Accelerating large scale image analyses on parallel, CPU-GPU equipped systems

George Teodoro*, Tahsin M. Kurc, Tony Pan, Lee Alex Donald Cooper, Jun Kong, Patrick Widener, Joel H. Saltz

*Corresponding author for this work

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

23 Scopus citations

Abstract

The past decade has witnessed a major paradigm shift in high performance computing with the introduction of accelerators as general purpose processors. These computing devices make available very high parallel computing power at low cost and power consumption, transforming current high performance platforms into heterogeneous CPU-GPU equipped systems. Although the theoretical performance achieved by these hybrid systems is impressive, taking practical advantage of this computing power remains a very challenging problem. Most applications are still deployed to either GPU or CPU, leaving the other resource under- or un-utilized. In this paper, we propose, implement, and evaluate a performance aware scheduling technique along with optimizations to make efficient collaborative use of CPUs and GPUs on a parallel system. In the context of feature computations in large scale image analysis applications, our evaluations show that intelligently co-scheduling CPUs and GPUs can significantly improve performance over GPU-only or multi-core CPU-only approaches.

Original languageEnglish (US)
Title of host publicationProceedings of the 2012 IEEE 26th International Parallel and Distributed Processing Symposium, IPDPS 2012
Pages1093-1104
Number of pages12
DOIs
StatePublished - 2012
Event2012 IEEE 26th International Parallel and Distributed Processing Symposium, IPDPS 2012 - Shanghai, China
Duration: May 21 2012May 25 2012

Publication series

NameProceedings of the 2012 IEEE 26th International Parallel and Distributed Processing Symposium, IPDPS 2012

Other

Other2012 IEEE 26th International Parallel and Distributed Processing Symposium, IPDPS 2012
CountryChina
CityShanghai
Period5/21/125/25/12

Keywords

  • CPU-GPU systems
  • Image analysis
  • In Silico
  • Microscopy

ASJC Scopus subject areas

  • Software

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