The knapsack problem is an NP-complete problem. Its resolution for large-scale instances requires prohibitive processing time. Lots of algorithms are proposed, but none is based on the cluster. A parallel algorithm fo...
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ISBN:
(纸本)0780384032
The knapsack problem is an NP-complete problem. Its resolution for large-scale instances requires prohibitive processing time. Lots of algorithms are proposed, but none is based on the cluster. A parallel algorithm for the knapsack problem based on the cluster and the two-list algorithm is introduced in this paper. With a proper number of processors, the communication cost is reduced to an appropriate proportion.
With the progress of research on cluster computing, many universities have begun to offer various courses covering cluster computing. A wide variety of content can be taught in these courses. Because of this variation...
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With the progress of research on cluster computing, many universities have begun to offer various courses covering cluster computing. A wide variety of content can be taught in these courses. Because of this variation, a difficulty that arises is the selection of appropriate course material. The selection is complicated because some content in cluster computing may also be covered by other courses in the undergraduate curriculum, and the background of students enrolled in cluster computing courses varies. These aspects of cluster computing make the development of good course material difficult. Combining experiences in teaching cluster computing at universities in the United States and Australia, this piper presents prospective topics in cluster computing and A wide variety of information sources from which instructors can choose. The course material is described in relation to the knowledge units of the Joint IEEE Computer Society and the Association for Computing Machinery (ACM) Computing Curricula 2001 and, includes system architecture, parallel programming, algorithms, and applications. Instructors can select units in each of the topical areas and develop their own syllabi to meet course objectives. The authors share their experiences in teaching cluster computing and the topics chosen, depending on course objectives.
A parallel algorithm for prefix computation was reported on a recently proposed interconnection network called optical multi-trees (OMULT) [6]. Using 2n3 - nn processors, the algorithm was shown to run in O(log n)A el...
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In the paper the parallel algorithms of the Finite-Difference Time-Domain method are presented. Those algorithms are based on the space domain decomposition. In the presented work, communications among computation nod...
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ISBN:
(纸本)3540219463
In the paper the parallel algorithms of the Finite-Difference Time-Domain method are presented. Those algorithms are based on the space domain decomposition. In the presented work, communications among computation nodes in a cluster of PCs and the efficiency of the parallel algorithms are also discussed....
In this paper we present a coarse-grained parallel multilevel algorithm for the k-way hypergraph partitioning problem. The algorithm significantly improves on our previous work in terms of run time and scalability beh...
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In this paper, we propose a new distribution scheme for a parallel Strassen's matrix multiplication algorithm on heterogeneous clusters. In the heterogeneous clustering environment, appropriate data distribution i...
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ISBN:
(纸本)0769521320
In this paper, we propose a new distribution scheme for a parallel Strassen's matrix multiplication algorithm on heterogeneous clusters. In the heterogeneous clustering environment, appropriate data distribution is the most important factor for achieving maximum overall performance. However, Strossen's algorithm reduces the total operation count to about 7/8 times per one recursion and, hence, the recursion level has an effect on the total operation count. Thus, we need to consider not only load balancing but also the recursion level in Strossen's algorithm. Our scheme achieves both load balancing and reduction of the total operation count. As a result, we achieve a speedup of nearly 21.7% compared to the conventional parallel Strossen's algorithm in a heterogeneous clustering environment.
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.
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