Token bus interconnection network for tightly-coupled multiprocessor systems

The end product of this research is the development of an efficient method of interconnecting hundreds of processors via buses that use techniques known in local area network systems. The buses provide a high bandwidth channel with a token bus protocol that significantly reduces the latency found in most interconnection systems. The system consists of a bus interface unit to provide an interface between each processor and the buses. The system provides multiple buses to increase the system throughput and reliability. The token bus protocol is based on the IEEE 802.4 protocol with modifications to facilitate the use of multiple buses;The dissertation describes the interconnection network and the performance of the network. The bus interface unit and the token bus protocol are defined. The network supports two types of media. Both are described and a comparison is made between them. The performance of the token bus protocol is studied and compared with other protocols;The interconnection network is compared with several other interconnection networks using both cost and performance measures. The token bus interconnection network shows better performance and higher network quality than the other networks

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

Reliability Analysis of the Hypercube Architecture.

This dissertation presents improved techniques for analyzing network-connected (NCF), 2-connected (2CF), task-based (TBF), and subcube (SF) functionality measures in a hypercube multiprocessor with faulty processing elements (PE) and/or communication elements (CE). These measures help study system-level fault tolerance issues and relate to various application modes in the hypercube. Solutions discussed in the text fall into probabilistic and deterministic models. The probabilistic measure assumes a stochastic graph of the hypercube where PE\u27s and/or CE\u27s may fail with certain probabilities, while the deterministic model considers that some system components are already failed and aims to determine the system functionality. For probabilistic model, MIL-HDBK-217F is used to predict PE and CE failure rates for an Intel iPSC system. First, a technique called CAREL is presented. A proof of its correctness is included in an appendix. Using the shelling ordering concept, CAREL is shown to solve the exact probabilistic NCF measure for a hypercube in time polynomial in the number of spanning trees. However, this number increases exponentially in the hypercube dimension. This dissertation, then, aims to more efficiently obtain lower and upper bounds on the measures. Algorithms, presented in the text, generate tighter bounds than had been obtained previously and run in time polynomial in the cube dimension. The proposed algorithms for probabilistic 2CF measure consider PE and/or CE failures. In attempting to evaluate deterministic measures, a hybrid method for fault tolerant broadcasting in the hypercube is proposed. This method combines the favorable features of redundant and non-redundant techniques. A generalized result on the deterministic TBF measure for the hypercube is then described. Two distributed algorithms are proposed to identify the largest operational subcubes in a hypercube C\sb{n} with faulty PE\u27s. Method 1, called LOS1, requires a list of faulty components and utilizes the CMB operator of CAREL to solve the problem. In case the number of unavailable nodes (faulty or busy) increases, an alternative distributed approach, called LOS2, processes m available nodes in O(mn) time. The proposed techniques are simple and efficient

Three Highly Parallel Computer Architectures and Their Suitability for Three Representative Artificial Intelligence Problems

Virtually all current Artificial Intelligence (AI) applications are designed to run on sequential (von Neumann) computer architectures. As a result, current systems do not scale up. As knowledge is added to these systems, a point is reached where their performance quickly degrades. The performance of a von Neumann machine is limited by the bandwidth between memory and processor (the von Neumann bottleneck). The bottleneck is avoided by distributing the processing power across the memory of the computer. In this scheme the memory becomes the processor (a smart memory ). This paper highlights the relationship between three representative AI application domains, namely knowledge representation, rule-based expert systems, and vision, and their parallel hardware realizations. Three machines, covering a wide range of fundamental properties of parallel processors, namely module granularity, concurrency control, and communication geometry, are reviewed: the Connection Machine (a fine-grained SIMD hypercube), DADO (a medium-grained MIMD/SIMD/MSIMD tree-machine), and the Butterfly (a coarse-grained MIMD Butterflyswitch machine)

A bibliography on parallel and vector numerical algorithms

This is a bibliography of numerical methods. It also includes a number of other references on machine architecture, programming language, and other topics of interest to scientific computing. Certain conference proceedings and anthologies which have been published in book form are listed also

Redundancy management for efficient fault recovery in NASA's distributed computing system

The management of redundancy in computer systems was studied and guidelines were provided for the development of NASA's fault-tolerant distributed systems. Fault recovery and reconfiguration mechanisms were examined. A theoretical foundation was laid for redundancy management by efficient reconfiguration methods and algorithmic diversity. Algorithms were developed to optimize the resources for embedding of computational graphs of tasks in the system architecture and reconfiguration of these tasks after a failure has occurred. The computational structure represented by a path and the complete binary tree was considered and the mesh and hypercube architectures were targeted for their embeddings. The innovative concept of Hybrid Algorithm Technique was introduced. This new technique provides a mechanism for obtaining fault tolerance while exhibiting improved performance

A Portable Multicomputer Communication Library atop the Reactive Kernel

Sophisticated multicomputer applications require efficient, flexible, convenient underlying communication primitives. In the work described here, Zipcode, a new, portable communication library, has been designed, developed, articulated and evaluated. The primary goals were: high efficiency compared to lowest-level primitives, user-definable message receipt selectivity, as well as abstraction of collections of processes and message selectivity to allow multiple, independently conceived libraries to work together without conflict. Zipcode works atop the Caltech Reactive Kernel, a portable, minimalistic multicomputer node operating system. Presently, the Reactive Kernel is implemented for Intel iPSC/1, iPSC/2, and Symult s2010 multicomputers and emulated on shared-memory computers as well as networks of Sun workstations. Consequently, Zipcode addresses an equally wide audience, and can plausibly be run in other environments

Implementing a tool for designing portable parallel programs

The Implementation aspects of a novel parallel programming model called Cluster-M is presented in this thesis. This model provides an environment for efficiently designing highly parallel portable software. The two main components of this model are Cluster-M Specifications and Cluster-M Representations. A Cluster-M Specification consists of a number of clustering levels emphasizing computation and communication requirements of a parallel solution to a given problem. A Cluster-M Representation on the other hand, represents a multi-layered partitioning of a system graph corresponding to the topology of the target architecture. A set of basic constructs essential for writing Cluster-M Specifications using PCN are presented. Also, a. C program for generating the Cluster-M Representations is shown. Cluster-M Specifications are to be mapped onto the Representations using a proposed mapping methodology. Using Cluster-M a single software can be ported among various parallel computing systems. This thesis concentrates on the implementation of the Specifications and the Representations