https://doi.org/10.1051/epjconf/201817509011
A staggered eigensolver based on sparse matrix bidiagonalization
Leadership Computing Facility, Argonne National Laboratory, 9700 S. Cass Ave., Argonne, IL 60439, USA
* Speaker, e-mail: osborn@alcf.anl.gov Acknowledgments: This research used resources of the Argonne Leadership Computing Facility (ALCF), which is a U.S. Department of Energy Offce of Science User Facility operated under Contract DEAC02-06CH11357. JCO was supported by the ALCF. XYJ was supported by the U.S. Department of Energy Offce of Science under the ECP and SciDAC programs.
Published online: 26 March 2018
We present a method for calculating eigenvectors of the staggered Dirac operator based on the Golub-Kahan-Lanczos bidiagonalization algorithm. Instead of using orthogonalization during the bidiagonalization procedure to increase stability, we choose to stabilize the method by combining it with an outer iteration that refines the approximate eigenvectors obtained from the inner bidiagonalization procedure. We discuss the performance of the current implementation using QEX and compare with other methods.
© The Authors, published by EDP Sciences, 2018
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