A map-reduce based framework for heterogeneous processing element cluster environments

Yu Shyang Tan, Bu Sung Lee, Bingsheng He, Roy H. Campbell

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

Abstract

In this paper, we present our design of a Processing Element (PE) Aware MapReduce base framework, Pamar. Pamar is designed for supporting distributed computing on clusters where node PE configurations are asymmetric on different nodes. Pamar's main goal is to allow users to seamlessly utilize different kinds of processing elements (e.g., CPUs or GPUs) collaboratively for large scale data processing. To show proof of concept, we have incorporated our designs into the Hadoop framework and tested it on cluster environments having asymmetric node PE configurations. We demonstrate Pamar's ability to identify PEs available on each node and match-make user jobs with nodes, base on job PE requirements. Pamar allows users to easily parallelize applications across large datasets and at the same time utilizes different PEs for processing different classes of functions efficiently. The experiments show improvement in job queue completion time with Pamar over clusters with asymmetric nodes as compared to clusters with symmetric nodes.

Original languageEnglish (US)
Title of host publicationProceedings - 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGrid 2012
Pages57-64
Number of pages8
DOIs
StatePublished - Jul 16 2012
Event12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGrid 2012 - Ottawa, ON, Canada
Duration: May 13 2012May 16 2012

Publication series

NameProceedings - 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGrid 2012

Other

Other12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGrid 2012
CountryCanada
CityOttawa, ON
Period5/13/125/16/12

Keywords

  • GPGPU
  • Heterogeneous resource framework
  • MapReduce

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Applied Mathematics

Fingerprint Dive into the research topics of 'A map-reduce based framework for heterogeneous processing element cluster environments'. Together they form a unique fingerprint.

Cite this