HyperForest: A high performance multi-processor architecture for real-time intelligent systems

Intelligent Systems are characterized by the intensive use of computer power. The computer revolution of the last few years is what has made possible the development of the first generation of Intelligent Systems. Software for second generation Intelligent Systems will be more complex and will require more powerful computing engines in order to meet real-time constraints imposed by new robots, sensors, and applications. A multiprocessor architecture was developed that merges the advantages of message-passing and shared-memory structures: expendability and real-time compliance. The HyperForest architecture will provide an expandable real-time computing platform for computationally intensive Intelligent Systems and open the doors for the application of these systems to more complex tasks in environmental restoration and cleanup projects, flexible manufacturing systems, and DOE`s own production and disassembly activities

Fault Tolerance of Artificial Neural Networks with Applications in Critical Systems

One of the key benefits of future hardware implementations of certain artificial neural networks (ANN's) is their apparently "built-in" fault tolerance which makes them potential candidates for critical tasks with high reliability requirements. This paper investigates the fault-tolerance characteristics of time-continuous, recurrent ANN's that can be used to solve optimization problems. The principle of operation and the performance of these networks are first illustrated by using well-known model problems like the traveling salesman problem and the assignment problem. The ANN's are then subjected to up to 13 simultaneous "stuck-at-1" or "stuck-at-0" faults for network sizes of up to 900 "neurons." The effect of these faults on the performance is demonstrated and the cause for the observed fault tolerance is discussed. An application is presented in which a network performs a critical task for a real-time distributed processing system by generating new task allocat..