Author
Hess, Andrew Michael
Other Contributors
Sotoudeh, Zahra; Maniatty, Antoinette M.; Oberai, Assad;
Date Issued
2014-08
Subject
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.;
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.; Detailed plans for future work with regard to integration into the modeling package and optimization are also discussed.; The primary motivation for this work was the acceleration of a here unnamed nonlinear modeling package whose current computational performance is limited by it's current MATLAB based platform. As a rst step toward an independent implementation it was decided to develop in-house GPU accelerated numerical solvers using the NVIDIA CUDA platform.;
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
Restricted to current Rensselaer faculty, staff and students. Access inquiries may be directed to the Rensselaer Libraries.;