Towards Efficient GPU Sharing on Multicore Processors
ECE Department, George Washington University
The 2nd International Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computing Systems (PMBS11), 2011
@article{wang40towards,
title={Towards Efficient GPU Sharing on Multicore Processors},
author={Wang, L. and Huang, M. and El-Ghazawi, T.},
journal={SIGMETRICS Performance Evaluation Review},
volume={40},
number={2},
year={2011}
}
Scalable systems employing a mix of GPUs with CPUs are becoming increasingly prevalent in high-performance computing (HPC). The presence of such accelerators introduces significant challenges and complexities to both language developers and end users. This paper provides a close study of efficient coordination mechanisms to handle parallel requests from multiple hosts of control to a GPU under hybrid programming. Using a set of microbenchmarks and applications on a GPU cluster, we show that thread- and process-based context hosting have different tradeoffs. Experimental results on application benchmarks suggest that both thread-based context funneling and process-based context switching natively perform similarly on the latest Fermi GPU, while manually guided context funneling is currently the best way to achieve optimal performance.
November 19, 2011 by hgpu