DAOS — Scalable And-Or Parallelism

Castro, Luís Fernando; Costa, Vítor Santos; Geyer, Cláudio F. R.; Silva, Fernando M. A.; Vargas, Patrícia Kayser; Correia, Manuel E.

doi:10.1007/3-540-48311-x_125

Cited by 5 publications

(7 citation statements)

References 9 publications

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“…Research on execution of logic programs on Distributed Memory architectures (e.g., [Benjumea and Troya 1993;Kacsuk and Wise 1992]) has been more sparse and perhaps less incisive. Currently, there is renewed interest in distributed memory architectures [Silva and Watson 2000;Araujo and Ruz 1998;Castro et al 1999;Gupta and Pontelli 1999c;Hermenegildo 1994;Cabeza and Hermenegildo 1996], thanks to their increased availability at affordable prices and their scalability. Nevertheless, the focus of this survey is on describing execution models for shared memory architectures.…”

Section: Discussionmentioning

confidence: 99%

“…Various approaches have been proposed that allow support for Prolog's sequential semantics even during parallel execution Correia et al 1997;Castro et al 1999;Santos Costa et al 1991c]. Another issue that arises in systems that exploit independent and-parallelism is whether to recompute solutions of independent goals, or to reuse them.…”

Section: Issuesmentioning

confidence: 99%

“…However, no system exists that efficiently exploits all sources of parallelism present in logic programs. Efforts are already under way to remedy this [Montelius 1997;Pontelli and Gupta 1997b;Correia et al 1997;Castro et al 1999], and we believe that this is one of the areas in which much of the research in parallel logic programming may lie in the future. One approach to achieving this goal, inspired by the duality [Pontelli and Gupta 1995b] and orthogonality [Correia et al 1997] principles and by views such as those argued in [Hermenegildo and CLIP Group 1994], would be to configure an ideal parallel logic programming system as a true "plug-and-play" system, where a basic Prolog kernel engine can be incrementally extended with different modules implementing different parallelization strategies, scheduling strategies, etc.…”

Section: Conclusion and Future Of Parallel Logic Programmingmentioning

confidence: 99%

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Parallel execution of prolog programs

Gupta

Pontelli

Ali

et al. 2001

ACM Trans. Program. Lang. Syst.

116

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Since the early days of logic programming, researchers in the field realized the potential for exploitation of parallelism present in the execution of logic programs. Their high-level nature, the presence of non-determinism, and their referential transparency, among other characteristics, make logic programs interesting candidates for obtaining speedups through parallel execution. At the same time, the fact that the typical applications of logic programming frequently involve irregular computations, make heavy use of dynamic data structures with logical variables, and involve search and speculation, makes the techniques used in the corresponding parallelizing compilers and run-time systems potentially interesting even outside the field. The objective of this paper is to provide a comprehensive survey of the issues arising in parallel execution of logic programming languages along with the most relevant approaches explored to date in the field. Focus is mostly given to the challenges emerging from the parallel execution of Prolog programs. The paper describes the major techniques used for shared memory implementation of Or-parallelism, Andparallelism, and combinations of the two. We also explore some related issues, such as memory management, compile-time analysis, and execution visualization.

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Section: Discussionmentioning

confidence: 99%

Section: Issuesmentioning

confidence: 99%

Section: Conclusion and Future Of Parallel Logic Programmingmentioning

confidence: 99%

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Parallel execution of prolog programs

Gupta

Pontelli

Ali

et al. 2001

ACM Trans. Program. Lang. Syst.

116

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“…Distributed implementations of Prolog have been proposed by several researchers (Foong 1995;Araujo and Ruz 1998;Castro et al 1999). However, none of these systems are very effective in producing speedups over a wide range of benchmarks.…”

Section: Related Workmentioning

confidence: 99%

“…Most research in or-parallel execution of Prolog so far has focused on techniques aimed at shared-memory multiprocessors (SMPs). Relatively fewer efforts (Foong 1995;Araujo and Ruz 1998;Castro et al 1999;Briat et al 1992;Benjumea and Troya 1993;Silva and Watson 2000) have been devoted to implementing Prolog systems on distributed-memory platforms (DMPs). Out of these efforts only a small number have been implemented as working prototypes, and even fewer have produced acceptable speedups.…”

Section: Introductionmentioning

confidence: 99%

PALS: Efficient Or-Parallel execution of Prolog on Beowulf clusters

Pontelli

Villaverde

Guo

et al. 2007

Theory and Practice of Logic Programming

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This paper describes the development of the PALS system, an implementation of Prolog capable of efficiently exploiting or-parallelism on distributed-memory platformsspecifically 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.

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