Independence in constraint logic programs

Studying independence of literals, variables, and substitutions has proven very useful in the context of logic programming (LP). Here we study independence in the broader context of constraint logic programming (CLP). We show that a naive extrapolation of the LP definitions of independence to CLP is unsatisfactory (in fact, wrong) for two reasons. First, because interaction between variables through constraints is more complex than in the case of logic programming. Second, in order to ensure the efUciency of several optimizations not only must independence of the search space be considered, but also an orthogonal issue - "independence of constraint solving." We clarify these issues by proposing various types of search independence and constraint solver independence, and show how they can be combined to allow different independence-related optimizations, from parallelism to intelligent backtracking. Sufficient conditions for independence which can be evaluated "a-priori" at run-time are also proposed. Our results suggest that independence, provided a suitable definition is chosen, is even more useful in CLP than in LP

Independence and search space preservation in dynamically scheduled constraint logic languages

This paper performs a further generalization of the notion of independence in constraint logic programs to the context of constraint logic programs with dynamic scheduling. The complexity of this new environment made necessary to first formally define the relationship between independence and search space preservation in the context of CLP languages. In particular, we show that search space preservation is, in the context of CLP languages, not only a sufficient but also a necessary condition for ensuring that both the intended solutions and the number of transitions performed do not change. These results are then extended to dynamically scheduled languages and used as the basis for the extension of the concepts of independence. We also propose several a priori sufficient conditions for independence and also give correctness and efficiency results for parallel execution of constraint logic programs based on the proposed notions of independence

The CIAO multiparadigm compiler and system: A progress report

Abstract is not available

Non-failure analysis for logic programs

We provide a method whereby, given mode and (upper approximation) type information, we can detect procedures and goals that can be guaranteed to not fail (i.e., to produce at least one solution or not termínate). The technique is based on an intuitively very simple notion, that of a (set of) tests "covering" the type of a set of variables. We show that the problem of determining a covering is undecidable in general, and give decidability and complexity results for the Herbrand and linear arithmetic constraint systems. We give sound algorithms for determining covering that are precise and efiicient in practice. Based on this information, we show how to identify goals and procedures that can be guaranteed to not fail at runtime. Applications of such non-failure information include programming error detection, program transiormations and parallel execution optimization, avoiding speculative parallelism and estimating lower bounds on the computational costs of goals, which can be used for granularity control. Finally, we report on an implementation of our method and show that better results are obtained than with previously proposed approaches

Some challenges for constraint programming

We propose a number of challenges for future constraint programming systems, including improvements in implementation technology (using global analysis based optimization and parallelism), debugging facilities, and the extensión of the application domain to distributed, global programming. We also briefly discuss how we are exploring techniques to meet these challenges in the context of the development of the CIAO constraint logic programming system

Towards a concurrent semantics-based analysis of CC and CLP: principles and practice of constraint programming

Abstract is not available

The CIAO multi-dialect compiler and system: A demo and status report

Abstract is not availabl

The CIAO multi-dialect compiler and system: An experimentation workbench for future (C)LP systems

Abstract is not available

Towards CIAO-Prolog - A parallel concurrent constraint system

Abstract is not available

Relating data—parallelism and (and—) parallelism in logic programs

Much work has been done in the áreas of and-parallelism and data parallelism in Logic Programs. Such work has proceeded to a certain extent in an independent fashion. Both types of parallelism offer advantages and disadvantages. Traditional (and-) parallel models offer generality, being able to exploit parallelism in a large class of programs (including that exploited by data parallelism techniques). Data parallelism techniques on the other hand offer increased performance for a restricted class of programs. The thesis of this paper is that these two forms of parallelism are not fundamentally different and that relating them opens the possibility of obtaining the advantages of both within the same system. Some relevant issues are discussed and solutions proposed. The discussion is illustrated through visualizations of actual parallel executions implementing the ideas proposed