Reduction to condensed forms for symmetric eigenvalue problems on multi-core architectures

Authors:
Paolo Bientinesi;Francisco D. Igual;Daniel Kressner;Enrique S. Quintana-Ortí
Affiliations:
AICES, RWTH Aachen University, Aachen, Germany;Depto. de Ingeniería y Ciencia de Computadores, Universidad Jaume I, Castellón, Spain;Seminar für angewandte Mathematik, ETH Zürich, Switzerland;Depto. de Ingeniería y Ciencia de Computadores, Universidad Jaume I, Castellón, Spain
Venue:
PPAM'09 Proceedings of the 8th international conference on Parallel processing and applied mathematics: Part I
Year:
2009

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Abstract

We investigate the performance of the routines in LAPACK and the Successive Band Reduction (SBR) toolbox for the reduction of a dense matrix to tridiagonal form, a crucial preprocessing stage in the solution of the symmetric eigenvalue problem, on general-purpose multicore processors. In response to the advances of hardware accelerators, we also modify the code in SBR to accelerate the computation by offloading a significant part of the operations to a graphics processor (GPU). Performance results illustrate the parallelism and scalability of these algorithms on current high-performance multi-core architectures.