97 research outputs found

    Parallel processing and expert systems

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    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

    Mapping Divide-and-Conquer Algorithms to Parallel Architectures

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    24 pagesIn this paper, we identify the binomial tree as an ideal computation structure for parallel divide-and-conquer algorithms. We show its superiority to the classic full binary tree structure with respect to speedup and efficiency. We also present elegant and efficient algorithms for mapping the binomial tree to two interconnection networks commonly used in multicomputers, namely the hypercube and the two-dimensional mesh. Our mappings are optimal with respect to both average dilation and link contention. We discuss the practical implications of these results for message-passing architectures using store-and-forward routing vs. those using wormhole routing

    OREGAMI: Software Tools for Mapping Parallel Computations to Parallel Architectures

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    22 pagesThe mapping problem in message-passing parallel processors involves the assignment of tasks in a parallel computation to processors and the routing of inter-task messages along the links of the interconnection network. We have developed a unified set of software tools called OREGAMI for automatic and guided mapping of parallel computations to parallel architectures in order to achieve portability and maximal performance from parallel systems. Our tools include a description language which enables the programmer of parallel algorithms to specify information about the static and dynamic communication behavior of the computation to be mapped. This information is used by the mapping algorithms to assign tasks to processors and to route communication in the network topology. Two key features of our system are (a) the ability to take advantage of the regularity present in both the computation structure and the interconnection network and (b) the desire to balance the user's knowledge and intuition with the computational power of efficient combinatorial algorithms

    Visibility-Related Problems on Parallel Computational Models

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    Visibility-related problems find applications in seemingly unrelated and diverse fields such as computer graphics, scene analysis, robotics and VLSI design. While there are common threads running through these problems, most existing solutions do not exploit these commonalities. With this in mind, this thesis identifies these common threads and provides a unified approach to solve these problems and develops solutions that can be viewed as template algorithms for an abstract computational model. A template algorithm provides an architecture independent solution for a problem, from which solutions can be generated for diverse computational models. In particular, the template algorithms presented in this work lead to optimal solutions to various visibility-related problems on fine-grain mesh connected computers such as meshes with multiple broadcasting and reconfigurable meshes, and also on coarse-grain multicomputers. Visibility-related problems studied in this thesis can be broadly classified into Object Visibility and Triangulation problems. To demonstrate the practical relevance of these algorithms, two of the fundamental template algorithms identified as powerful tools in almost every algorithm designed in this work were implemented on an IBM-SP2. The code was developed in the C language, using MPI, and can easily be ported to many commercially available parallel computers

    The nondeterministic divide

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    The nondeterministic divide partitions a vector into two non-empty slices by allowing the point of division to be chosen nondeterministically. Support for high-level divide-and-conquer programming provided by the nondeterministic divide is investigated. A diva algorithm is a recursive divide-and-conquer sequential algorithm on one or more vectors of the same range, whose division point for a new pair of recursive calls is chosen nondeterministically before any computation is performed and whose recursive calls are made immediately after the choice of division point; also, access to vector components is only permitted during activations in which the vector parameters have unit length. The notion of diva algorithm is formulated precisely as a diva call, a restricted call on a sequential procedure. Diva calls are proven to be intimately related to associativity. Numerous applications of diva calls are given and strategies are described for translating a diva call into code for a variety of parallel computers. Thus diva algorithms separate logical correctness concerns from implementation concerns

    The Architecture and Programming of a Fine-Grain Multicomputer

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    The research presented in this thesis was conducted in the context of the Mosaic C, an experimental, fine-grain multicomputer. The objective of the Mosaic experiment was to develop a concurrent-computing system with maximum performance per unit cost, while still retaining a general-purpose application span. A stipulation of the Mosaic project was that the complexity of a Mosaic node be limited by the silicon complexity available on a single VLSI chip. The two most important original results reported in the thesis are: (1) The design and implementation of C+-, a concurrent, object-oriented programming system. Syntactically, C+- is an extension of C++. The concurrent semantics of C+- are contained within the process concept. A C+- process is analogous to a C++ object, but it is also an autonomous computing agent, and a unit of potential concurrency. Atomic single-process updates that can be individually enabled and disabled are the execution units of the concurrent computation. The limited set of primitives that C+- provides is shown to be sufficient to express a variety of concurrent-programming problems concisely and efficiently. An important design requirement for C+- was that efficient implementations should exist on a variety of concurrent architectures, and, in particular, on the simple and inexpensive hardware of the Mosaic node. The Mosaic runtime system was written entirely in C+-. (2) Pipeline synchronization, a novel, generally- applicable technique for hardware synchronization. This technique is a simple, low-cost, high-bandwidth, high- reliability solution to interfaces between synchronous and asynchronous systems, or between synchronous systems operating from different clocks. The technique can sustain the full communication bandwidth and achieve an arbitrarily low, non-zero probability of synchronization failure, Pf, with the price in both latency and chip area being O(log 1/Pf). Pipeline synchronization has been successfully applied to the highperformance inter-computer communication in Mosaic node ensembles

    Silkroad : A system supporting DSM and multiple paradigms in cluster computing

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    Ph.DDOCTOR OF PHILOSOPH

    Submicron Systems Architecture Project: Semiannual Technical Report

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