Abstract
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.
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Toyokawa, H., Ishigami, H., Kimura, K., Takata, M., Nakamura, Y. (2013). Accelerating the Reorthogonalization of Singular Vectors with a Multi-core Processor. In: Daydé, M., Marques, O., Nakajima, K. (eds) High Performance Computing for Computational Science - VECPAR 2012. VECPAR 2012. Lecture Notes in Computer Science, vol 7851. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38718-0_35
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DOI: https://doi.org/10.1007/978-3-642-38718-0_35
Publisher Name: Springer, Berlin, Heidelberg
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