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

Massively-parallel marker-passing in semantic networks

AbstractOne approach to using the information available in a semantic network is the use of marker-passing algorithms, which propagate information through the network to determine relationships between objects. One of the primary arguments in favor of these algorithms are their ability to be implemented in parallel. Despite this, most implementations have been serial and have only sometimes gone so far as to simulate parallelism. In this paper the marker-passing approach is presented. An actual parallel implementation which shows that such programs can be written on commercially available massively parallel machines is also presented

Rediflow architecture prospectus

Journal ArticleRediflow is intended as a multi-function (symbolic and numeric) multiprocessor, demonstrating techniques for achieving speedup for Lisp-coded problems through the use of advanced programming concepts, high-speed communication, and dynamic load-distribution, in a manner suitable for scaling to upwards of 10,000 processors. An initial physical realization is proposed employing 16 nodes (initially in a hypercube topology), with processor, memory, and intelligent switch at each node

A Survey of Parallel Programming Constructs

This paper surveys the types of parallelism found in Functional, Lisp and Object-Oriented languages. In particular, it concentrates on the addition of high level parallel constructs to these types of languages. The traditional area of the automatic extraction of parallelism by a compiler [39] is ignored here in favor of the addition of new constructs, because the long history of such automatic techniques has shown that they are not sufficient to allow the massive parallelism promised from modem computer architectures [26. 58]. The problem then, simply stated, is given that it is now possible for us to build massively parallel machines and given that our current compilers seem incapable of generating sufficient parallelism automatically, what should the language designer do? A reasonable answer seems to be to add constructs to languages that allow the expression of additional parallelism in a natural way. Indeed that is what the designers of the the Functional, Lisp, and Object-Oriented languages described below have attempted to do. The three particular programming formalisms were picked because most of the initial ideas seem to have been generated by the designers of the functional languages and most of the current activity seems to be in the Lisp and Objected-Oriented domains. There is also a great deal of activity in the Logic programming area, but this activity is more in the area of executing the existing constructs in parallel as opposed to adding constructs specifically designed to increase parallelism

The Incremental Garbage Collection of Processes

Key Words and Phrases: garbage collection, multiprocessing systems, processor scheduling. "lazy evaluation, "eager" evaluation. CR Categories: 3.60, 3.80, 4.13, 4.22, 4.32. This report describes research done at the Artificial Intelligence Laboratory of the Massachusetts Institute of Technology. Support for the laboratory's artificial intelligence research is provided in part by the Advanced Research Projects Agency of the Department of Defense under Office of Naval Research contract N00014-75-C-0522. This paper was presented at the AI*PL Conference at Rochester, N.Y. in August, 1977.This paper investigates some problems associated with an argument evaluation order that we call "future" order, which is different from both call-by-name and call-by-value. In call-by-future, each formal parameter of a function is bound to a separate process (called a "future") dedicated to the evaluation of the corresponding argument. This mechanism allows the fully parallel evaluation of arguments to a function, and has been shown to augment the expressive power of a language. We discuss an approach to a problem that arises in this context: futures which were thought to be relevant when they were created become irrelevant through being ignored in the body of the expression where they were bound. The problem of irrelevant processes also appears in multiprocessing problem-solving systems which start several processors working on the same problem but with different methods, and return with the solution which finishes first. This parallel method strategy has the drawback that the processes which are investigating the losing methods must be identified, stopped, and re-assigned to more useful tasks. The solution we propose is that of garbage collection. We propose that the goal structure of the solution plan be explicitly represented in memory as part of the graph memory (like Lisp's heap) so that a garbage collection algorithm can discover which processes are performing useful work, and which can be recycled for a new task. An incremental algorithm for the unified garbage collection of storage and processes is described.MIT Artificial Intelligence Laboratory Department of Defense Advanced Research Projects Agenc

The ModelCC Model-Driven Parser Generator

Syntax-directed translation tools require the specification of a language by means of a formal grammar. This grammar must conform to the specific requirements of the parser generator to be used. This grammar is then annotated with semantic actions for the resulting system to perform its desired function. In this paper, we introduce ModelCC, a model-based parser generator that decouples language specification from language processing, avoiding some of the problems caused by grammar-driven parser generators. ModelCC receives a conceptual model as input, along with constraints that annotate it. It is then able to create a parser for the desired textual syntax and the generated parser fully automates the instantiation of the language conceptual model. ModelCC also includes a reference resolution mechanism so that ModelCC is able to instantiate abstract syntax graphs, rather than mere abstract syntax trees.Comment: In Proceedings PROLE 2014, arXiv:1501.0169

Computational methods and software systems for dynamics and control of large space structures

Two key areas of crucial importance to the computer-based simulation of large space structures are discussed. The first area involves multibody dynamics (MBD) of flexible space structures, with applications directed to deployment, construction, and maneuvering. The second area deals with advanced software systems, with emphasis on parallel processing. The latest research thrust in the second area involves massively parallel computers

An abstract machine for parallel graph reduction

technical reportAn abstract machine for parallel graph reduction on a shared memory multiprocessor is described. This is intended primarily for normal order (lazy) evaluation of functional programs. It is absolutely essential in such a design to adapt an efficient sequential model since during execution under limited resources available, performance will be reduced in the limit to that of the sequential engine. Parallel evaluation of normal order functional languages performed naively can result in poor overall performance despite the availability of sufficient processing elements and parallelism in the application. Needless context switching, task migration and continuation building may occur when a sequential thread of control would have sufficed. Furthermore, the compiler using static information cannot be fully aware of the availability of resources and their optimal utilization at any moment in run time. Indeed this may vary between runs which further aggravates the job of the compiler writer in generating optimal and compact code for programs. The benefits derived from this model are: 1) it is based on the G-machine so that execution under limited resources will default to a performance close to that of the G-machine; 2) the additional instructions needed to control the complexities of parallel evaluation are extremely simple, almost trivializing the job of the compiler writer; 3) attempts are made where possible to avoid context switching and task migration by retaining a sequential thread of control (made more clear in the paper), and 4) the method has demonstrated good overall performance on a shared memory multiprocessor