Performance Analysis of a Strategy to Distribute And-work and Or-work in Parallel Logic Programming Systems

Abstract

This paper studies the performance of Andorra-I, a parallel logic programming system that exploits and-parallelism and or-parallelism with a novel strategy to distribute and-work and or-work among processors. The strategy, work-guided guides it’s decisions by looking at the amount of current and-work and or-work avaliable in an application during execution. The scheduler decision strategy moves workers from one parallel task to another according to the tasks sizes. Results show that the work-guided strategy works quite well and produces better results than the ones produced with a version of Andorra-I that does not a flow dynamic migration of workers during execution. We believe that this strategy can be applied to other parallel logic programming systems that aim to exploit both and-and or-parallelism in a single framework.