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, And-parallelism, and combinations of the two. We also explore some related issues, such as memory

Abstract: While the ability to simulate nondeterminism and compute multiple solutions for a single query is a powerful and attractive feature of logic programming languages, it is expensive in both time and space. Since programs in such languages are very often functional, i.e. do not produce more than one distinct solution for a single input, this overhead is especially undesirable. This paper describes how pro-grams may be analyzed statically to determine which literals and predicates are functional, and how the program may then be optimized using this information. Our notion of ‘‘functionality’ ’ subsumes the notion of ‘‘determinacy’ ’ that has been considered by various researchers. Our algorithm is less reliant on language features such as the cut, and thus extends more easily to parallel execution strategies, than others that have been proposed.

This paper describes an extension to NU-Prolog which allows evaluable functions to be defined using equations. We consider it to be the most pragmatic way of combining functional and relational programming. The implementation consists of several hundred lines of Prolog code and the underlying Prolog implementation was not modified at all. However, the system is reasonably efficient and supports coroutining, optional lazy evaluation, higher order functions and parallel execution. Efficiency is gained in several ways. First, we use some new implementation techniques. Second, we exploit some of the unique features of NU-Prolog, though these features are not essential to the implementation. Third, the language is designed so that we can take advantage of implicit mode and determinism information. Although we have not concentrated on the semantics of the language, we believe that our language design decisions and implementation techniques will be useful in the next generation of combined functional and relational languages. Keywords: logic programming, equations, functions, parallelism, indexing, lazy evaluation, higher order. -- 1 -- 1 Introduction

Parallelizing logic programming has attracted much interest in the research community, because of the intrinsic OR- and AND-parallelisms of logic programs. One research stream aims at transparent exploitation of parallelism in existing logic programming languages such as Prolog, whale the family of concurrent logic languages develops language constructs allowing programmers to express the concurrency—that is, the communication and synchronization between parallel processes—within their algorithms. This article concentrates mainly on transparent exploitation of parallelism and surveys the most mature solutions to the problems to be solved in order to obtain efficient implementations. These solutions have been implemented, and the most efficient parallel logic programming systems reach effective speedups over state-of-the-art sequential Prolog implementations. The article also addresses current and prospective research issues in extending the applicability and the efficiency of existing systems, such as models merging the transparent parallehsm and the concurrent logic languages approaches, combination of constraint logic programming with parallelism, and use of highly parallel architectures.

Muse (Multi-sequential Prolog engines) is a simple and efficient approach to Orparallel execution of Prolog programs. It is based on having several sequential Prolog engines, each with its local address space, and some shared memory space. It is currently implemented on a 7-processors machine with local/shared memory constructed at SICS, a 16-processors Sequent Symmetry, a 96-processors BBN Butterfly I, and a 45-processors BBN Butterfly II. The sequential SICStus Prolog system has been adapted to Or-parallel implementation. Extra overhead associated with this adaptation is very low in comparison with the other approaches. The speed-up factor is very close to the number of processors in the system for a large class of problems. The goal of this paper is to present the Muse execution model, some of its implementation issues, a variant of Prolog suitable for multiprocessor implementations, and some experimental results obtained from two different multiprocessor systems. Key Words: Or-Par...

PROLOG, the most popular logic programming language, has been developed for single-processor computers. The implementations of sequential Prolog became efficient with the development of the Warren Abstract Machine (WAM) and are still improving. Today many parallel computers are commercially available and the question is how to utilize this opportunity to speed up the execution of Prolog programs. Our approach has been to study and develop efficient techniques for implementing OR-parallel systems for the full Prolog language on UMA and NUMA computers. Based on those techniques a high performance OR-parallel Prolog system has been designed and implemented on six different parallel computers. The system has a number of processes, called workers, consisting of two components: the engine, which does the actual Prolog work, and the scheduler. The schedulers, working together, divide the available work between the engines and support the sequential semantics of Prolog. We have extended th...

We discuss fundamental limitations of or-parallel execution models of nondeterministic programming languages. Or-parallelism corresponds to executing the dierent nondeterministic computational paths in parallel. A natural way to represent the state of (parallel) execution of a nondeterministic program is by means of an or-parallel tree. We identify three important criteria that underlie the design of or-parallel implementations based upon the or-parallel tree: constant-time access to variables, constant-time task creation, and constant-time task switching, where the term `constant-time' means that the time for these operations is independent of the number of nodes in the or-parallel tree, as well as the size of each node. We prove that all three criteria cannot be simultaneously satised by any or-parallel execution model based on a nite number of processors but unbounded memory. We discuss in detail the application of our result to the class of logic programming languages, and show ...

Andorra-I is an experimental parallel Prolog system based on the Basic Andorra model. This model supports both dependent and-parallelism, by executing determinate goals in parallel, and or-parallelism, stemming from the nondeterminate goals. In this paper, we present a new compiler-based version of the Andorra-I system and discuss its performance. We study the system with a wide set of real-life, non-trivial logic programming applications. As Andorra-I provides a powerful programming model, we are able to include Prolog programs, committed-choice programs, and Andorra-style programs. The results show that the system is very effective at exploiting both forms of parallelism, that it compares well with exclusively or-parallel and exclusively and-parallel systems, and that the extra complexity of the model is manageable. Basic performance compares quite well with other compiler-based systems such as SICStus and JAM.

We argue that in order to exploit both Independent And- and Or-parallelism in Prolog programs there is advantage in recomputing some of the independent goals, as opposed to all their solutions being reused. We present an abstract model, called the Composition-Tree, for representing and-or parallelism in Prolog Programs. The Composition-tree closely mirrors sequential Prolog execution by recomputing some independent goals rather than fully re-using them. We also outline two environment representation techniques for And-Or parallel execution of full Prolog based on the Composition-tree model abstraction. We argue that these techniques have advantages over earlier proposals for exploiting and-or parallelism in Prolog. 1. Introduction One of the most attractive features of logic programming languages is that they allow implicit parallel execution of programs. There are three main forms of parallelism present in logic programs: or-parallelism, independent and-parallelism and dependent and...

Independent and-parallelism, dependent and-parallelism and or-parallelism are the three main forms of implicit parallelism present in logic programs. In this paper we present a model, IDIOM, which exploits all three forms of parallelism in a single framework. IDIOM is based on a combination of the Basic Andorra Model and the Extended And-Or Tree Model. Our model supports both Prolog as well as the flat concurrent logic languages. We discuss the issues that arise in combining the three forms of parallelism, and our solutions to them. We also present an implementation scheme, based on binding arrays, for implementing IDIOM.