In: 11th IEEE International Conference on Computational Science and Engineering
Abstract: The increase of computational power of programmable GPU (Graphics Processing Unit) brings new concepts for using these devices for generic processing. Hence, with the use of the CPU and the GPU for data processing come new ideas that deals with distribution of tasks among CPU and GPU, such as automatic distribution. The importance of the automatic distribution of tasks between CPU and GPU lies in three facts. First, automatic task distribution enables the applications to use the best of both processors. Second, the developer does not have to decide which processor will do the work, allowing the automatic task distribution system to choose the best option for the moment. And third, sometimes, the application can be slowed down by other processes if the CPU or GPU is already overloaded. Based on these facts, this paper presents new schemes for efficient automatic task distribution between CPU and GPU. This paper also includes tests and results of implementing those schemes with a test case and with a real-time system.
Link: http://dl.acm.org/citation.cfm?id=1381168
Bibitex:
@inproceedings{JoselliCSE2008,
author = {Joselli, Mark and Zamith, Marcelo
and Clua, Esteban and Montenegro, Anselmo
and Conci, Aura and Leal-Toledo, Regina
and Valente, Luis and Feij\'{o}, Bruno
and Ornellas, Marcos d' and Pozzer, Cesar},
title = {Automatic Dynamic Task Distribution between CPU and GPU for Real-Time Systems},
booktitle = {Proceedings of the 2008 11th IEEE International Conference on Computational Science and Engineering},
series = {CSE '08},
year = {2008},
isbn = {978-0-7695-3193-9},
pages = {48--55},
numpages = {8},
url = {http://dx.doi.org/10.1109/CSE.2008.38},
doi = {10.1109/CSE.2008.38},
acmid = {1381168},
publisher = {IEEE Computer Society},
address = {Washington, DC, USA},
keywords = {Parallel computing, task distribution, GPGPU, real-time loop models, real-time systems},
}
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