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GPU Acceleration for Hermitian Eigensystems

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

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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
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

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