Using location dependence to manage mobile data
Daniel Crawl, Joseph Dunn, et al.
MobiQuitous 2006
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 messagepassing systems to reduce the communication time of individual messages and to improve the bandwidth of the overall system. We implement and evaluate the cMPI message-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. © 2004 IEEE.
Daniel Crawl, Joseph Dunn, et al.
MobiQuitous 2006
Hazim Shafi, Evan Speight, et al.
SRDS 2003
Song Peng, Evan Speight
IPDPS 2004
Milind Kulkarni, Martin Burtscher, et al.
PPoPP 2009