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. © 2010 John Wiley & Sons, Ltd.


Published in:
Concurrency Computation Practice and Experience, 23, 7, 694-707
Year:
2011
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 Record created 2011-05-05, last modified 2018-03-17

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