Parallel Logic Programming System Research Articles

The performance of parallel Prolog programs

Performance results are presented for a parallel execution model for Prolog that supports AND-parallelism, OR-parallelism, and intelligent backtracking. The results show that restricted AND-parallelism is of limited benefit for small programs, but produced speedups from 7-10 on two large programs. OR-parallelism was found to be generally not useful for the benchmarks examined if the semantics of Prolog were preserved. Of particular interest is the phenomenon of super-multiplicative behavior, in which the performance improvement obtained when more than one technique is used is greater than the product of the performance improvements due to each technique individually. The implications of the performance results for parallel Prolog systems are discussed, and directions for future work are indicated.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

A garbage collection algorithm for shared memory parallel processors

This paper describes a technique for adapting the Morris sliding garbage collection algorithm to execute on parallel machines with shared memory. The algorithm is described within the framework of an implementation of the parallel logic language Parlog. However, the algorithm is a general one and can easily be adapted to parallel Prolog systems and to other languages. The performance of the algorithm executing a few simple Parlog benchmarks is analyzed. Finally, it is shown how the technique for parallelizing the sequential algorithm can be adapted for a semi-space copying algorithm.

Designing a high performance parallel logic programming system

Compilation techniques such as those portrayed by the Warren Abstract Machine (WAM) have greatly improved the speed of execution of logic programs. The research presented herein is geared towards providing additional performance to logic programs through the use of parallelism, while preserving the conventional semantics of logic languages. Two areas to which special attention is given are the preservation of sequential performance and storage efficiency, and the use of low overhead mechanisms for controlling parallel execution. Accordingly, the techniques used for supporting parallelism are efficient extensions of those which have brought high inferencing speeds to sequential implementations. At a lower level, special attention is also given to design and simulation detail and to the architectural implications of the execution model behavior. This paper offers an overview of the basic concepts and techniques used in the parallel design, simulation tools used, and some of the results obtained to date.

System structure for parallel logic programming

A system structure supporting parallel processing in general and parallel logic programming and expert system applications in particular is described. It is not based on special hardware but has rather been designed as an evolutionary extension to most existing machine architectures. It is aimed at parallel processing support for e.g. PROLOG as well as for expert system (shells) implemented in a general purpose language. A layered structure consisting of an extended machine interface and a macro language is chosen to support a range of various applications.