The recognition of polygons in 3-D space is an important task in robot vision. Advances in VLSI technology have now made it possible to implement inexpensive, efficient and very fast custom designs. The authors have e...
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The recognition of polygons in 3-D space is an important task in robot vision. Advances in VLSI technology have now made it possible to implement inexpensive, efficient and very fast custom designs. The authors have earlier proposed a class of VLSI architectures for this computationally intensive task, which makes use of a set of local shape descriptors for polygons which are invariant under affine transformations, i.e. translation, scaling, rotation and orthographic projection from 3-D to any 2-D plane. This paper discusses the design and implementation of PMAC, a prototype for polygon matching, as a custom CMOS VLSI chip. The recognition procedure is based on the matching of edge-length ratios using a simplified version of the dynamic programming procedure commonly employed for string matching. The matching procedure also copes with partial occlusions of polygons. The implemented architecture is systolic and fully utilizes the principles of pipelining and parallelism in order to obtain high speed and throughput.
Massively parallel computers have become widely available for the solution of a wide range of numerical problems. However, methods that work well on single processor architectures are often not the best algorithms whe...
Massively parallel computers have become widely available for the solution of a wide range of numerical problems. However, methods that work well on single processor architectures are often not the best algorithms when multiple processors are available. In this paper, we present a dynamic programming approach to the numerical solution of elliptic partial differential equations. This method, based upon the earlier work of Angel and others, indicates that reconsideration of direct (noniterative) approaches to the numerical solution of partial differential equations can lead to competitive algorithms.
The activity of research group of massively parallelprogramming language is introduced. This group is developing two types of languages. The first one is the SIMD type language called NCX which is oriented toward dat...
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The activity of research group of massively parallelprogramming language is introduced. This group is developing two types of languages. The first one is the SIMD type language called NCX which is oriented toward data parallel execution, and the second is the MIMD type highly asynchronous language called V, which is oriented toward data parallel and concurrent object oriented language. The NCX is designed as a data parallel extension of the language C in order to support practical massively parallel computations especially in the application area of scientific computations. The language V on the other hand is designed as an experimental language for exploring a new massively parallelprogramming paradigm.
Maher proposed the ALPS class of committed-choice languages, which can be seen as a further development of concurrent logic programming languages in the direction of CLP(X). However, due to the lack of OR-nondetermini...
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Maher proposed the ALPS class of committed-choice languages, which can be seen as a further development of concurrent logic programming languages in the direction of CLP(X). However, due to the lack of OR-nondeterminism, ALPS is a class of declarative algorithmic programming languages. In this paper, we present the FENG class of concurrent constraint logic programming languages and give its soundness and completeness results. With the novel feature of constraint based nondeterminism, FENG enriches the semantics of the ALPS and CLP(X). One of the features of FENG is that it supports constraint based nondeterminism. For some class of programs, this much improves the efficiency of program execution. FENG reveals a direction for data-parallel implementations of constraint logic programs. This has been confirmed by our experience in design and implementation of Firebird, a restriction of FENG, on the massively parallel machine DECmpp.
The majority of numerical algorithms employs floating-point vector and matrix operations. On a parallel computer these algorithms should be solved fast and reliably in order to avoid a time-consuming error analysis. T...
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The majority of numerical algorithms employs floating-point vector and matrix operations. On a parallel computer these algorithms should be solved fast and reliably in order to avoid a time-consuming error analysis. The XSC-languages (high-level language extensions for eXtended Scientific Computation) are well-suited for this purpose since they support the design of numerical algorithms delivering correct and automatically verified results. This goal is attained by an arithmetic with maximum accuracy (especially for vector and matrix operations), highly accurate standard functions, and exact evaluation of dot product expressions. Within the ESPRIT parallel Computing Action, one XSC-language, PASCAL-XSC, was implemented on a Supercluster Transputer System under the operating system HELIOS. parallel algorithms for computationally intensive and maximally accurate matrix operations were implemented and tested on various transputer architectures. We will sketch some features of these architectures and present some benchmarks for the algorithms used. These algorithms form a parallel C runtime library of PASCAL-XSC (or any other XSC-language that uses a C runtime library) and are called automatically. This can be considered a basis for implicit parallelization in an XSC-language.
Some reactive scattering codes have been ported on different innovative computer architectures ranging from massively parallel machines to clustered workstations. The porting has required a drastic restructuring of th...
Some reactive scattering codes have been ported on different innovative computer architectures ranging from massively parallel machines to clustered workstations. The porting has required a drastic restructuring of the codes to single out computationally decoupled cpu intensive subsections. The suitability of different theoretical approaches for parallel and distributed computing restructuring is discussed and the efficiency of related algorithms evaluated. (C) 1994 John Wiley & Sons, Inc.
The proceedings contain 38 papers. The topics discussed include: efficient compilation of high-level data parallel algorithms;improved abstract parity-declustered layouts for disk arrays;experiences with parallel n-bo...
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(纸本)0897916719
The proceedings contain 38 papers. The topics discussed include: efficient compilation of high-level data parallel algorithms;improved abstract parity-declustered layouts for disk arrays;experiences with parallel n-body simulation;a comparison of parallel algorithms for connected components;studying overheads in massively parallel min/max-tree evaluation;scheduling trees using FIFO queues: a control-memory tradeoff;SIMD instruction cache;dynamic parallel tree contraction;improved bounds for routing and sorting on multi-dimensional meshes;parallel sorting by overpartitioning;an optimal randomized logarithmic time connectivity algorithm for the EREW PRAM;list ranking and list scan on the CRAY C-90;modeling communication in parallel algorithms: a fruitful interaction between theory and systems?;on testing cache-coherent shared memories;diffracting trees;programming abstract DEC-alpha based multiprocessors the easy way;scheduling parallelizable tasks to minimize average response time;and an analysis of diffusive load-balancing.
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