Liviu Octavian Mafteiu-Scai, Calin Alexandru Cornigeanu
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引用次数: 2
Abstract
This paper proposes a parallel hybrid heuristic aiming the reduction of the bandwidth of sparse matrices. Mainly based on the geometry of the matrix, the proposed method uses a greedy selection of rows/columns to be interchanged, depending on the nonzero extremities and other parameters of the matrix. Experimental results obtained on an IBM Blue Gene/P supercomputer illustrate the fact that the proposed parallel heuristic leads to better results, with respect to time efficiency, speedup, efficiency and quality of solution, in comparison with serial variants and of course in comparison with other reported results.
提出了一种以减少稀疏矩阵带宽为目标的并行混合启发式算法。该方法主要基于矩阵的几何特性,根据矩阵的非零极值和其他参数,贪婪地选择待交换的行/列。在IBM Blue Gene/P超级计算机上获得的实验结果表明,与串行变量相比,当然也与其他报告的结果相比,所提出的并行启发式在时间效率、加速、效率和解决方案质量方面都有更好的结果。