Quartile and outlier detection on heterogeneous clusters using distributed radix sort

Kyle L. Spafford, Jeremy S. Meredith, Jeffrey S. Vetter

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Scopus citations

Abstract

In the past few years, performance improvements in CPUs and memory technologies have outpaced those of storage systems. When extrapolated to the exascale, this trend places strict limits on the amount of data that can be written to disk for full analysis, resulting in an increased reliance on characterizing in-memory data. Many of these characterizations are simple, but require sorted data. This paper explores an example of this type of characterization - the identification of quartiles and statistical outliers - and presents a performance analysis of a distributed heterogeneous radix sort as well as an assessment of current architectural bottlenecks.

Original languageEnglish
Title of host publicationProceedings - 2011 IEEE International Conference on Cluster Computing, CLUSTER 2011
Pages412-419
Number of pages8
DOIs
StatePublished - 2011
Event2011 IEEE International Conference on Cluster Computing, CLUSTER 2011 - Austin, TX, United States
Duration: Sep 26 2011Sep 30 2011

Publication series

NameProceedings - IEEE International Conference on Cluster Computing, ICCC
ISSN (Print)1552-5244

Conference

Conference2011 IEEE International Conference on Cluster Computing, CLUSTER 2011
Country/TerritoryUnited States
CityAustin, TX
Period09/26/1109/30/11

Keywords

  • GPUs
  • performance analysis
  • sorting

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