Diego Supercomputer Center: San Diego Supercomputer Center
NICS: National Institute for Computational Sciences
University of Illinois: The University of Illinois at Urbana-Champaign

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Association for Computing Machinery

New York, NY, United States

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Published: 17 July 2016

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XSEDE16

XSEDE16: Diversity, Big Data, and Science at Scale

July 17 - 21, 2016

Miami, USA

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Aggarwal DJoshi HDutta S(2024)Advancements in High Performance Computing Cluster Resource Utilization through a Comprehensive Monitoring Dashboard2024 11th International Conference on Computing for Sustainable Global Development (INDIACom)10.23919/INDIACom61295.2024.10498826(158-165)Online publication date: 28-Feb-2024
https://doi.org/10.23919/INDIACom61295.2024.10498826
Lu CMilfeld K(2023)REMORA Resource Monitor: Usability, Performance and User Interface ImprovementsProceedings of the SC '23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis10.1145/3624062.3624141(663-672)Online publication date: 12-Nov-2023
https://dl.acm.org/doi/10.1145/3624062.3624141
Jiang XBaigalmaa TNguyen LAkiyoshi DRamthun EParajuli NPeck C(2018)High Performance Cluster Monitoring System2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)10.23919/APSIPA.2018.8659536(1188-1193)Online publication date: Nov-2018
https://doi.org/10.23919/APSIPA.2018.8659536

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References

Cited By

Recommendations

Monitoring HPC applications in the production environment

Analyzing Resource Utilization in an HPC System: A Case Study of NERSC’s Perlmutter

Taxonomist: Application Detection Through Rich Monitoring Data

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