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An accurate parallel block Gram-Schmidt algorithm without reorthogonalization

机译:无需重新正交化的精确并行块Gram-Schmidt算法

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摘要

The modified Gram-Schmidt (MGS) orthogonalization process-used for example in the Arnoldi algorithm-often constitutes the bottleneck that Limits parallel efficiencies. Indeed, a number of communications, proportional to the square of the problem size, are required to compute the dot-products. A block formulation is attractive but it suffers from potential numerical instability. In this paper, we address this issue and propose a simple procedure that allows the use of a block Gram-Schmidt algorithm while guaranteeing a numerical accuracy close to that of MGS. The main idea is to determine the size of the blocks dynamically. The main advantages of this dynamic procedure are two-fold: first, high performance matrix-vector multiplications can be used to decrease the execution time. Next, in a parallel environment, the number of communications is reduced. Performance comparisons with the alternative Iterated CGS also show an improvement for a moderate number of processors. Copyright (C) 2000 John Wiley & Sons, Ltd. [References: 17]
机译:例如,在Arnoldi算法中使用的改进的Gram-Schmidt(MGS)正交化过程通常构成限制并行效率的瓶颈。实际上,计算点积需要大量与问题大小的平方成正比的通信。嵌段配方是有吸引力的,但是它具有潜在的数值不稳定性。在本文中,我们解决了这个问题,并提出了一个简单的过程,该过程允许使用块Gram-Schmidt算法,同时保证数值精度接近MGS。主要思想是动态确定块的大小。该动态过程的主要优点有两个:首先,可以使用高性能矩阵矢量乘法来减少执行时间。接下来,在并行环境中,减少了通信数量。与替代的迭代CGS的性能比较也显示了对中等数量处理器的改进。版权所有(C)2000 John Wiley&Sons,Ltd. [引用:17]

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