Improving the efficiency of nondeterministic independent and-parallel systems

Authors:
Enrico Pontelli;Gopal Gupta;Dongxing Tang;Manuel Carro;Manuel V. Hermenegildo
Affiliations:
Laboratory for Logic and Databases, Dept of Computer Science, New Mexico State University. Las Cruces, NM, U.S.A.;Laboratory for Logic and Databases, Dept of Computer Science, New Mexico State University. Las Cruces, NM, U.S.A.;Laboratory for Logic and Databases, Dept of Computer Science, New Mexico State University. Las Cruces, NM, U.S.A.;Facultad de Informática, Universidad Politécnica de Madrid, 28660 Boadilla del Monte, Madrid, Spain;Facultad de Informática, Universidad Politécnica de Madrid, 28660 Boadilla del Monte, Madrid, Spain
Venue:
Computer Languages
Year:
1996

Citing 12
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Abstract

We present the design and implementation of the and-parallel component of ACE. ACE is a computational model for the full Prolog language that simultaneously exploits both or-parallelism and independent and-parallelism. A high-performance implementation of the ACE model has been realized and its performance reported in this paper. We discuss how some of the standard problems which appear when implementing and-parallel systems are solved in ACE. We then propose a number of optimizations aimed at reducing the overheads and the increased memory consumption which occur in such systems when using previously proposed solutions. Finally, we present results from an implementation of ACE which includes the optimizations proposed. The results show that ACE exploits and-parallelism with high efficiency and high speedups. Furthermore, they also show that the proposed optimizations, which are applicable to many other and-parallel systems, significantly decrease memory consumption and increase speedups and absolute performance both in forward execution and during backtracking.