Current advances in Virtual Memory for Parallel Architectures have changed the idea that software architectures with global address spaces cannot execute well on Distributed Memory Message Passing (DMMP) architectures. This paper presents a parallel logic programming platform for complex applications based on a shared binding environment. The software architecture of this platform has been designed taking into account a range of parallel architectures, including DMMP machines. Preliminary results of the simulation of the software architecture on the EDS architecture, an Esprit II development of a DMMP machine, are also discussed.

ElipSys is a parallel programming system based on logic being developed at ECRC. The aim of the project is to support the development and delivery of large decision support systems. It integrates three of the most important technologies required to support such systems: constraint satisfaction, tight database coupling and parallel evaluation. The project addresses issues at all levels: from language design to implementation. Of particular note is the work to improve the expressiveness and declarativeness of logic programming, and the design of an execution model that is appropriate to a range of parallel machine architectures, from shared memory to distributed memory. A prototype version of ElipSys is running on the Sequent Symmetry and a network of SUN workstations running the MACH operating system. Prototypes of a number of commercially and technologically important applications have been implemented using ElipSys by a number of end-user application development organizations.

ElipSys is a programming system supporting a constraint logic programming (CLP) language and OR-parallel execution. These two features complement each other: CLP programming eases the writing of efficient search programs while OR-parallelism allows one to attain quasi-linear or super-linear speed-ups when the programs are executed on parallel machines. The speed-ups come without significant additional programming effort. This paper gives the rationale behind this combination, explains how it influences the design of the language and the implementation, and gives results providing evidence for the synergy of these two paradigms.

The APPLAUSE ESPRIT Project is building major applications using the ElipSys parallel constraint logic programming system developed at ECRC. Two major aims of the project are to advance the state of the art in four commercially significant application areas and to promote the use of ElipSys-like languages among applications developers. This brief paper gives an outline of ElipSys and an overview of the applications being developed within the APPLAUSE Project.

This paper presents the constraint handling and garbage collection parts of ElipSys and gives an overview of its execution model. ElipSys is a logic programming system being developed at ECRC. It combines parallelism, constraint satisfaction on finite domains, and tight database coupling. Constraints in ElipSys are handled in a way that significantly improves the expressiveness and declarativeness of logic programming and offer an increase in efficiency through parallelism. The garbage collector tackles the additional complexity of the parallel execution environment and takes into consideration also the data generated by the constraint solver. The ElipSys execution model is designed to be appropriate to a range of parallel architectures, from shared to distributed memory machines.

MaTourA is a tourist advisory system about Greece that is being implemented in the parallel constraint logic programming language ElipSys. The purpose of MaTourA is to facilitate the work carried out in travel agencies by providing an interactive way to construct personalized tours, select predefined package tours and handle the underlying touristic information. The system has been designed as a set of high-level interacting agents. In this direction, the ElipSys language was extended with the appropriate features to support the development of multi-agent systems.

Many areas of scientific endeavour can be characterized as the attempt to provide a consistent interpretation of a broad range of heterogeneous data and theories. In the area of protein structure prediction, for example, there are many types of diverse mutually constraining data and theories of protein structural organization that need to be integrated in order to produce a single consistent prediction (or set of predictions) of the protein structure from the experimentally derived amino acid sequence data. Understanding the role and function of proteins in the control of cell growth is an important part of contemporary cancer research. Protein structure prediction is immensely (combinatorially) complex, and traditional computational approaches to problems such as this have been based on the ''generate and test' paradigm in which hypotheses are first generated and then tested against any relevant constraints. In this paper we demonstrate the benefits of a new approach to solving large constrained combinatorial problems which uses the 'constrain-and-generate' paradigm and the ElipSys parallel constraint logic programming system. In ElipSys, constraints are used for a priori pruning of the search tree while parallelism enhances the efficiency of the remaining search. Initial results show several orders of magnitude increase in performance over a sequential logic programming (Prolog) approach. The improved performance can be attributed to the complementary actions of the constraint handling and support for parallelism in the ElipSys runtime system. Taken together, the additional performance and new knowledge representation techniques made possible using ElipSys significantly extend the range and complexity of scientific problems that can be addressed using logic programming languages.