Processor power forecasting through model sample analysis and clustering-Reference-Cited by-同舟云学术

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Processor power forecasting through model sample analysis and clustering

Published:2023-06-12 Issue:3 Volume:5 Page:258-276
ISSN:2524-4922
Container-title:CCF Transactions on High Performance Computing
language:en
Short-container-title:CCF Trans. HPC

Author:

Zhou Kexing,Dong Yong,Chen Juan,Cao Yuhan,Li Zekai,Deng Rongyu,Guo Yifei,Ou Zhixin

Publisher

Springer Science and Business Media LLC

Subject

Information Systems,Hardware and Architecture,Computer Science Applications,Computer Science (miscellaneous)

Link

https://link.springer.com/content/pdf/10.1007/s42514-023-00152-0.pdf

Reference28 articles.

1. Ang, J.A., Barrett, B.W., Wheeler, K.B., et al.: Introducing the graph 500. Cray Users Group (2010). https://doi.org/10.1016/B0-08-043076-7/04384-9

2. Bailey, D.H., Barszcz, E., Barton, J.T., et al.: The nas parallel benchmarks summary and preliminary results. In: Proceedings of the 1991 ACM/IEEE Conference on Supercomputing, pp 158–165, https://doi.org/10.1145/125826.125925(1991)

3. Bertran, R., Gonzalez, M., Martorell, X., et al.: Decomposable and responsive power models for multicore processors using performance counters. In: Proceedings of the 24th ACM International Conference on Supercomputing, pp 147–158, https://doi.org/10.1145/1810085.1810108(2010)

4. Bienia, C., Kumar, S., Singh, J.P., et al: The parsec benchmark suite: Characterization and architectural implications. Princeton University pp 72–81. https://doi.org/10.1145/1454115.1454128(2008)

5. Chen, C., Luo, J., Parker, K.: Image segmentation via adaptive k-mean clustering and knowledge-based morphological operations with biomedical applications. IEEE Trans. Image Process. 7(12), 1673–1683 (1998). https://doi.org/10.1109/83.730379

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1. SI on parallel system and algorithm optimization;CCF Transactions on High Performance Computing;2023-08-16

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