A Platform Independent Parallelising Tool Based on Graph Theoretic Models
VECPAR '00 Selected Papers and Invited Talks from the 4th International Conference on Vector and Parallel Processing
Region-based hierarchical operation partitioning for multicluster processors
PLDI '03 Proceedings of the ACM SIGPLAN 2003 conference on Programming language design and implementation
Compact DAG representation and its symbolic scheduling
Journal of Parallel and Distributed Computing
Contention-aware scheduling with task duplication
Journal of Parallel and Distributed Computing
Toward better software test estimates and requirement tracking
Journal of Computational Methods in Sciences and Engineering
NewsCast: an adaptive video stream production and delivery system
CASCON '13 Proceedings of the 2013 Conference of the Center for Advanced Studies on Collaborative Research
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In this paper, we present an efficient algorithm, called CASS-II, for task clustering without task duplication. Unlike the DSC algorithm, which is empirically the best known algorithm to date in terms of both speed and solution quality, CASS-II uses only limited ``global'' information and does not recompute the critical path in each refinement step. Therefore, the algorithm runs in $O(|E| + |V| lg |V|)$ which is faster than $O((|V|+|E|)lg |V|)$ of the DSC algorithm. Indeed, our experimental results show that CASS-II is between 3 to 5 times faster than DSC. (It is worth pointing out that we used the C code for DSC developed by the authors of the DSC algorithm. The C code for CASS-II was developed by the authors of this paper.) With respect to solution quality, experimental results show that CASS-II is virtually as good as DSC and, in fact, even outperforms DSC for very fine grain DAGs (granularity less than 0.6).