Condensed forms for the symmetric eigenvalue problem on multi threaded architectures
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 multi core processors. In response to the advances of hardware accelerators, we also modify the code in the SBR toolbox to accelerate the computation by off loading a significant part of the operations to a graphics processor (GPU) The performance results illustrate the parallelism and scalability of these algorithms on current high performance multi core and many core architectures. Copyright (c) 2010 John Wiley Sons, Ltd.
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