Name
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 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 © 2010 John Wiley & Sons, Ltd. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1002/cpe.1680 | Concurrency and Computation: Practice and Experience |
Keywords | DocType | Volume |
Successive Band Reduction,Condensed form,SBR toolbox,crucial preprocessing stage,symmetric eigenvalue problem,current high-performance multi-core,performance result,dense matrix,multi-threaded architecture,graphics processor,John Wiley,hardware accelerator,general-purpose multi-core processor | Journal | 23 |
Issue | ISSN | Citations |
7 | 1532-0626 | 13 |
PageRank | References | Authors |
0.69 | 7 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Paolo Bientinesi | 1 | 448 | 53.91 |
| Francisco D. Igual | 2 | 635 | 62.51 |
| Daniel Kressner | 3 | 449 | 48.01 |
| Matthias Petschow | 4 | 32 | 3.25 |
| Enrique S. Quintana-Ortí | 5 | 1317 | 150.59 |