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Gpu Implementation Of A Novel Approach To Cramer’S Algorithm For Solving Large Scale Linear Systems, Rosanne Lane West
Gpu Implementation Of A Novel Approach To Cramer’S Algorithm For Solving Large Scale Linear Systems, Rosanne Lane West
Masters Theses
Scientific computing often requires solving systems of linear equations. Most software pack- ages for solving large-scale linear systems use Gaussian elimination methods such as LU- decomposition. An alternative method, recently introduced by K. Habgood and I. Arel, involves an application of Cramer’s Rule and Chio’s condensation to achieve a better per- forming system for solving linear systems on parallel computing platforms. This thesis describes an implementation of this algorithm on an nVidia graphics processor card us- ing the CUDA language. Increased performance, relative to the serial implementation, is demonstrated, paving the way for future parallel realizations of the scheme.
Performance Evaluation Of Memory And Computationally Bound Chemistry Applications On Streaming Gpgpus And Multi-Core X86 Cpus, Frederick E. Weber Iii
Performance Evaluation Of Memory And Computationally Bound Chemistry Applications On Streaming Gpgpus And Multi-Core X86 Cpus, Frederick E. Weber Iii
Masters Theses
In recent years, multi-core processors have come to dominate the field in desktop and high performance computing. Graphics processors traditionally used in CAD, video games, and other 3-d applications, have become more programmable and are now suitable for general purpose computing. This thesis explores multi-core processors and GPU performance and limitations in two computational chemistry applications: a memory bound component of ab-initio modeling and a computationally bound Monte Carlo simulation. For the applications presented in this thesis, exploiting multiple processors is done using a variety of tools and languages including OpenMP and MKL. Brook+ and the Compute Abstraction Layer streaming …