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 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. © 2013 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Garba, M. T., González-Vélez, H., & Roach, D. L. (2013). GPU acceleration for hermitian eigensystems. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7776 LNCS, 150–161. https://doi.org/10.1007/978-3-642-38496-7_10
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