Paper Info
Title
Scalable Communication-Aware Task Mapping Algorithms for Interconnected Multicore Systems
Abstract
Communication-aware task mapping algorithms, which map parallel tasks onto processing nodes according to the communication patterns of applications, are essential to reduce the communication time in modern high performance computing. In this paper, we design algorithms specifically for interconnected multicore systems, whose architectural property, namely small number of cores per node, large number of nodes, and large performance gap between the communication within a multicore and among multicores, had brought new challenges and opportunities to the mapping problem. Let k be the number of cores per multicore and n be the number of tasks. We consider the practical case that k is much smaller than n, for k = 2, 4, and 6. The designed algorithms are optimal for the mapping measurement, called Maximum Interconnective Message Size (MIMS), and of time complexity merely O(mlogm) for m communication pairs. Thus, they are highly scalable for large applications. We had experimented the algorithms on the IBM Blue Gene/P system for two synthetic benchmarks and two applications. The results show good communication performance improvement.
Year
DOI
Venue
2011
10.1109/IPDPSW.2012.9
IPDPSW '12 Proceedings of the 2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops & PhD Forum
Keywords
DocType
ISSN
scalable communication-aware task,mapping measurement,communication pattern,mapping algorithms,small number,m communication pair,large application,communication time,communication-aware task mapping algorithm,good communication performance improvement,large number,large performance gap,interconnected multicore systems,computational complexity
Conference
2164-7062
Citations 
PageRank 
References 
1
0.37
10
Authors
4
Name
Order
Citations
PageRank
I-hsin Chung138832.41
Che-Rung Lee27813.52
Jiazheng Zhou3345.35
Yeh-Ching Chung498397.16