A Performance Study of General Purpose Applications on Graphics Processors

Graphic Processors Unit (GPUs), with many light-weight data-parallel cores, can provide substantial parallel computational power to accelerate general purpose applications. To best utilize the GPU's parallel computing resources, it is crucial to understand how GPU architectures and programming models can be applied to different categories of traditionally CPU applications. In this paper the authors examine several common, computationally demanding applications - Traffic Simulation, Thermal Simulation, and K-Means - whose performance may benefit from graphics hardware's parallel computing capabilities.