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A parallel QR-factorization/solver of structured rank matrices

机译:结构化秩矩阵的并行QR分解/求解器

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摘要

This manuscript focuses on the development of a parallel QR-factorization of structured rank matrices, which can then be used for solving systems of equations. First we will prove the existence of two types of Givens transformations, named rank decreasing and rank expanding Givens transformations. Combining these two types of Givens transformations leads to different patterns for annihilating the lower triangular part of structured rank matrices. How to obtain different annihilation patterns, for computing the upper triangular factor R, such as the ∨ and ∧ pattern will be investigated. Another pattern namely the X-pattern will be used for computing the QR-factorization in a parallel way. As an example of such a parallel QR-factorization, we will implement it for a quasiseparable matrix. This factorization can be run on 2 processors, with one step of intermediate communication in which one row needs to be sent from one processor to the other and back. Another example, showing how to deduce a parallel QR-factorization for a more general rank structure will also be discussed. Numerical experiments are included for demonstrating the accuracy and speed of this parallel algorithm w.r.t. the existing factorization of quasiseparable matrices. Also some numerical experiments on solving systems of equations using this approach will be given.
机译:该手稿着重于结构化秩矩阵的并行QR分解的开发,然后可将其用于求解方程组。首先,我们将证明存在两种类型的Givens变换,即秩减小和秩扩展的Givens变换。结合这两种类型的Givens转换会导致消除模式化秩矩阵的下三角部分的不同模式。将研究如何获得不同的an灭模式,以计算computing和∧模式等上三角因子R。另一个模式,即X模式,将用于并行计算QR分解。作为此类并行QR分解的示例,我们将其用于拟分矩阵。该分解可以在2个处理器上运行,其中一步是中间通信,其中一行需要从一个处理器发送到另一处理器再返回。还将讨论另一个示例,该示例显示了如何为更通用的秩结构推导并行QR分解。包括数值实验,以证明该并行算法的准确性和速度。拟可分矩阵的现有分解。还将给出一些使用这种方法求解方程组的数值实验。

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