Junction tree decomposition for parallel exact inference

IPDPS Miami 2008 - Proceedings of the 22nd IEEE International Parallel and Distributed Processing Symposium, Program and CD-ROM

Volumn , Issue , 2008, Pages

  Xia, Yinglong ^a   Prasanna, Viktor K ^a  

^a University of Southern California   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BOOLEAN FUNCTIONS; CHLORINE COMPOUNDS; COMPUTER NETWORKS; DISTRIBUTED PARAMETER NETWORKS; TREES (MATHEMATICS);

EVIDENCE PROPAGATION; EXACT INFERENCE;

PARALLEL ALGORITHMS;

EID: 51049098148     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IPDPS.2008.4536315     Document Type: Conference Paper

References (18)

1. D. Bader. High-performance algorithm engineering for large-scale graph problems and computational biology. In 4th International Workshop on Efficient and Experimental Algorithms, pages 16-21, 2005.
2. R. Biswas, B. Hendrickson, and G. Karypis. Graph partitioning and parallel computing. In Parallel Computing, volume 12, pages 1515-1517, 2000.
3. D. Heckerman. Bayesian networks for data mining. In In Data Mining and Knowledge Discovery, 1997.
4. Y.-S. Hwang and J. H. Saltz. Identifying parallelism in programs with cyclic graphs. Journal of Parallel and Distributed Computing, 63(3):337-355, 2003.
5. Intel Open Source Probabilistic Networks Library. http://www.intel.com/ technology/computing/pnl/.
6. L. V. Kale, B. H. Richards, and T. D. Allen. Efficient parallel graph coloring with prioritization. In Lecture Notes in Computer Science, volume 1068, pages 190-208. 1995.
7. A. V. Kozlov and J. P. Singh. A parallel Lauritzen-Spiegelhalter algorithm for probabilistic inference. In Supercomputing, pages 320-329, 1994.
8. S. L. Lauritzen and D. J. Spiegelhalter. Local computation with probabilities and graphical structures and their application to expert systems. J. Royal Statistical Society B, 50:157-224, 1988.
9. V. K. Namasivayam, A. Pathak, and V. K. Prasanna. Scalable parallel implementation of Bayesian network to junction tree conversion for exact inference. In Proceedings of the 18th International Symposium on Computer Architecture and High Performance Computing, pages 167-176, 2006.
10. V. K. Namasivayam and V. K. Prasanna. Scalable parallel implementation of exact inference in Bayesian networks. In Proceedings of the 12th International Conference on Parallel and Distributed Systems, pages 143-150, 2006.
11. D. Pennock. Logarithmic time parallel Bayesian inference. In Proceedings of the 14th Annual Conference on Uncertainty in Artificial Intelligence, pages 431-438, 1998.
12. S. J. Russell and P. Norvig. Artificial Intelligence: A Modern Approach (2nd Edition). Prentice Hall, December 2002.
13. P. Sadayappan, F. Ercal, and J. Ramanujam. Partitioning graphs on message-passing machines by pairwise mincut. Information Sciences - Informatics and Computer Science: An International Journal, 111(1-4):223-237, 1998.
14. San Diego Supercomputer Center. http://www.sdsc.edu.
15. K. Schloegel, G. Karypis, and V. Kumar. Parallel multilevel algorithms for multi-constraint graph partitioning. In Lecture Notes in Computer Science, volume 1900, pages 296-310, 2001.
16. E. Segal, B. Taskar, A. Gasch, N. Friedman, and D. Koller. Rich probabilistic models for gene expression. In 9th International Conference on Intelligent Systems for Molecular Biology, pages 243-252, 2001.
17. R. D. Shachter, S. K. Andersen, and P. Szolovits. Global conditioning for probabilistic inference in belief networks. In Proceedings of the Tenth Conference on Uncertainty in Articial Intelligence, pages 514-522, 1994.
18. Y. Xia and V. K. Prasanna. Node level primitives for parallel exact inference. In Proceedings of the 19th International Symposium on Computer Architecture and High Performance Computing, pages 221-228, October 2007.