7281

Performance Analysis of a Novel GPU Computation-to-core Mapping Scheme for Robust Facet Image Modeling

Seung In Park, Yong Cao, Layne T. Watson, Francis Quek
Department of Computer Science, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, USA
Virginia Tech., Computer Science, Technical Report TR-12-05, 2012

@article{park2012performance,

   title={Performance Analysis of a Novel GPU Computation-to-core Mapping Scheme for Robust Facet Image Modeling},

   author={Park, S.I. and Cao, Y. and Watson, L.T. and Quek, F.},

   year={2012}

}

Download Download (PDF)   View View   Source Source   

577

views

Though the GPGPU concept is well-known in image processing, much more work remains to be done to fully exploit GPUs as an alternative computation engine. This paper investigates the computation-to-core mapping strategies to probe the efficiency and scalability of the robust facet image modeling algorithm on GPUs. Our fine-grained computation-to-core mapping scheme shows a significant performance gain over the standard pixel-wise mapping scheme. With in-depth performance comparisons across the two different mapping schemes, we analyze the impact of the level of parallelism on the GPU computation and suggest two principles for optimizing future image processing applications on the GPU platform.
No votes yet.
Please wait...

* * *

* * *

HGPU group © 2010-2017 hgpu.org

All rights belong to the respective authors

Contact us: