1979

A map reduce framework for programming graphics processors

Bryan Catanzaro, Narayanan Sundaram, Kurt Keutzer
University of California, Berkeley, 545Q Cory Hall, Berkeley, California 94720
In In Workshop on Software Tools for MultiCore Systems (2008)

@conference{catanzaro2008map,

   title={A map reduce framework for programming graphics processors},

   author={Catanzaro, B. and Sundaram, N. and Keutzer, K.},

   booktitle={Workshop on Software Tools for MultiCore Systems},

   year={2008},

   organization={Citeseer}

}

Download Download (PDF)   View View   Source Source   

1506

views

Recent developments in programmable, highly parallel Graphics Processing Units (GPUs) have enabled high performance general purpose computation. We describe a framework designed for high performance GPU programming, built on Nvidia’s Compute Unified Device Architecture (CUDA) platform. The framework is built around the Map Reduce abstraction, which allows application developers to focus on their application, while enabling high performance GPU implementation. We show the utility of our framework by implementing Support Vector Machine training as well as classification, achieving speedups of up to 32x and 150x respectively over commonly used SVM software running on a CPU.
No votes yet.
Please wait...

* * *

* * *

HGPU group © 2010-2024 hgpu.org

All rights belong to the respective authors

Contact us: