The connected vertex cover problem is a variant of the vertex cover problem, in which a vertex cover is additional required to induce a connected subgraph in a given connected graph. The problem is known to be NP-hard...
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The connected vertex cover problem is a variant of the vertex cover problem, in which a vertex cover is additional required to induce a connected subgraph in a given connected graph. The problem is known to be NP-hard and to be at least as hard to approximate as the vertex cover problem is. While several 2-approximation NC algorithms are known for vertex cover, whether unweighted or weighted, no parallel algorithm with guaranteed approximation is known for connected vertex cover. Moreover. converting the existing sequential 2-approximation algorithms for connected vertex cover to parallel ones results in RNC algorithms of rather high complexity at best. In this paper we present a 2-approximation NC (and RNC) algorithm for connected vertex cover (and tree cover). The NC algorithm runs in O(log(2) n) time using O(Delta(2)(m + n)/log n) processors on an EREW-PRAM, while the RNC algorithm runs in O(log n) expected time using O(m + n) processors on a CRCW-PRAM, when a given graph has n vertices and in edges with maximum vertex degree of Delta. (C) 2004 Elsevier B.V. All rights reserved.
This paper presents an efficient parallel algorithm for the shortest path problem in planar layered digraphs that runs in O(log^3n) time with n processors. The algorithms uses a divide and conquer approach and is base...
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This paper presents an efficient parallel algorithm for the shortest path problem in planar layered digraphs that runs in O(log^3n) time with n processors. The algorithms uses a divide and conquer approach and is based on the novel idea of a one-way separator, which has the property that any directed path can be crossed only once.
The tremendous amount of data generated by large-scale, parallel scientific and engineering simulations make the analysis and archiving of this data difficult. To address this problem, in previous work, we developed a...
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ISBN:
(纸本)0769521320
The tremendous amount of data generated by large-scale, parallel scientific and engineering simulations make the analysis and archiving of this data difficult. To address this problem, in previous work, we developed an efficient archival scheme based on the functional representation of simulation data - this approximation scheme can significantly reduce storage requirements. However, common visualization tools such as the marching cubes algorithm for isosurface generation cannot be directly applied with this data representation. Thus, in this paper we propose a new, efficient isosurface visualization algorithm that takes full advantage of the functional approximation of simulation data. This method is fundamentally different from the marching cubes approach in that the visualization of isosurface is achieved through the solution of sets of ordinary differential equations. We present computational results detailing the effectiveness of this new approach for a simulation modeling the fluid dynamics of a turbulent reacting flow. The results demonstrate that the method is efficient in a parallel environment and represents a promising approach for the visualization of isosurface in simulation data from large-scale scientific applications.
Permanent of a matrix is # p - complete problem shown by many authors. In this paper we present a parallel algorithm for evaluation of permanent of an n × n matrix with multi processors.
Permanent of a matrix is # p - complete problem shown by many authors. In this paper we present a parallel algorithm for evaluation of permanent of an n × n matrix with multi processors.
In this work we are concerned with the solution of a nonlocal boundary value problem. An approach is presented for solving the two-dimensional parabolic partial differential equation subject to integral boundary speci...
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In this work we are concerned with the solution of a nonlocal boundary value problem. An approach is presented for solving the two-dimensional parabolic partial differential equation subject to integral boundary specifications. The main objective is to propose an alternative method of solution, one not based on finite difference methods or finite element schemes or spectral techniques. The aim of the present paper is to investigate the application of the Adomian decomposition method for solving the two-dimensional linear parabolic partial differential equation with nonlocal boundary specifications replacing the classical boundary conditions. The Adomian decomposition method is used by many researchers to investigate several scientific applications and requires less work if compare with the traditional techniques. The introduction of this idea as will be discussed, not only provides the solution in a series form but it also guarantees considerable saving of the calculations volume. The solutions will be handle more easily, quickly and elegantly without linearizing the problem by implementing the decomposition method rather than the standard methods for the exact solutions. In this approach the solution is found in the form of a convergent power series with easily computed components. The Adomian decomposition scheme is easy to program in applied problems and provides immediate and convergent solutions without any need for linearization or discretization. To give a clear overview of the methodology, we have selected illustrative example. (C) 2003 Elsevier Inc. All rights reserved.
Early suggested parallel "ring" algorithm for solving of the spatially one-dimensional initial-boundary-value problem (IBVP) for a parabolic equation using an explicit difference method is shortly described....
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ISBN:
(纸本)3540219463
Early suggested parallel "ring" algorithm for solving of the spatially one-dimensional initial-boundary-value problem (IBVP) for a parabolic equation using an explicit difference method is shortly described. Asymptotical behaviour of the communication complexity of this parallel algorithm is studied. Communication complexity is determined as a ratio between the number of interchanges and the number of arithmetical operations. It is proved that the coefficient of the communication complexity for spatially m-dimensional IBVP tends in general to 3/4.
In this article we discuss sparse matrix algorithms and parallel algorithms, as well as their application to large-scale systems. For illustration, we solve the linear-quadratic regulator (LQR) problem and apply balan...
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In this article we discuss sparse matrix algorithms and parallel algorithms, as well as their application to large-scale systems. For illustration, we solve the linear-quadratic regulator (LQR) problem and apply balanced truncation model reduction using either parallel computing or sparse matrix algorithms. We conclude that modern tools from numerical linear algebra, along with careful investigation and exploitation of the problem structure, can be used to derive algorithms capable of solving large control problems. Since these approaches are implemented in production-quality software, control engineers can employ complex models and use computational tools to analyse and design feedback control laws.
An independent set in a graph G is a set I subset of or equal to V(G) such that the induced subgraph on I has no edges. A maximal independent set (MIS) is an independent set not properly contained in any other indepen...
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An independent set in a graph G is a set I subset of or equal to V(G) such that the induced subgraph on I has no edges. A maximal independent set (MIS) is an independent set not properly contained in any other independent set. We present a simple proof that an algorithm of Luby [SIAM J. Comput. 15 (1986) 1036] is an RNC algorithm for finding an MIS in a graph. Our proof can be easily derandomized, giving a corresponding NC algorithm. (C) 2004 Elsevier B.V. All rights reserved.
Determining 3-dimensional (3D) structures of proteins is still a challenging problem. Certain experimental techniques can produce partial information about protein structures, yet not enough to solve the structure. In...
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ISBN:
(纸本)3540241280
Determining 3-dimensional (3D) structures of proteins is still a challenging problem. Certain experimental techniques can produce partial information about protein structures, yet not enough to solve the structure. In this paper, we investigate the problem of relating such partial information to its protein sequence. We developed an algorithm of building a library to map helices in a 3D structure to its 1-dimensional (1D) structure using the length constraints of helices, obtained from such partial information. We present a parallel algorithm for building a mapping tree using dynamic distributed scheduling for load balancing. The algorithm shows near linear speedup for up to 20 processors tested. If the protein secondary structure prediction is good, the library contains a mapping that correctly assigns the majority of the helices in the protein.
In this paper, we set up a geometric framework for solving sparse rnatrix problems. We introduce geometric sparseness, a notion which applies to several well-known families of sparse matrix. Two algorithms are present...
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In this paper, we set up a geometric framework for solving sparse rnatrix problems. We introduce geometric sparseness, a notion which applies to several well-known families of sparse matrix. Two algorithms are presented for solving geometrically-sparse rnatrix problems. These algorithms are inspired by techniques in classical algebraic topology, and involve the construction of a simplicial complex from certain data on the matrix. In both cases, large parts of the computation can be parallelised. (C) 2003 Elsevier Inc. All rights reserved.
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