Data-Localization Scheduling inside Processor-Cluster for Multigrain Parallel Processing

Akimasa YOSHIDA  Ken'ichi KOSHIZUKA  Wataru OGATA  Hironori KASAHARA  

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E80-D   No.4   pp.473-479
Publication Date: 1997/04/25
Online ISSN: 
DOI: 
Print ISSN: 0916-8532
Type of Manuscript: Special Section PAPER (Special Issue on Parallel and Distributed Supercomputing)
Category: 
Keyword: 
task scheduling,  data-localization,  automatic data decomposition,  multigrain parallel processing,  parallelizing compilers,  

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Summary: 
This paper proposes a data-localization scheduling scheme inside a processor-cluster for multigrain parallel processing, which hierarchically exploits parallelism among coarsegrain tasks like loops, medium-grain tasks like loop iterations and near-fine-grain tasks like statements. The proposed scheme assigns near-fine-grain or medium-grain tasks inside coarse-grain tasks onto processors inside a processor-cluster so that maximum parallelism can be exploited and inter-processor data transfer can be minimum after data-localization for coarse-grain tasks across processor-clusters. Performance evaluation on a multiprocessor system OSCAR shows that multigrain parallel processing with the proposed data-localization scheduling can reduce execution time for application programs by 10% compared with multigrain parallel processing without data-localization.