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AMA: asynchronous management of accelerators for task-based programming models

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10.1016/j.procs.2015.05.212
 
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Planas, Judit
Badia Sala, Rosa MariaMés informacióMés informacióMés informació
Ayguadé Parra, EduardMés informacióMés informacióMés informació
Labarta Mancho, Jesús JoséMés informacióMés informacióMés informació
Document typeConference report
Defense date2015
PublisherElsevier
Rights accessOpen Access
Attribution-NonCommercial-NoDerivs 3.0 Spain
Except where otherwise noted, content on this work is licensed under a Creative Commons license : Attribution-NonCommercial-NoDerivs 3.0 Spain
Abstract
Computational science has benefited in the last years from emerging accelerators that increase the performance of scientific simulations, but using these devices hinders the programming task. This paper presents AMA: a set of optimization techniques to efficiently manage multi-accelerator systems. AMA maximizes the overlap of computation and communication in a blocking-free way. Then, we can use such spare time to do other work while waiting for device operations. Implemented on top of a task-based framework, the experimental evaluation of AMA on a quad-GPU node shows that we reach the performance of a hand-tuned native CUDA code, with the advantage of fully hiding the device management. In addition, we obtain up to more than 2x performance speed-up with respect to the original framework implementation.
CitationPlanas, J., Badia, R.M., Ayguadé, E., Labarta, J. AMA: asynchronous management of accelerators for task-based programming models. A: International Conference on Computational Science. "Procedia Computer Science (Vol. 51, 2015)". Reykjavík: Elsevier, 2015, p. 130-139. 
URIhttp://hdl.handle.net/2117/104266
DOI10.1016/j.procs.2015.05.212
ISBN1877-0509
Publisher versionhttp://www.sciencedirect.com/science/article/pii/S1877050915010200
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