Lapack 3.1 xHSEQR: Tuning and Implementation Notes on the Small Bulge Multi-shift QR Algorithm with Aggressive Early Deflation
نویسنده
چکیده
This note documents implementation details of the small bulge, multi-shift QR algorithm with aggressive early deflation that appears as Lapack version 3.1 programs CHSEQR, DHSEQR, SHSEQR and ZHSEQR and the subroutines they call. These codes calculate eigenvalues and optionally a Schur factorization of a Hessenberg matrix. They do the bulk of the work required to calculate eigenvalues and optionally eigenvectors of a general non-symmetric matrix. This report is intended to provide some guidance for setting the machine dependent tuning parameters, to help maintainers to identify and correct problems, and to help developers improve upon this implementation. ∗Portions of this work were accomplished while this author was on sabbatical leave at and partially supported by the Lawrence Berkeley National Laboratory. This work was also partially supported by by the National Science Foundation under awards 0098150 and 0112375.
منابع مشابه
LAPACK Working Note # 216 : A novel parallel QR algorithm for hybrid distributed memory HPC systems ∗
A novel variant of the parallel QR algorithm for solving dense nonsymmetric eigenvalue problems on hybrid distributed high performance computing (HPC) systems is presented. For this purpose, we introduce the concept of multi-window bulge chain chasing and parallelize aggressive early deflation. The multi-window approach ensures that most computations when chasing chains of bulges are performed ...
متن کاملThe Multishift QR Algorithm. Part II: Aggressive Early Deflation
Aggressive early deflation is a QR algorithm deflation strategy that takes advantage of matrix perturbations outside of the subdiagonal entries of the Hessenberg QR iterate. It identifies and deflates converged eigenvalues long before the classic small-subdiagonal strategy would. The new deflation strategy enhances the performance of conventional large-bulge multishift QR algorithms, but it is ...
متن کاملA Complex Mix-Shifted Parallel QR Algorithm for the C-Method
The C-method is an exact method for analyzing gratings and rough surfaces. This method leads to large-size dense complex non-Hermitian eigenvalue. In this paper, we introduce a parallel QR algorithm that is specifically designed for the C-method. We define the “early shift” for the matrix according to the observed properties. We propose a combination of the “early shift”, Wilkinson’s shift and ...
متن کاملA novel parallel QR algorithm for hybrid distributed memory HPC systems
A novel variant of the parallel QR algorithm for solving dense nonsymmetric eigenvalue problems on hybrid distributed high performance computing (HPC) systems is presented. For this purpose, we introduce the concept of multi-window bulge chain chasing and parallelize aggressive early deflation. The multi-window approach ensures that most computations when chasing chains of bulges are performed ...
متن کاملParallel library software for the multishift QR algorithm with aggressive early deflation
Library software implementing a parallel small-bulge multishift QR algorithm with aggressive early deflation (AED) targeting distributed memory high-performance computing systems is presented. Starting from recent developments of the parallel multishift QR algorithm [Granat et al., SIAM J. Sci. Comput. 32(4), 2010], we describe a number of algorithmic and implementation improvements. These incl...
متن کامل