ElipSys(ID:6703/eli004)

parallel constraint logic programming language
References:
  • Clark DA, Rawlings CJ, Shirazi J, Veron A, Reeve M "Protein topology prediction through parallel constraint logic programming" Proc Int Conf Intell Syst Mol Biol. 1993 1 pp83-91 view details Abstract: In this paper, two programs are described (CBS1e and CBS2e). These are implemented in the parallel constraint logic programming language ElipSys. These predict protein alpha/beta-sheet and beta-sheet topologies from secondary structure assignments and topological folding rules (constraints). These programs illustrate how recent developments in logic programming environments can be applied to solve large-scale combinatorial problems in molecular biology. We demonstrate that parallel constraint logic programming is able to overcome some of the important limitations of more established logic programming languages i.e. Prolog. This is particularly the case in providing features that enhance the declarative nature of the program and also in addressing directly the problems of scaling-up logic programs to solve scientifically realistic problems. Moreover, we show that for large topological problems CBS1e was approximately 60 times faster than an equivalent Prolog implementation (CBS1) on a sequential device with further performance enhancements possible on parallel computer architectures. CBS2e is an extension of CBS1e that addresses the important problem of integrating the use of uncertain (weighted) protein folding constraints with categorical ones, through the use of a cost function that is minimized. CBS2e achieves this with a relatively minor reduction of performance. These results significantly extend the range and complexity of protein structure prediction methods that can reasonably be addressed using AI languages.
  • Clark DA, Rawlings CJ, Doursenot S "Genetic map construction with constraints" Proc Int Conf Intell Syst Mol Biol. 1994;2:78-86 view details Abstract: A pilot program, CME, is described for generating a physical genetic map from hybridization fingerprinting data. CME is implemented in the parallel constraint logic programming language ElipSys. The features of constraint logic programming are used to enable the integration of pre-existing mapping information (partial probe orders from cytogenetic maps and local physical maps) into the global map generation process, while parallelism enables the search space to be traversed more efficiently. CME was tested using data from chromosome 2 of Schizosaccharomyces pombe and was found able to generate maps as well as (and sometimes better than) a more traditional method. This paper illustrates the practical benefits of using a symbolic logic programming language and shows that the features of constraint handling and parallel execution bring the development of practical systems based on AI programming technologies nearer to being a reality.
  • PARallel FORmal Computing Environment (ESPRIT Basic Research) EATCS 1994 Report view details Abstract: ParForCE is aimed at constructing (and evaluating the use of) formal tools for the development of parallel programs and their efficient execution. To this end the emerging techniques for formal program analysis and manipulation are applied to central issues relating to parallel execution such as dependency and granularity analysis or memory management. Tools based on these techniques are built to aid in the formal development of parallel logic programs. These tools are then integrated with parallel execution platforms and their effectiveness assessed. Extract: Parallel Logic Programming Platforms
    A number of parallel logic programming systems, which have been shown to be capable of significant speedups over state of the art sequential Prolog systems, are already being used as platforms by the project partners. These include &-Prolog [39] (developed at Madrid), Muse [2, 3] (developed at SICS), and ElipSys [7] (developed at ECRC). The ElipSys execution platform, a prototype of which was developed as part of ESPRIT Project 2025, EDS, supports OR-parallelism as well as a framework for implementing constraint solvers and a close coupling to databases. Muse is a well established execution platform that allows Prolog to be executed in parallel by exploiting OR-parallelism. The &-Prolog system is also a well established parallel Prolog system that exploits (independent) AND-parallelism. Some parts of the &-Prolog and Muse models were developed by SICS and Madrid in ESPRIT Project 2471, PEPMA.

    A matter of great interest is the combination of the capabilities of these systems, as well as those of other languages, both from the point of view of concurrency and constraint support.

    The AGENTS Language (AKL) is a new concurrent logic language developed by SICS in ESPRIT Project 2471, PEPMA, with a large potential for parallel execution. It provides the programming paradigms of search-oriented languages such as Prolog, process-oriented languages such as GHC, and the constraint logic programming languages in a unified framework.

    A proposal for combining Muse and &-Prolog into one system to exploit their two sources of parallelism while maintaining the high efficiency of both systems is represented by the ACE model [35]. We refer to a further enhancement of this model which also supports constraint solving (and explicit concurrency) in the same framework as Ciao-Prolog --(Concurrent,) Constraint, Independence-based And/Or parallel Prolog.