Managing computational gateway resources with XDMoD

Jeanette M. Sperhac; Robert L. DeLeon; Thomas R. Furlani; Steven M. Gallo; Martins Innus; Matthew D. Jones; Jeffrey T. Palmer; Abani Patra; Benjamin D. Plessinger; Ryan Rathsam; Nikolay Simakov; Joseph P. White; Rudra Chakraborty; Gregary Dean

doi:10.1016/j.future.2019.03.029

Managing computational gateway resources with XDMoD

Jeanette M. Sperhac
, Robert L. DeLeon
, Thomas R. Furlani
, Steven M. Gallo
, Martins Innus
, Matthew D. Jones
, Jeffrey T. Palmer
, Abani Patra
, Benjamin D. Plessinger
, Ryan Rathsam
, Nikolay Simakov
, Joseph P. White
, Rudra Chakraborty
, Gregary Dean

Center for Computational Research

SUNY Buffalo

Research output: Contribution to journal › Article › peer-review

3 Scopus citations

Abstract

The U.S. National Science Foundation (NSF) has invested heavily in research computing, funding the XSEDE network of supercomputers and enabling their integration with science gateways. To ensure maximal return on this substantial investment, it is essential to monitor the use of these computing resources. XD Metrics on Demand (XDMoD) is an NSF-funded tool that was developed to help manage high performance computational resources. XDMoD metrics describe accounting and performance data for computational jobs, including resources consumed, wait times, and quality of service. XDMoD can provide information on individual jobs, or data aggregated over an ensemble of jobs. Its web interface offers centralized charting, exploration, and reporting of these metrics, for user-selected time ranges, and across resources. XDMoD is directly relevant to the gateways community. In this paper, we introduce XDMoD, demonstrate its utility for gateways, and outline our plans to further enhance its capabilities for the gateways community. Furthermore, we demonstrate how XDMoD can help gateway users and gateway and resource managers answer many questions about utilization, performance, and availability. In doing so, we showcase the evolution of gateways in the XSEDE ecosystem.

Original language	English
Pages (from-to)	154-166
Number of pages	13
Journal	Future Generation Computer Systems
Volume	98
DOIs	https://doi.org/10.1016/j.future.2019.03.029
State	Published - Sep 2019

Keywords

High performance computing
Monitoring
Science gateways

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10.1016/j.future.2019.03.029

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title = "Managing computational gateway resources with XDMoD",

abstract = "The U.S. National Science Foundation (NSF) has invested heavily in research computing, funding the XSEDE network of supercomputers and enabling their integration with science gateways. To ensure maximal return on this substantial investment, it is essential to monitor the use of these computing resources. XD Metrics on Demand (XDMoD) is an NSF-funded tool that was developed to help manage high performance computational resources. XDMoD metrics describe accounting and performance data for computational jobs, including resources consumed, wait times, and quality of service. XDMoD can provide information on individual jobs, or data aggregated over an ensemble of jobs. Its web interface offers centralized charting, exploration, and reporting of these metrics, for user-selected time ranges, and across resources. XDMoD is directly relevant to the gateways community. In this paper, we introduce XDMoD, demonstrate its utility for gateways, and outline our plans to further enhance its capabilities for the gateways community. Furthermore, we demonstrate how XDMoD can help gateway users and gateway and resource managers answer many questions about utilization, performance, and availability. In doing so, we showcase the evolution of gateways in the XSEDE ecosystem.",

keywords = "High performance computing, Monitoring, Science gateways",

author = "Sperhac, \{Jeanette M.\} and DeLeon, \{Robert L.\} and Furlani, \{Thomas R.\} and Gallo, \{Steven M.\} and Martins Innus and Jones, \{Matthew D.\} and Palmer, \{Jeffrey T.\} and Abani Patra and Plessinger, \{Benjamin D.\} and Ryan Rathsam and Nikolay Simakov and White, \{Joseph P.\} and Rudra Chakraborty and Gregary Dean",

note = "Publisher Copyright: {\textcopyright} 2019 Elsevier B.V.",

year = "2019",

month = sep,

doi = "10.1016/j.future.2019.03.029",

language = "English",

volume = "98",

pages = "154--166",

journal = "Future Generation Computer Systems",

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AU - Sperhac, Jeanette M.

AU - DeLeon, Robert L.

AU - Furlani, Thomas R.

AU - Gallo, Steven M.

AU - Innus, Martins

AU - Jones, Matthew D.

AU - Palmer, Jeffrey T.

AU - Patra, Abani

AU - Plessinger, Benjamin D.

AU - Rathsam, Ryan

AU - Simakov, Nikolay

AU - White, Joseph P.

AU - Chakraborty, Rudra

AU - Dean, Gregary

PY - 2019/9

Y1 - 2019/9

N2 - The U.S. National Science Foundation (NSF) has invested heavily in research computing, funding the XSEDE network of supercomputers and enabling their integration with science gateways. To ensure maximal return on this substantial investment, it is essential to monitor the use of these computing resources. XD Metrics on Demand (XDMoD) is an NSF-funded tool that was developed to help manage high performance computational resources. XDMoD metrics describe accounting and performance data for computational jobs, including resources consumed, wait times, and quality of service. XDMoD can provide information on individual jobs, or data aggregated over an ensemble of jobs. Its web interface offers centralized charting, exploration, and reporting of these metrics, for user-selected time ranges, and across resources. XDMoD is directly relevant to the gateways community. In this paper, we introduce XDMoD, demonstrate its utility for gateways, and outline our plans to further enhance its capabilities for the gateways community. Furthermore, we demonstrate how XDMoD can help gateway users and gateway and resource managers answer many questions about utilization, performance, and availability. In doing so, we showcase the evolution of gateways in the XSEDE ecosystem.

AB - The U.S. National Science Foundation (NSF) has invested heavily in research computing, funding the XSEDE network of supercomputers and enabling their integration with science gateways. To ensure maximal return on this substantial investment, it is essential to monitor the use of these computing resources. XD Metrics on Demand (XDMoD) is an NSF-funded tool that was developed to help manage high performance computational resources. XDMoD metrics describe accounting and performance data for computational jobs, including resources consumed, wait times, and quality of service. XDMoD can provide information on individual jobs, or data aggregated over an ensemble of jobs. Its web interface offers centralized charting, exploration, and reporting of these metrics, for user-selected time ranges, and across resources. XDMoD is directly relevant to the gateways community. In this paper, we introduce XDMoD, demonstrate its utility for gateways, and outline our plans to further enhance its capabilities for the gateways community. Furthermore, we demonstrate how XDMoD can help gateway users and gateway and resource managers answer many questions about utilization, performance, and availability. In doing so, we showcase the evolution of gateways in the XSEDE ecosystem.

KW - High performance computing

KW - Monitoring

KW - Science gateways

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DO - 10.1016/j.future.2019.03.029

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VL - 98

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EP - 166

JO - Future Generation Computer Systems

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ER -

Managing computational gateway resources with XDMoD

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Keywords

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