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Adjustable GPU Acceleration for Hermitian Eigensystems

Garba, Michael T. , González-Vélez, Horacio and Roach, Daniel L. (2011) Adjustable GPU Acceleration for Hermitian Eigensystems. In:

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This paper explores the early 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 eispack routines with a NVIDIA Tesla C2050 GPU, potentially allowing an order of magnitude increase in the complexity or resolution of a Inelastic Neutron Scattering (INS) modelling application.

Item Type: Conference or Workshop Item (Paper)
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: 04 Mar 2014 10:28
Last Modified: 30 May 2018 13:09

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