Abstract
Stewart’s Krylov–Schur algorithm offers two advantages over Sorensen’s implicitly restarted Arnoldi (IRA) algorithm. The first is ease of deflation of converged Ritz vectors, the second is the avoidance of the potential forward instability of the QR algorithm. In this paper we develop a block version of the Krylov–Schur algorithm for symmetric eigenproblems. Details of this block algorithm are discussed, including how to handle rank deficient cases and how to use varying block sizes. Numerical results on the efficiency of the block Krylov–Schur method are reported.
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Work supported by US Department of Energy under contract DE-FG02-03ER25585, by NSF grants ITR-0428774 and CMMI-0727194, and by the Minnesota Supercomputing Institute.
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Zhou, Y., Saad, Y. Block Krylov–Schur method for large symmetric eigenvalue problems. Numer Algor 47, 341–359 (2008). https://doi.org/10.1007/s11075-008-9192-9
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DOI: https://doi.org/10.1007/s11075-008-9192-9