Instruction Sets and Beyond: Computers, Complexity, and Controversy

Some issues in designing computers for artificial intelligence (AI) processing are discussed. These issues are divided into three levels: the representation level, the control level, and the processor level. The representation level deals with the knowledge and methods used to solve the problem and the means to represent it. The control level is concerned with the detection of dependencies and parallelism in the algorithmic and program representations of the problem, and with the synchronization and scheduling of concurrent tasks. The processor level addresses the hardware and architectural components needed to evaluate the algorithmic and program representations. Solutions for the problems of each level are illustrated by a number of representative systems. Design decisions in existing projects on AI computers are classed into top-down, bottom-up, and middle-out approaches. >

A survey on the design of multiprocessing systems for artificial intelligence applications

In this survey, we will provide a short survey and classification on the current work in special purpose architectures to support AI applications. In spite of the growing importance of AI applications, work in the area of designing AI architectures are so diversified that articles were published in other areas besides Al, ranging from psychology, medicine, manufacturing, computer architecture, software engineering, and database management to industrial engineering, operations research, and the list grows. The literature search is also complicated by the fact that with the development of the Fifth-Generation Computer Systems, some work in this area is very recent and was published in many foreign countries. During our literature search to compile this survey, we systematically went through over sixty different journals published in various countries and proceedings from over fifty conferences in the last twenty years and over seventy books.

A survey on special purpose computer architecture for AI

In this survey, we will provide a short survey and classification on the current work in special purpose architectures to support AI applications In spite of the growing importance of AI applications, work in the area of designing AI architectures are so diversified that articles were published in other areas besides Al, ranging from psychology, medicine, manufacturing, computer architecture, software engineering, and database management to industrial engineering, operations research, and the list grows The literature search is also complicated by the fact that with the development of the Fifth-Generation Computer Systems, some work in this area is very recent and was published in many foreign countries During our literature search to compile this survey, we systematically went through over sixty different journals published in various countries and proceedings from over fifty conferences in the last twenty years and over seventy books

Survey on special purpose computer architectures for AI

Preliminary analysis of RISC architectures performance

The article proposes a new Tree-Structured-Architecture (TSA). The TSA is object-oriented, implements the notions of capability-based-addressing and the single-level-store, and it is particularly designed to narrow the semantic gap. It encourages modular programming and directly supports the concepts of tasks and inter-task communication, making it particularly suitable for multiprocessing and multiprogramming implementation.The TSA is implemented on a multi-resource, distributed, matrix-structured, reconfigurable, fault-tolerant computing system, proposed in this article. The system implements some ideas of the dynamic and the flexible architecture. The system possesses a high degree of regularity by implementing large amounts of identical units. The hardware is modular, permitting the addition or removal of groups of units, without a change in the system's software.

Daniel Tabak

Papers

A Tree Structured Architecture for semantic gap reduction

The MODHEL microcomputer for RISCS study

Method for implementing distributed control of a communication system

Introduction to numerical methods for parallel computers: U. Schendel: (Transl. B. W. Conolly), Wiley, New York, 1984, 151 pp

A microprocessor-based Kalman filter