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Accelerating the Reorthogonalization of Singular Vectors with a Multi-core Processor

机译:加速多核处理器的奇异载体的谱交流

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摘要

The dLV twisted factorization is an algorithm to compute singular vectors for given singular values fast and in parallel. However the orthogonality of the computed singular vectors may be worse if a matrix has clustered singular values. In order to improve the orthogonality, reorthogonalization by, for example, the modified Gram-Schmidt algorithm should be done. The problem is that this process takes a longer time. In this paper an algorithm to accelerate the reorthogonalization of singular vectors with a multi-core processor is devised.
机译:DLV扭曲分解是一种算法,用于快速和平行计算给定奇异值的奇异矢量。然而,如果矩阵具有聚类奇异值,则计算的奇异矢量的正交性可能更差。为了改善正交性,通过例如改进的Gram-Schmidt算法应该进行reorthOnalization。问题是这个过程需要更长的时间。在本文中,设计了一种加速多核处理器的奇异向量的互转化的算法。

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