Scheduling In-Situ Analytics in Next-Generation Applications

Oscar H. Mondragon; Patrick G. Bridges; Scott Levy; Kurt B. Ferreira; Patrick Widener

doi:10.1109/CCGrid.2016.42

Scheduling In-Situ Analytics in Next-Generation Applications

Oscar H. Mondragon, Patrick G. Bridges, Scott Levy, Kurt B. Ferreira, Patrick Widener

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

5 Scopus citations

Abstract

Next-generation applications increasingly rely on in situ analytics to guide computation, reduce the amount of I/O performed, and perform other important tasks. Scheduling where and when to run analytics is challenging, however. This paper quantifies the costs and benefits of different approaches to scheduling applications and analytics on nodes in large-scale applications, including space sharing, uncoordinated time sharing, and gang scheduled time sharing.

Original language	English
Title of host publication	Proceedings - 2016 16th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing, CCGrid 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	102-105
Number of pages	4
ISBN (Electronic)	9781509024520
DOIs	https://doi.org/10.1109/CCGrid.2016.42
State	Published - Jul 18 2016
Externally published	Yes
Event	16th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing, CCGrid 2016 - Cartagena, Colombia Duration: May 16 2016 → May 19 2016

Publication series

Name	Proceedings - 2016 16th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing, CCGrid 2016

Conference

Conference	16th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing, CCGrid 2016
Country/Territory	Colombia
City	Cartagena
Period	05/16/16 → 05/19/16

Funding

The authors would like to thank Jai Dayal and Terry Jones for their input on different approaches to running and scheduling in situ analytics and gang scheduling in HPC systems. This work is supported in part by the 2013 Exascale Operating and Runtime Systems Program from the DOE Office of Science, Advanced Scientific Computing Research, under award number DE-SC0005050, program manager Sonia Sachs, and by the Colciencias-Fulbright Colombia and The Universidad Autonoma de Occidente through the Caldas scholarships program.

Funders	Funder number
Colciencias-Fulbright Colombia and The Universidad Autonoma de Occidente
Office of Science
Advanced Scientific Computing Research	DE-SC0005050

Keywords

Exascale applications
composed applications
in-situ
performance interference
resource sharing

Access to Document

10.1109/CCGrid.2016.42

Cite this

Mondragon, O. H., Bridges, P. G., Levy, S., Ferreira, K. B., & Widener, P. (2016). Scheduling In-Situ Analytics in Next-Generation Applications. In Proceedings - 2016 16th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing, CCGrid 2016 (pp. 102-105). Article 7515676 (Proceedings - 2016 16th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing, CCGrid 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CCGrid.2016.42

Mondragon, Oscar H. ; Bridges, Patrick G. ; Levy, Scott et al. / Scheduling In-Situ Analytics in Next-Generation Applications. Proceedings - 2016 16th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing, CCGrid 2016. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 102-105 (Proceedings - 2016 16th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing, CCGrid 2016).

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title = "Scheduling In-Situ Analytics in Next-Generation Applications",

abstract = "Next-generation applications increasingly rely on in situ analytics to guide computation, reduce the amount of I/O performed, and perform other important tasks. Scheduling where and when to run analytics is challenging, however. This paper quantifies the costs and benefits of different approaches to scheduling applications and analytics on nodes in large-scale applications, including space sharing, uncoordinated time sharing, and gang scheduled time sharing.",

keywords = "Exascale applications, composed applications, in-situ, performance interference, resource sharing",

author = "Mondragon, {Oscar H.} and Bridges, {Patrick G.} and Scott Levy and Ferreira, {Kurt B.} and Patrick Widener",

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language = "English",

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Mondragon, OH, Bridges, PG, Levy, S, Ferreira, KB & Widener, P 2016, Scheduling In-Situ Analytics in Next-Generation Applications. in Proceedings - 2016 16th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing, CCGrid 2016., 7515676, Proceedings - 2016 16th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing, CCGrid 2016, Institute of Electrical and Electronics Engineers Inc., pp. 102-105, 16th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing, CCGrid 2016, Cartagena, Colombia, 05/16/16. https://doi.org/10.1109/CCGrid.2016.42

Scheduling In-Situ Analytics in Next-Generation Applications. / Mondragon, Oscar H.; Bridges, Patrick G.; Levy, Scott et al.
Proceedings - 2016 16th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing, CCGrid 2016. Institute of Electrical and Electronics Engineers Inc., 2016. p. 102-105 7515676 (Proceedings - 2016 16th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing, CCGrid 2016).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Mondragon OH, Bridges PG, Levy S, Ferreira KB, Widener P. Scheduling In-Situ Analytics in Next-Generation Applications. In Proceedings - 2016 16th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing, CCGrid 2016. Institute of Electrical and Electronics Engineers Inc. 2016. p. 102-105. 7515676. (Proceedings - 2016 16th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing, CCGrid 2016). doi: 10.1109/CCGrid.2016.42

Scheduling In-Situ Analytics in Next-Generation Applications

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Keywords

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