Flexible LU linear solver using low-level CUDA algorithms

Authors
Hess, Andrew Michael
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Other Contributors
Sotoudeh, Zahra
Maniatty, Antoinette M.
Oberai, Assad
Issue Date
2014-08
Keywords
Mechanical engineering
Degree
MS
Terms of Use
This electronic version is a licensed copy owned by Rensselaer Polytechnic Institute, Troy, NY. Copyright of original work retained by author.
Full Citation
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
Department
Dept. of Mechanical, Aerospace, and Nuclear Engineering
Publisher
Rensselaer Polytechnic Institute, Troy, NY
Relationships
Rensselaer Theses and Dissertations Online Collection
Access
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