State space construction and steady-state solution of GSPNs on a shared-memory multiprocessor

S.C. Allmaier, M. Kowarschik, G. Horton
Proceedings of the Seventh International Workshop on Petri Nets and Performance Models  
A c ommon approach for the quantitative analysis of a generalized s t o chastic Petri net (GSPN) is to generate its entire state space and then solve the corresponding continuous{time Markov chain (CTMC) numerically. This analysis often su ers from two major problems: the state space explosion and the sti ness of the CTMC. In this paper we present parallel algorithms for shared{memory machines that attempt to alleviate both of these di culties: the large main memory capacity of a multiprocessor
more » ... can be utilized and long computation times are r educed by e cient parallelization. The algorithms comprise both CTMC construction and numerical steady{state solution. We give experimental results obtained with a Convex SPP1600 shared{memory multiprocessor that show the behavior of the algorithms and the parallel speedups obtained.
doi:10.1109/pnpm.1997.595542 dblp:conf/pnpm/AllmaierKH97 fatcat:rj5aamnnzvgkzaufo7ysituizm