Irregular Redistribution Scheduling by Partitioning Messages [chapter]

Chang Wu Yu, Ching-Hsien Hsu, Kun-Ming Yu, C. -K. Liang, Chun-I Chen
<span title="">2005</span> <i title="Springer Berlin Heidelberg"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2w3awgokqne6te4nvlofavy5a4" style="color: black;">Lecture Notes in Computer Science</a> </i> &nbsp;
Dynamic data redistribution enhances data locality and improves algorithm performance for numerous scientific problems on distributed memory multi-computers systems. Previous results focus on reducing index computational cost, schedule computational cost, and message packing/unpacking cost. In irregular redistribution, however, messages with varying sizes are transmitted in the same communication step. Therefore, the largest sized messages in the same communication step dominate the data
more &raquo; ... r time required for this communication step. This work presents an efficient algorithm to partition large messages into multiple small ones and schedules them by using the minimum number of steps without communication contention and, in doing so, reducing the overall redistribution time. When the number of processors or the maximum degree of the redistribution graph increases or the selected size of messages is medium, the proposed algorithm can significantly reduce the overall redistribution time to 52%.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/11572961_24">doi:10.1007/11572961_24</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/2lpuebmb2vd7zgkcpns2sstaje">fatcat:2lpuebmb2vd7zgkcpns2sstaje</a> </span>
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