Runtime Compression of MPI Messanes to Improve the Performance and Scalability of Parallel Applications

  • Authors:
  • Jian Ke;Martin Burtscher;Evan Speight

  • Affiliations:
  • Cornell University;Cornell University;IBM Austin Research Lab

  • Venue:
  • Proceedings of the 2004 ACM/IEEE conference on Supercomputing
  • Year:
  • 2004

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Abstract

Communication-intensive parallel applications spend a significant amount of their total execution time exchanging data between processes, which leads to poor performance in many cases. In this paper, we investigate message compression in the context of large-scale parallel message-passing systems to reduce the communication time of individual messages and to improve the bandwidth of the overall system. We implement and evaluate the cMPImessage-passing library, which quickly compresses messages on-the-fly with a low enough overhead that a net execution time reduction is obtained. Our results on six large-scale benchmark applications show that their execution speed improves by up to 98% when message compression is enabled.