Evaluating In-Clique and Topological Parallelism Strategies for Junction Tree-Based Bayesian Inference Algorithm on the Cray XMT

Conference · Thu Sep 01 00:00:00 EDT 2011

DOI:https://doi.org/10.1109/IPDPS.2011.328· OSTI ID:1028552

Chin, George; Choudhury, Sutanay; Kangas, Lars J; McFarlane, Sally A; Marquez, Andres

Long viewed as a strong statistical inference technique, Bayesian networks have emerged to be an important class of applications for high-performance computing. We have applied an architecture-conscious approach to parallelizing the Lauritzen-Spiegelhalter Junction Tree algorithm for exact inferencing in Bayesian networks. In optimizing the Junction Tree algorithm, we have implemented both in-clique and topological parallelism strategies to best leverage the fine-grained synchronization and massive-scale multithreading of the Cray XMT architecture. Two topological techniques were developed to parallelize the evidence propagation process through the Bayesian network. One technique involves performing intelligent scheduling of junction tree nodes based on its topology and relative size. The second technique involves decomposing the junction tree into a much finer tree-like representation to offer much more opportunities for parallelism. We evaluate these optimizations on five different Bayesian networks and report our findings and observations. Another important contribution of this paper is to demonstrate the application of massive-scale multithreading for load balancing and use of implicit parallelism-based compiler optimizations in designing scalable inferencing algorithms.

• Research Organization: Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
• Sponsoring Organization: USDOE
• DOE Contract Number: AC05-76RL01830
• OSTI ID: 1028552
• Report Number(s): PNNL-SA-77562; 400470000; TRN: US201122%%393
• Resource Relation: Conference: Proceedings of the IEEE International Symposium on Parallel and Distributed Processing Workshops and Phd Forum (IPDPSW 2011), May 16-20, 2011, Anchorage, Alaska, 1710-1719
• Country of Publication: United States
• Language: English

Related Subjects

99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE
ALGORITHMS
COMPUTER ARCHITECTURE
PROCESSING
SYNCHRONIZATION
TOPOLOGY
PARALLEL PROCESSING
Bayesian network
dynamic Bayesian network
junction tree
in-clique parallelism
topological parallelism
Cray XMT
massive-scale multithreading
fine-grained synchronization