Abstract
In this paper, we propose two parallel Aggregation-Isolation iterative methods for solving Markov chains. These parallel methods conserves as much as possible the benefits of aggregation, and Gauss-Seidel effects. Some experiments have been conducted testing models from queuing systems and models from Google Page Ranking. The results of the experiments show super linear speed-up for the parallel Aggregation-Isolation method.
| Original language | English |
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| Title of host publication | Proceedings of the 2010 IEEE International Symposium on Parallel and Distributed Processing, Workshops and Phd Forum, IPDPSW 2010 |
| DOIs | |
| Publication status | Published - 2010 |
| Event | 2010 IEEE International Symposium on Parallel and Distributed Processing, Workshops and Phd Forum, IPDPSW 2010 - Atlanta, GA, United States Duration: Apr 19 2010 → Apr 23 2010 |
Other
| Other | 2010 IEEE International Symposium on Parallel and Distributed Processing, Workshops and Phd Forum, IPDPSW 2010 |
|---|---|
| Country | United States |
| City | Atlanta, GA |
| Period | 4/19/10 → 4/23/10 |
ASJC Scopus subject areas
- Computational Theory and Mathematics
- Software
- Theoretical Computer Science
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Cite this
Touzene, A. (2010). Parallel isolation-aggregation algorithms to solve Markov Chains problems with application to page Ranking. In Proceedings of the 2010 IEEE International Symposium on Parallel and Distributed Processing, Workshops and Phd Forum, IPDPSW 2010 [5470779] https://doi.org/10.1109/IPDPSW.2010.5470779