TY - GEN

T1 - A parallel algorithm for exact bayesian network inference

AU - Nikolova, Olga

AU - Zola, Jaroslaw

AU - Aluru, Srinivas

N1 - Copyright:
Copyright 2010 Elsevier B.V., All rights reserved.

PY - 2009

Y1 - 2009

N2 - Given n random variables and a set of m observations of each of the n variables, the Bayesian network inference problem is to infer a directed acyclic graph (DAG) on the n variables such that the implied joint probability distribution best explains the set of observations. Bayesian networks are widely used in many fields ranging from data mining to computational biology. Exact inference of Bayesian networks takes O(n2 · 2n) time plus the cost of O(n · 2n) evaluations of an application-specific scoring function. In this paper, we present a parallel algorithm for exact Bayesian inference that is work-optimal and communication-efficient. We demonstrate the applicability of our method by an implementation on the IBM Blue Gene/L, with experimental results that exhibit near perfect scaling.

AB - Given n random variables and a set of m observations of each of the n variables, the Bayesian network inference problem is to infer a directed acyclic graph (DAG) on the n variables such that the implied joint probability distribution best explains the set of observations. Bayesian networks are widely used in many fields ranging from data mining to computational biology. Exact inference of Bayesian networks takes O(n2 · 2n) time plus the cost of O(n · 2n) evaluations of an application-specific scoring function. In this paper, we present a parallel algorithm for exact Bayesian inference that is work-optimal and communication-efficient. We demonstrate the applicability of our method by an implementation on the IBM Blue Gene/L, with experimental results that exhibit near perfect scaling.

UR - http://www.scopus.com/inward/record.url?scp=77952207369&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=77952207369&partnerID=8YFLogxK

U2 - 10.1109/HIPC.2009.5433194

DO - 10.1109/HIPC.2009.5433194

M3 - Conference contribution

AN - SCOPUS:77952207369

SN - 9781424449224

T3 - 16th International Conference on High Performance Computing, HiPC 2009 - Proceedings

SP - 342

EP - 349

BT - 16th International Conference on High Performance Computing, HiPC 2009 - Proceedings

T2 - 16th International Conference on High Performance Computing, HiPC 2009

Y2 - 16 December 2009 through 19 December 2009

ER -