The initial version of PRISM uses a simulation of the ZMOB hardware, and has been fully tested and debugged. In addition, several enhancements were made to PRISM to permit experimental analyses to be made, and to incorporate additional features to take full advantage of parallelism in a problem solving environment. Tracing and a statistical gathering package were added to permit experimental analysis. An AND-parallelism capability was added to achieve a second version of the PRISM system, and other features were added to the system to more fully exploit parallelism. Preliminary application and evaluation studies were performed.
This progress report summarizes work performed under AFOSR-88-0152 on parallel logic programming, problem solving, and deductive databases. A parallel problem solving system, PRISM (Parallel Inference System), that was implemented on McMOB was ported to the BBN Butterfly machine. Two versions of PRISM were developed and are operational on the Butterfly: a message passing ring structure system and a shared-memory system. Experimental testing of PRISM on McMOB continued, while experiments were also conducted on the Butterfly systems. Three enhancements were made and completed during the grant period. These are: a capability to handle negated queries and a capability to assert and retract statements. In addition to the above, work continued in the area of informative answers to queries in deductive data bases. A thesis was completed on the subject. An interpreter was developed and is running, that can take restricted natural language as input and can respond with a cooperative natural language output. In the area of parallel software development, the following were accomplished. Theoretical work on slicing/splicing was completed. Tools were provided for software development using artificial intelligence techniques. AI software for massively parallel architectures was started. (kr).
Multiprocessor Execution of Logic Programs addresses the problem of efficient implementation of logic programming languages, specifically Prolog, on multiprocessor architectures. The approaches and implementations developed attempt to take full advantage of sequential implementation technology developed for Prolog (such as the WAM) while exploiting all forms of control parallelism present in logic programs, namely, or-parallelism, independent and-parallelism and dependent and-parallelism. Coverage includes a thorough survey of parallel implementation techniques and parallel systems developed for Prolog. Multiprocessor Execution of Logic Programs is recommended for people implementing parallel logic programming systems, parallel symbolic systems, parallel AI systems, and parallel theorem proving systems. It will also be useful to people who wish to learn about the implementation of parallel logic programming systems.
Constraint Logic Programming (CLP), an area of extreme research interest in recent years, extends the semantics of Prolog in such a way that the combinatorial explosion, a characteristic of most problems in the field of Artificial Intelligence, can be tackled efficiently. By employing solvers dedicated to each domain instead of the unification algorithm, CLP drastically reduces the search space of the problem, which leads to increased efficiency in the execution of logic programs. CLP offers the possibility of solving complex combinatorial problems in an efficient way, and at the same time maintains the advantages offered by the declarativeness of logic programming. The aim of this book is to present parallel and constraint logic programming, offering a basic understanding of the two fields to the reader new to the area. The first part of the book gives an introduction to the fundamental aspects of conventional logic programming which is necessary for understanding the parts that follow. The second part includes an introduction to parallel logic programming, architectures and implementations proposed in the area. Finally, the third part presents the principles of constraint logic programming. The last two parts also include descriptions of the supporting facilities for the two paradigms in two popular systems; ECLIPSe and SICStus. These platforms have been selected mainly because they offer both parallel and constraint features. Annotated and explained examples are also included in the relevant parts, offering a valuable guide and a first practical experience to the reader. Finally, applications of the covered paradigms are presented. The authors felt that a book of this kind should provide some theoretical background necessary for the understanding of the covered logic programming paradigms, and a quick start for the reader interested in writing parallel and constraint logic programming programs. However it is outside the scope of this book to provide a deep theoretical background of the two areas. In that sense, this book is addressed to a public interested in obtaining a knowledge of the domain, without spending the time and effort to understand the extensive theoretical work done in the field – namely postgraduate and advanced undergraduate students in the area of logic programming. This book fills a gap in the current bibliography, since there is no comprehensive book of this level that covers the areas of conventional, parallel, and constraint logic programming. Parallel and Constraint Logic Programming: An Introduction to Logic, Parallelism and Constraints is appropriate for an advanced level course on Logic Programming or Constraints, and as a reference for practitioners and researchers in industry.
This final report presents a summary of research accomplished to investigate parallel problem solving. Under the current grant a parallel problem solving system, PRISM (Parallel Inference System), that was implemented on the VAX/11-780, the PYRAMID and SUN machines, was ported successfully to McMOB and then to the BBN Butterfly parallel architecture. The McMOB architecture is essentially the ZMOB architecture with 16 Motorola 68000 processors, upgrading the Z80A microprocessors, interconnected in a ring structure. Experimental testing of PRISM on McMOB was undertaken in the current year. In addition, several enhancements were made to PRISM to permit experimental analyses to be made, and to incorporate additional features to take full advantage of parallelism in a problem solving environment. The tracing and statistical gathering packages were extended. An ability to display AND-parallelism was added to the trace program which displays the execution of a program on the parallel machines. In addition to the above, work continued in the area of informative answers to be presented to a user. Heuristic techniques were developed to determine which information to display. Keywords: Splicing compilers, Debugging software, Artificial intelligence. (KR).
Highly parallel machines have been available for many years but, because advances in hardware have always outpaced progress in software development, designers and users of these machines have yet to realize their full potential. Until recently there have been few, if any, high-class parallel programming languages that could be implemented on the wide variety of parallel processing systems in use. This book helps to redress the balance by teaching programming techniques as well as performance analysis of parallel programming languages and architectures using logic programming; specifically, it focuses on the Prolog-like languages OR-parallel Prolog and AND-parallel FGHC. Parallel Logic Programmingbrings to light practical applications of a previously esoteric/theoretical area of parallel logic programming and is unique in presenting programming hand-in-hand with performance analysis of real empirical measurements. Its quantitative approach to symbolic parallel programming provides students and professionals with tools for implementing and critically evaluating larger projects. The book includes useful chapter summaries, programming projects, and a glossary.
