Job Parallelism using Graphical Processing Unit individual Multi-Processors and Highly Localised Memory
Computer Science, Massey University, North Shore 102-904, Auckland, New Zealand
CSTN Computational Science Technical Note Series, Technical Report CSTN-159, 2012
@techreport{playne2012job,
title={Job parallelism using graphical processing unit individual multiprocessors and highly localised memory},
author={Playne, D and Hawick, K},
year={2012},
institution={Tech. Rep. CSTN-159, Computer Science, Massey University}
}
Graphical Processing Units(GPUs) are usually programmed to provide data-parallel acceleration to a host processor. Modern GPUs typically have an internal multi-processor (MP) structure that can be exploited in an unusual way to offer semi-independent task parallelism providing the MPs can operate within their own localised memory and apply data-parallelism to their own problem subset. We describe a combined simulation and statistical analysis application using component labelling and benchmark it on a range of modern GPU and CPU devices with various numbers of cores. As well as demonstrating a high degree of job parallelism and throughput we find a typical GPU MP outperforms a conventional CPU core.
May 29, 2013 by hgpu