A GPU-accelerated toolbox for the solutions of systems of linear equations
John R. Humphrey, Aaron L. Paolini, Daniel K. Price, Eric J. Kelmelis · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2009
The modern graphics processing unit (GPU) found in many off-the shelf personal computers is a very high performance computing engine that often goes unutilized. The tremendous computing power coupled with reasonable pricing has made the GPU a topic of interest in recent research. An application for such power would be the solution to large systems of linear equations. Two popular solution domains are direct solution, via the LU decomposition, and iterative solution, via a solver such as the Generalized Method of Residuals (GMRES). Our research focuses on the acceleration of such processes, utilizing the latest in GPU technologies. We show performance that exceeds that of a standard computer by an order of magnitude, thus significantly reducing the run time of the numerous applications that depend on the solution of a set of linear equations.