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

by P. Bientinesi and F. D. Igual and D. Kressner and E. S. Quintana-Orti

(Report number 2009-13)

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. The target architecture is a current general purpose multi-core processor, where parallelism is extracted using a tuned multi-threaded implementation of BLAS. Also, in response to the advances of hardware accelerators, we modify the code in SBR to accelerate the computation by off-loading a significant part of the operations to a graphics processor (GPU). Our results on a system with two Intel QuadCore processors and a Tesla C1060 GPU illustrate the performance and scalability delivered by these architectures.

Keywords:

@Techreport{BIKQ09_400,
  author = {P. Bientinesi and F. D. Igual and D. Kressner and E. S. Quintana-Orti},
  title = {Reduction to condensed forms for aymmetric eigenvalue problems on multi-core architectures},
  institution = {Seminar for Applied Mathematics, ETH Z{\"u}rich},
  number = {2009-13},
  address = {Switzerland},
  url = {https://www.sam.math.ethz.ch/sam_reports/reports_final/reports2009/2009-13.pdf },
  year = {2009}
}

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