FERMAT: FPGA energy reduction method by approximation theory
Author:
Publisher
Springer Science and Business Media LLC
Subject
Hardware and Architecture,Information Systems,Theoretical Computer Science,Software
Link
https://link.springer.com/content/pdf/10.1007/s11227-021-03644-4.pdf
Reference39 articles.
1. Rodríguez A, Navarro A, Asenjo R, Corbera F, Gran R, Suárez D, Nunez-Yanez J (2020) Parallel multiprocessing and scheduling on the heterogeneous Xeon+FPGA platform. J Supercomput 76:4645–4665. https://doi.org/10.1007/s11227-019-02935-1
2. Barua HB, Mondal KC (2018) Green Data Mining using Approximate Computing: An experimental analysis with Rule Mining. IEEE Int Conf Comput Power Commun Technol. https://doi.org/10.1109/GUCON.2018.8675095
3. J. Han, M. Orshansky (2013) Approximate Computing: An Emerging Paradigm for Energy-Efficient Design. In: Proc. 18th IEEE European Test Symposium (ETS). https://doi.org/10.1109/ETS.2013.6569370
4. Alaghi A, Hayes JP (2013) Survey of stochastic computing. ACM Trans Embedded Comp Syst DOI 10(1145/2465787):2465794
5. Cheemalavagu S, Korkmaz P, Palem KV, Akgul BES, Chakrapani LN (2005) A Probabilistic CMOS switch and its realization by exploiting noise. Proc IFIP-VLSI SoC. https://doi.org/10.1007/978-0-387-74909-9_7
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