Parallel processing and expert systems

Whether it be monitoring the thermal subsystem of Space Station Freedom, or controlling the navigation of the autonomous rover on Mars, NASA missions in the 1990s cannot enjoy an increased level of autonomy without the efficient implementation of expert systems. Merely increasing the computational speed of uniprocessors may not be able to guarantee that real-time demands are met for larger systems. Speedup via parallel processing must be pursued alongside the optimization of sequential implementations. Prototypes of parallel expert systems have been built at universities and industrial laboratories in the U.S. and Japan. The state-of-the-art research in progress related to parallel execution of expert systems is surveyed. The survey discusses multiprocessors for expert systems, parallel languages for symbolic computations, and mapping expert systems to multiprocessors. Results to date indicate that the parallelism achieved for these systems is small. The main reasons are (1) the body of knowledge applicable in any given situation and the amount of computation executed by each rule firing are small, (2) dividing the problem solving process into relatively independent partitions is difficult, and (3) implementation decisions that enable expert systems to be incrementally refined hamper compile-time optimization. In order to obtain greater speedups, data parallelism and application parallelism must be exploited

The DADO Parallel Computer

DADO is a parallel, tree-structured machine designed to provide significant performance improvements in the execution of large production systems. A full-scale production version of the DADO machine would comprise a large (on the order of a hundred thousand) set of processing elements (PE's), each containing its own processor, a small amount (8K bytes, in the current prototype design) of local random access memory, and a specialized I/O switch. The PE's are interconnected to form a complete binary tree. This paper describes the organization of, and programming language for two prototypes of the DADO system. We also detail a general procedure for the parallel execution of production systems on the DADO machine and outline how this procedure can be extended to include commutative and multiple, independent production systems. We then compare this with the RETE machine matching algorithm, and indicate how PROLOG programs may be implemented directly on DADO

Logic programming in the context of multiparadigm programming: the Oz experience

Oz is a multiparadigm language that supports logic programming as one of its major paradigms. A multiparadigm language is designed to support different programming paradigms (logic, functional, constraint, object-oriented, sequential, concurrent, etc.) with equal ease. This article has two goals: to give a tutorial of logic programming in Oz and to show how logic programming fits naturally into the wider context of multiparadigm programming. Our experience shows that there are two classes of problems, which we call algorithmic and search problems, for which logic programming can help formulate practical solutions. Algorithmic problems have known efficient algorithms. Search problems do not have known efficient algorithms but can be solved with search. The Oz support for logic programming targets these two problem classes specifically, using the concepts needed for each. This is in contrast to the Prolog approach, which targets both classes with one set of concepts, which results in less than optimal support for each class. To explain the essential difference between algorithmic and search programs, we define the Oz execution model. This model subsumes both concurrent logic programming (committed-choice-style) and search-based logic programming (Prolog-style). Instead of Horn clause syntax, Oz has a simple, fully compositional, higher-order syntax that accommodates the abilities of the language. We conclude with lessons learned from this work, a brief history of Oz, and many entry points into the Oz literature.Comment: 48 pages, to appear in the journal "Theory and Practice of Logic Programming

Algorithm to layout (ATL) systems for VLSI design

PhD ThesisThe complexities involved in custom VLSI design together with the failure of CAD techniques to keep pace with advances in the fabrication technology have resulted in a design bottleneck. Powerful tools are required to exploit the processing potential offered by the densities now available. Describing a system in a high level algorithmic notation makes writing, understanding, modification, and verification of a design description easier. It also removes some of the emphasis on the physical issues of VLSI design, and focus attention on formulating a correct and well structured design. This thesis examines how current trends in CAD techniques might influence the evolution of advanced Algorithm To Layout (ATL) systems. The envisaged features of an example system are specified. Particular attention is given to the implementation of one its features COPTS (Compilation Of Occam Programs To Schematics). COPTS is capable of generating schematic diagrams from which an actual layout can be derived. It takes a description written in a subset of Occam and generates a high level schematic diagram depicting its realisation as a VLSI system. This diagram provides the designer with feedback on the relative placement and interconnection of the operators used in the source code. It also gives a visual representation of the parallelism defined in the Occam description. Such diagrams are a valuable aid in documenting the implementation of a design. Occam has also been selected as the input to the design system that COPTS is a feature of. The choice of Occam was made on the assumption that the most appropriate algorithmic notation for such a design system will be a suitable high level programming language. This is in contrast to current automated VLSI design systems, which typically use a hardware des~ription language for input. These special purpose languages currently concentrate on handling structural/behavioural information and have limited ability to express algorithms. Using a language such as Occam allows a designer to write a behavioural description which can be compiled and executed as a simulator, or prototype, of the system. The programmability introduced into the design process enables designers to concentrate on a design's underlying algorithm. The choice of this algorithm is the most crucial decision since it determines the performance and area of the silicon implementation. The thesis is divided into four sections, each of several chapters. The first section considers VLSI design complexity, compares the expert systems and silicon compilation approaches to tackling it, and examines its parallels with software complexity. The second section reviews the advantages of using a conventional programming language for VLSI system descriptions. A number of alternative high level programming languages are considered for application in VLSI design. The third section defines the overall ATL system COPTS is envisaged to be part of, and considers the schematic representation of Occam programs. The final section presents a summary of the overall project and suggestions for future work on realising the full ATL system

DADO: A Parallel Processor for Expert Systems

DADO is a parallel, tree-structured machine designed to provide significant performance improvements in the execution of large expert systems implemented in production system form. A full-scale version of the DADO machine would comprise a large (on the order of a hundred thousand) set of processing elements (PE's), each containing its own processor, a small amount (16K bytes, in the current prototype design) of local random access memory, and a specialized I/O switch. The PE's are introduced to form a complete binary tree. This paper describes the application domain of the DADO machine and the rationale for its design. We then focus on the machine architecture and detail the hardware design of a moderately large prototype comprising 1023 microprocessors currently under development at Columbia University. We conclude with very encouraging performance statistics recently calculated from an analysis of extensive simulations of the system

DADO: A Parallel Processor for Expert Systems

DADO is a parallel, tree-structured machine designed to provide significant performance improvements in the execution of large expert systems implemented in production system form. A full-scale version of the DADO machine would comprise a large (on the order of a hundred thousand) set of processing elements (PE's), each containing its own processor, a small amount (16K bytes, in the current prototype design) of local random access memory, and a specialized I/O switch. The PE's are introduced to form a complete binary tree. This paper describes the application domain of the DADO machine and the rationale for its design. We then focus on the machine architecture and detail the hardware design of a moderately large prototype comprising 1023 microprocessors currently under development at Columbia University. We conclude with very encouraging performance statistics recently calculated from an analysis of extensive simulations of the system