PALS: Efficient Or-Parallelism on Beowulf Clusters

TL;DR

The paper introduces PALS, a novel system that enables efficient or-parallel execution of Prolog on distributed Beowulf clusters using an innovative incremental stack-splitting technique, advancing parallel logic programming.

Contribution

It presents the first distributed or-parallel Prolog implementation based on stack-splitting, combining it with incremental copying for improved performance on distributed-memory systems.

Findings

PALS outperforms previous methods in distributed environments.

Stack-splitting with incremental copying is effective for distributed Prolog.

Experimental results validate the efficiency of PALS on Beowulf clusters.

Abstract

This paper describes the development of the PALS system, an implementation of Prolog capable of efficiently exploiting or-parallelism on distributed-memory platforms--specifically Beowulf clusters. PALS makes use of a novel technique, called incremental stack-splitting. The technique proposed builds on the stack-splitting approach, previously described by the authors and experimentally validated on shared-memory systems, which in turn is an evolution of the stack-copying method used in a variety of parallel logic and constraint systems--e.g., MUSE, YAP, and Penny. The PALS system is the first distributed or-parallel implementation of Prolog based on the stack-splitting method ever realized. The results presented confirm the superiority of this method as a simple yet effective technique to transition from shared-memory to distributed-memory systems. PALS extends stack-splitting by combining it with incremental copying; the paper provides a description of the implementation of PALS, including details of how distributed scheduling is handled. We also investigate methodologies to effectively support order-sensitive predicates (e.g., side-effects) in the context of the stack-splitting scheme. Experimental results obtained from running PALS on both Shared Memory and Beowulf systems are presented and analyzed.