In this paper, we present two parallel algorithms for computing the all nearest neighbors of an n × n binary image on the Bulk-Synchronous parallel(BSP) model. The first algorithm is for weighted distance, and th...
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In this paper, we present two parallel algorithms for computing the all nearest neighbors of an n × n binary image on the Bulk-Synchronous parallel(BSP) model. The first algorithm is for weighted distance, and the second algorithm is for Lp distance. Both two algorithms run in O(n2/p + L) computation time and O(g n/√p + L) communication time using p (1 &le p &le n) processors and in O(n2/p + (d + L)log p/n/log(d + l)) computation time and in O(g n/√p + (gd + L)log p/n/log(d + l)) communication time using p (n 2) processors, for any integer d (1 &le d &le p/n), where L denotes synchronization periodicity and g denotes a reciprocal of communication bandwidth.
We integrate the semantics of higher-order functional programs with a notion of explicit static processes as used in BSP and PRAM algorithms. The result is the construction of a cartesian closed category (CCC), a mode...
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The class of cographs, or complement-reducible graphs, arises naturally in many different areas of applied mathematics and computer science. In this paper we present an O(n) time sequential algorithm and a parallel al...
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The class of cographs, or complement-reducible graphs, arises naturally in many different areas of applied mathematics and computer science. In this paper we present an O(n) time sequential algorithm and a parallel algorithm of O(log n) time and O(n/log n) processors on the EREW PRAM model to solve the maximum weight independent set problem on weighted cographs. Using such algorithms we can easily solve the minimum weight vertex cover, maximum weight clique, minimum weight independent dominating set, minimum weight dominating set, and minimum weight maximal irredundant set problems on weighted cographs with the same bounds of time and processors.
The performance of software executed on a microprocessor is adversely affected by the basic fetch-execute cycle. A further performance penalty results from the load-execute-store paradigm associated with the use of lo...
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In this paper, the basic functionality of the MatSol (MATlab SOLvers) library to the solution of realistic contact problems with millions of degrees of freedom will be presented. The library is based on Matlab Distrib...
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The Prefix Matching Problem is to determine, for each location in the text t, the longest prefix of a given pattern p which occurs beginning at that location. We present two work-optimal parallel algorithms for this p...
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This paper discusses some aspects of implementing parallel algorithms on distributed computer systems like a LAN-connected set of workstations. The notions of parallel and distributed computing are represented by thei...
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Multi-level network optimization (MLNO) problems arise in many contexts such as telecommunication, transportation, or electric power systems. This paper is mainly concerned with parallel implementations of the classic...
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Multi-level network optimization (MLNO) problems arise in many contexts such as telecommunication, transportation, or electric power systems. This paper is mainly concerned with parallel implementations of the classical branch-and-bound algorithm for multi-level network design. A model for such a problem is presented and formulated as a mixed-integer program. The formulation is appealing because it integrates in the same model aspects of discrete facility location, topological network design, and dimensioning. We propose implementations that are suitable for multiple instruction stream, multiple data stream (MIMD) parallel computation systems. Thus, the implementations are very convenient for use in networks of workstations, which nowadays has become so popular. We have tested two versions of the branch-and-bound algorithm as well as different load balancing strategies. The results are very encouraging indicating a gain over sequential computations in terms of execution time.
In this paper we present a general approach for reducing switching activity on the algorithmic level. We concentrate on iterative algorithms that are suitable for an implementation on parallel processor arrays. The re...
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In this paper we present a general approach for reducing switching activity on the algorithmic level. We concentrate on iterative algorithms that are suitable for an implementation on parallel processor arrays. The reduction is substantially reached by avoiding operations that hardly contribute to the convergence of the implemented algorithm. Our general approach is exemplified on the implementation of a specific algorithm, i.e. the eigenvalue decomposition (EVD) of a real symmetric matrix.
This paper adopts a transformational programming approach for deriving massively parallel algorithms from functional specific ations. It gives a brief description of a framework for relating key higher order functions...
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