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An asynchronous algorithm on the NetSolve global computing system

机译:NetSolve全局计算系统上的异步算法

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The explicitly restarted Arnoldi method (ERAM) allows one to find a few eigenpairs of a large sparse matrix. The multiple explicitly restarted Arnoldi method (MERAM) is a technique based upon a multiple projection of ERAM and accelerates its convergence [N. Emamad, S. Petiton, G. Edjlali, Multiple explicitly restarted Arnoldi method for solving large eigenproblems, SIAM J. Sci. Comput. SJSC 27(1) (2005) 253-277]. MERAM allows one to update the restarting vector of an ERAM by taking into account the interesting eigen-information obtained by its other ERAM processes. This method is particularly well suited to the GRID-type environments. We present an adaptation of the asynchronous version of MERAM for the NetSolve global computing system. We point out some advantages and limitations of this kind of system to implement the asynchronous hybrid algorithms. We give some results of our experiments and show that we can obtain a good acceleration of the convergence compared to ERAM. These results also show the potential of the MERAM-like hybrid methods for the GRID computing environments.
机译:显式重启的Arnoldi方法(ERAM)允许人们找到大型稀疏矩阵的几个本征对。多重显式重新启动的Arnoldi方法(MERAM)是一种基于ERAM多重投影的技术,可加快其收敛速度[N. Emamad,S. Petiton,G. Edjlali,多重显式重新启动Arnoldi方法以解决大特征问题,SIAM J. Sci。计算SJSC 27(1)(2005)253-277]。 MERAM允许人们通过考虑其他ERAM过程获得的有趣的本征信息来更新ERAM的重启向量。此方法特别适合GRID类型的环境。我们提出了针对NetSolve全局计算系统的MERAM异步版本的改编。我们指出了实现异步混合算法的这种系统的一些优点和局限性。我们给出了一些实验结果,并表明与ERAM相比,我们可以获得更快的收敛速度。这些结果还显示了类似MERAM的混合方法在GRID计算环境中的潜力。

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