GPU power prediction via ensemble machine learning for DVFS space exploration-Reference-Cited by-同舟云学术

GPU power prediction via ensemble machine learning for DVFS space exploration

Published:2018-05-08 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 15th ACM International Conference on Computing Frontiers
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Author:

Dutta Bishwajit¹,Adhinarayanan Vignesh¹,Feng Wu-chun¹

Affiliation:

1. Virginia Tech

Funder

U.S. Department of Energy (DOE) Office of Advanced Scientific Computing Research (ASCR)

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3203217.3203273

Reference19 articles.

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2. Abe Y. Sasaki H. Kato S. Inoue K. Edahiro M. and Peres M. Power and Performance Characterization and Modeling of GPU-Accelerated Systems. In IEEE Int'l Parallel and Distributed Processing Symposium (IPDPS) (May 2014). 10.1109/IPDPS.2014.23 Abe Y. Sasaki H. Kato S. Inoue K. Edahiro M. and Peres M. Power and Performance Characterization and Modeling of GPU-Accelerated Systems. In IEEE Int'l Parallel and Distributed Processing Symposium (IPDPS) (May 2014). 10.1109/IPDPS.2014.23

3. Adhinarayanan V. Subramaniam B. and Feng W. Online Power Estimation of Graphics Processing Units. In IEEE/ACM Int'l Symposium on Cluster Cloud and Grid Computing (CCGrid) (May 2016). Adhinarayanan V. Subramaniam B. and Feng W. Online Power Estimation of Graphics Processing Units. In IEEE/ACM Int'l Symposium on Cluster Cloud and Grid Computing (CCGrid) (May 2016).

4. Ahern S. etal Scientific Discovery at the Exascale: Report from the DOE ASCR Workshop on Exascale Data Management Analysis and visualization. DOE Office of Advanced Scientific Computing Research (2011). Ahern S. et al. Scientific Discovery at the Exascale: Report from the DOE ASCR Workshop on Exascale Data Management Analysis and visualization. DOE Office of Advanced Scientific Computing Research (2011).

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