Flexible LU linear solver using low-level CUDA algorithms
Authors
Hess, Andrew Michael
Issue Date
2014-08
Type
Electronic thesis
Thesis
Thesis
Language
ENG
Keywords
Mechanical engineering
Alternative Title
Abstract
This specic research involved the initial analysis, design, and coding of a CUDA based LU decomposition linear solver with partial pivoting with the intention of being compact and flexible. A block based approach to decomposition and substitution was derived and applied to produce desirable GPU based algorithms. The result was a properly working linear solver with reasonable but less than desired performance due to lack of optimization. Developing CUDA based programs at the kernel (lowest) level is an extensive process with complex optimization requirements and thus, as a foundation, this work maintained the basic goal of producing a functional but not necessarily refined solver. This goal was achieved and the resulting code is thoroughly described and documented in the body of the article.
Description
August 2014
School of Engineering
School of Engineering
Full Citation
Publisher
Rensselaer Polytechnic Institute, Troy, NY