Compilation as partitioning: a new approach to compiling non-strict functional languages

Traub, Kenneth R.

doi:10.1145/99370.99376

Cited by 11 publications

(4 citation statements)

References 21 publications

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“…The first work on this specific problem is that by Giacobazzi and Ricci [1990], which attempts a bottom-up abstract interpretation to identify pipelined computations. Some similarities are also shared with the various studies on partitioning techniques for declarative concurrent languages [Traub 1989], that aim to identify partitioning of the program components into sequential threads, and the work on management of parallel tasks in committed choice languages [Ueda and Morita 1993]. Techniques have also been proposed for detecting non-strict independent and-parallelism at compile-time [Cabeza and Hermenegildo 1994].…”

Section: Detection Of Parallelismmentioning

confidence: 99%

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: Detection Of Parallelismmentioning

confidence: 99%

Parallel execution of prolog programs

Gupta

Pontelli

Ali

et al. 2001

ACM Trans. Program. Lang. Syst.

116

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“…The idea is very interesting and probably can be integrated in our scheme, but taken by itself is very unlikely to produce e ective results in a scheme like DDAS. Some similarities are also shared with the various studies on partitioning techniques for declarative concurrent languages 32,19], aimed at identifying partitioning of the program components into sequential threads.…”

Section: Analysis and Annotation For Dapmentioning

confidence: 99%

Automatic Compile-Time Parallelization of Prolog Programs for Dependent And-Parallelism

Pontelli¹,

Gupta²,

Pulvirenti³

et al. 1997

Logic Programming

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The problem of automatically detecting dependent andparallelism in Prolog programs has not been studied so far. In this paper we discuss major issues involved in using static analysis to detect dependent and-parallelism in Prolog programs. We present a static analysis technique based on abstract interpretation that detects (fruitful) dependent and-parallelism. Our method makes use of several types of information about the program|sharing and freeness, granularity of subgoals, and binding-times of program variables|computed using abstract interpretation. The information collected from di erent sources is used to produce a suitable annotation of the original program. This annotation identi es: (i) the most fruitful sources of parallelism; and, (ii) the dependencies that must be respected during execution. A prototype compiler that incorporates these ideas has been implemented and tested on the ACE and-or parallel Prolog system. The (very encouraging) results obtained are reported here.

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“…Consider the following example from [Traub 1989 If z > 0, the only possible order of evaluation is: p, b, bb, a, aa, c. If x < 0, the expressions must be evaluated in a different order: p, a, aa, b, c. This provides an example of an Id fragment in which the order of execution of statements cannot be determined at compiletime. This provides a theoretical limit on compile-time scheduling, beyond any practical limits based on insufficiently sophisticated compilers, because no compile-time scheduling exists.…”

Section: Blocksmentioning

confidence: 99%

Dataflow Computation for the J-Machine

Spertus¹

1990

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Compilation as partitioning: a new approach to compiling non-strict functional languages

Cited by 11 publications

References 21 publications

Parallel execution of prolog programs

Parallel execution of prolog programs

Automatic Compile-Time Parallelization of Prolog Programs for Dependent And-Parallelism

Dataflow Computation for the J-Machine

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