Publication Date
1-28-2015
Abstract
In this thesis we present the first, to our knowledge, implementation and performance analysis of Hermite methods on GPU accelerated systems. We give analytic background for Hermite methods; give implementations of the Hermite methods on traditional CPU systems as well as on GPUs; give the reader background on basic CUDA programming for GPUs; discuss performance characteristics of GPUs; we give recommended design choices for GPU implementations of Hermite methods; and present and discuss examples which illustrate the effect these design choices have on performance. Lastly, we present areas of future research that may yield increased performance for Hermite methods on GPUs.
Degree Name
Mathematics
Level of Degree
Masters
Department Name
Mathematics & Statistics
First Committee Member (Chair)
Daniel Appelö
Second Committee Member
Stephen Lau
Third Committee Member
Jens Lorenz
Project Sponsors
National Science Foundation
Language
English
Keywords
GPU, Hermite, Optimization, OpenCL, CUDA, Computational, Performance, PDE, Partial Differential Equation, Analysis, Applied Mathematics, Mathematics, Numerical, NVIDIA
Document Type
Thesis
Recommended Citation
Dye, Evan T.. "Performance Analysis and Optimization of Hermite Methods on NVIDIA GPUs Using CUDA." (2015). https://digitalrepository.unm.edu/math_etds/15
