Garba, Michael T. , González-Vélez, Horacio and Roach, Daniel L. (2013) GPU Acceleration for Hermitian Eigensystems. In: Transactions on Computational Collective Intelligence X. Lecture Notes in Computer Science (7776). Springer Berlin Heidelberg, Berlin, pp. 150-161. ISBN 9783642384967
Full text not available from this repository.Abstract
As a recurrent problem in numerical analysis and computational science, eigenvector and eigenvalue determination usually employs high-performance linear algebra libraries. This paper explores the implementation of high-performance routines for the solution of multiple large Hermitian eigenvector and eigenvalue systems on a Graphics Processing Unit (GPU). We report a performance increase of up to two orders of magnitude over the original \textscEispack routines with a NVIDIA Tesla C2050 GPU, providing an effective order of magnitude increase in unit cell size or simulated resolution for Inelastic Neutron Scattering (INS) modelling from atomistic simulations.
Item Type: | Book Section |
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Subjects: | Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science |
Divisions: | School of Computing > Staff Research and Publications |
Depositing User: | Caoimhe Ní Mhaicín |
Date Deposited: | 03 Mar 2014 16:41 |
Last Modified: | 11 Jun 2014 16:27 |
URI: | https://norma.ncirl.ie/id/eprint/981 |
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