Parallel Jess

Abstract

Parallel production or rule-based systems, like a parallel version of Jess, are needed for real applications. The proposed architecture for a such system is based on a wrapper allowing the cooperation between several instances of Jess running on different computers. The system has been designed having in mind the final goal to speedup current P system simulators. Preliminary tests show its efficiency in this particular case and on classical benchmarks.

A Novel Approach to Distributed Rule Matching and Multiple Firing Based on MapReduce

“…The existing cluster-based solutions can be mainly divided into two categories as follows. The first way is to partition and allocate the rule base in rule level (Petcu, 2005a;Wu et al, 2008;Cabitza et al, 2005;Wu et al, 2010;Wu, 2011), which is focused on the parallel execution of rules. The production system instances in the cluster systems of Petcu et al (2005b) and are peer-to-peer, which don't carry out global selection and execution of rules; each engine instance uses its own rule base to reason in the local working memory, depending on the central server or parallel libraries such as Octopus (Petcu et al, 2005b), JPVM (Petcu, 2005b), and MPI (Wu et al, 2008) to realize asynchronous communications with each other.…”

“…Nowadays, both the cloud computing paradigm and MapReduce programming framework have become key enablers for running big data analytics and large-scale compute-and data intensive applications (Palanisamy et al, 2015;Lee et al, 2016;Qi et al, 2015;Eldawy et al, 2016). The way of using cluster or cloud to construct production systems (Petcu, 2005a) can flexibly expand system processing capability by increasing the cluster scale. That can effectively respond to the challenges of massive rule processing.…”