Identifying the Culprits behind Network Congestion

Abhinav Bhatele, Andrew R. Titus, Jayaraman J. Thiagarajan, Nikhil Jain, Todd Gamblin, Peer Timo Bremer, Martin Schulz, Laxmikant V. Kale

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Network congestion is one of the primary causes of performance degradation, performance variability and poor scaling in communication-heavy parallel applications. However, the causes and mechanisms of network congestion on modern interconnection networks are not well understood. We need new approaches to analyze, model and predict this critical behaviour in order to improve the performance of large-scale parallel applications. This paper applies supervised learning algorithms, such as forests of extremely randomized trees and gradient boosted regression trees, to perform regression analysis on communication data and application execution time. Using data derived from multiple executions, we create models to predict the execution time of communication-heavy parallel applications. This analysis also identifies the features and associated hardware components that have the most impact on network congestion and intern, on execution time. The ideas presented in this paper have wide applicability: predicting the execution time on a different number of nodes, or different input datasets, or even for an unknown code, identifying the best configuration parameters for an application, and finding the root causes of network congestion on different architectures.

Original languageEnglish (US)
Title of host publicationProceedings - 2015 IEEE 29th International Parallel and Distributed Processing Symposium, IPDPS 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages113-122
Number of pages10
ISBN (Electronic)9781479986484
DOIs
StatePublished - Jul 17 2015
Event29th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2015 - Hyderabad, India
Duration: May 25 2015May 29 2015

Publication series

NameProceedings - 2015 IEEE 29th International Parallel and Distributed Processing Symposium, IPDPS 2015

Other

Other29th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2015
CountryIndia
CityHyderabad
Period5/25/155/29/15

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Keywords

  • congestion
  • interconnection network
  • machine learning
  • modeling
  • performance prediction
  • root cause

ASJC Scopus subject areas

  • Computer Networks and Communications

Cite this

Bhatele, A., Titus, A. R., Thiagarajan, J. J., Jain, N., Gamblin, T., Bremer, P. T., Schulz, M., & Kale, L. V. (2015). Identifying the Culprits behind Network Congestion. In Proceedings - 2015 IEEE 29th International Parallel and Distributed Processing Symposium, IPDPS 2015 (pp. 113-122). [7161501] (Proceedings - 2015 IEEE 29th International Parallel and Distributed Processing Symposium, IPDPS 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IPDPS.2015.92