Parallel ‘go with the winners’ algorithms in distributed memory models

We parallelize the ‘go with the winners’ algorithm of Aldous and Vazirani (in: Proceedings of the 35th IEEE Symposium on the Foundations of Computer Science, IEEE Computer Society Press, Silver Spring., MD, 1994, pp. 492–501) and analyze the resulting parallel algorithm in the LogP-model (in: Procee...

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Veröffentlicht in:Journal of parallel and distributed computing Jg. 63; H. 9; S. 801 - 814
Hauptverfasser: Peinado, Marcus, Lengauer, Thomas
Format: Journal Article
Sprache:Englisch
Veröffentlicht: San Diego, CA Elsevier Inc 01.09.2003
Elsevier
Schlagworte:
Algorithmics. Computability. Computer arithmetics
Amorphous solids
Applied sciences
Computer science; control theory; systems
Computer systems and distributed systems. User interface
Exact sciences and technology
Go with the winners
Load balancing
LogP model
Parallel algorithms
Second moment method
Self-avoiding walks
Software
Theoretical computing
LogP model
Amorphous solids
Second moment method
Go with the winners
Self-avoiding walks
Load balancing
Parallel algorithms
Parallel algorithm
Second moment
Distributed memory
Parallel programming
Distributed algorithm
Self avoiding walk
LogP model: Second moment method
Shared memory
Algorithm analysis
ISSN:0743-7315, 1096-0848
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Zusammenfassung:We parallelize the ‘go with the winners’ algorithm of Aldous and Vazirani (in: Proceedings of the 35th IEEE Symposium on the Foundations of Computer Science, IEEE Computer Society Press, Silver Spring., MD, 1994, pp. 492–501) and analyze the resulting parallel algorithm in the LogP-model (in: Proceedings of the Fourth ACM SIGPLAN Symposium on Principles & Practice of Parallel Programming, 1993, pp. 1–12). The main issues in the analysis are load imbalances and communication delays. The result of the analysis is a practical algorithm which, under reasonable assumptions, achieves linear speedup. Finally, we analyze our algorithm for a concrete application: generating models of amorphous chemical structures.
ISSN:0743-7315
1096-0848
DOI:10.1016/S0743-7315(03)00109-6