parallel computation of continuous petri nets based on hypergraph partitioning

Abstract

Continuous Petri net can be used for performance analysis or static analysis. The analysis is based on solving the associated ordinary differential equations. This paper presents a method to parallel compute these differential equations. We first map the Petri net to a hypergraph, and then partition the hypergraph to minimize interprocessor communication while maintaining a good load balance; Based on the partition result, we divide the differential equations into several blocks; Finally, we design a parallel computing algorithm to compute these equations. Software hMETIS is used to partition the hypergraph, and software SUNDIALS is used to support the parallel computing of differential equations. Gas station problem and dining philosopher problem have been used to demonstrate the feasibility, accuracy, and scalability of our method. © 2011 Springer Science+Business Media, LLC.NSF 90818013; Zhejiang Science Foundation Z1090357Continuous Petri net can be used for performance analysis or static analysis. The analysis is based on solving the associated ordinary differential equations. This paper presents a method to parallel compute these differential equations. We first map the Petri net to a hypergraph, and then partition the hypergraph to minimize interprocessor communication while maintaining a good load balance; Based on the partition result, we divide the differential equations into several blocks; Finally, we design a parallel computing algorithm to compute these equations. Software hMETIS is used to partition the hypergraph, and software SUNDIALS is used to support the parallel computing of differential equations. Gas station problem and dining philosopher problem have been used to demonstrate the feasibility, accuracy, and scalability of our method. © 2011 Springer Science+Business Media, LLC