Parallel Algorithms for Hybrid Multi-core CPU-GPU Implementations of Component Labelling in Critical Phase Models
Computer Science, Massey University, North Shore 102-904, Auckland, New Zealand
Massey University, Computational Science Technical Note CSTN-177, 2013
@inproceedings{CSTN-177,
author={K. A. Hawick and D. P. Playne},
title={Parallel Algorithms for Hybrid Multi-core CPU-GPU Implementations of Component Labelling in Critical Phase Models},
booktitle={Proc. Int. Conf. on Parallel and Distributed Processing Techniques and Applications (PDPTA’13)},
year={2013},
number={CSTN-177},
pages={PDP3297},
address={Las Vegas, USA},
month={22-25 July},
publisher={WorldComp},
institution={Computer Science, Massey University, Auckland, New Zealand},
keywords={hybrid CPU/GPU; component labelling, phase transitions; Potts model; heterogeneous system; multi-core},
owner={kahawick},
timestamp={2013.04.22}
}
Optimising the use of all the cores of a hybrid multi-core CPU and its accelerating GPUs is becoming increasingly important as such combined systems become widely available. We show how a complex interplay of cross-calling kernels and host components can be used to support good throughput performance on hybrid simulation tasks that have inherently serial analysis calculations that must be run alongside more easily parallelisable simulation time-stepping calculations. We present results for a cluster component-labelling analysis performed during simulation of a Potts lattice simulation model. We discuss how these hybrid techniques can be more broadly applied to this class of numerical simulation experiments in computational science.
June 19, 2013 by hgpu