A GPU-accelerated toolbox for the solutions of systems of linear equations

John R. Humphrey Jr.; Aaron L. Paolini; Daniel K. Price; Eric J. Kelmelis

doi:10.1117/12.818598

30 April 2009 A GPU-accelerated toolbox for the solutions of systems of linear equations

John R. Humphrey Jr., Aaron L. Paolini, Daniel K. Price, Eric J. Kelmelis

Proceedings Volume 7348, Modeling and Simulation for Military Operations IV; 73480Q (2009) https://doi.org/10.1117/12.818598
Event: SPIE Defense, Security, and Sensing, 2009, Orlando, Florida, United States

Abstract

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.

Citation Download Citation

John R. Humphrey Jr., Aaron L. Paolini, Daniel K. Price, and Eric J. Kelmelis "A GPU-accelerated toolbox for the solutions of systems of linear equations", Proc. SPIE 7348, Modeling and Simulation for Military Operations IV, 73480Q (30 April 2009); https://doi.org/10.1117/12.818598

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KEYWORDS

Computing systems

Chemical elements

Graphics processing units

Computer programming

Field programmable gate arrays

Matrices

Photonics

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