Dissertation
GPU Accelerated Polynomial Spectral Transformation Methods
Doctor of Philosophy (PhD), Washington State University
01/2014
Handle:
https://hdl.handle.net/2376/5177
Abstract
A new class of methods for accelerating linear system solving and eigenvalue computations for positive definite matrices using GPUs is presented. This method makes use of techniques from polynomial approximation theory to construct new types of polynomial spectral transformations that are easy to parallelize and when combined with GPUs can give a factor of 100 reduction in run times for certain matrices. These methods also require significantly less memory than traditional methods, making it possible to solve large problems on an average workstation.
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Details
- Title
- GPU Accelerated Polynomial Spectral Transformation Methods
- Creators
- Jared Lee Aurentz
- Contributors
- David S Watkins (Advisor)Kevin Cooper (Committee Member)Sandra Cooper (Committee Member)
- Awarding Institution
- Washington State University
- Academic Unit
- Mathematics and Statistics, Department of
- Theses and Dissertations
- Doctor of Philosophy (PhD), Washington State University
- Number of pages
- 73
- Identifiers
- 99900581644001842
- Language
- English
- Resource Type
- Dissertation