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Physical Computing: Unifying Real Number Computation to Enable Energy Efficient Computing

Electrical and Computer Engineering (ECE), Georgia Institute of Technology, Atlanta, GA 30332-250, USA
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Academic Editor: Andrea Acquaviva
J. Low Power Electron. Appl. 2021, 11(2), 14; https://doi.org/10.3390/jlpea11020014
Received: 18 February 2021 / Revised: 22 March 2021 / Accepted: 22 March 2021 / Published: 26 March 2021
Physical computing unifies real value computing including analog, neuromorphic, optical, and quantum computing. Many real-valued techniques show improvements in energy efficiency, enable smaller area per computation, and potentially improve algorithm scaling. These physical computing techniques suffer from not having a strong computational theory to guide application development in contrast to digital computation’s deep theoretical grounding in application development. We consider the possibility of a real-valued Turing machine model, the potential computational and algorithmic opportunities of these techniques, the implications for implementation applications, and the computational complexity space arising from this model. These techniques have shown promise in increasing energy efficiency, enabling smaller area per computation, and potentially improving algorithm scaling. View Full-Text
Keywords: physical computing; analog computing; complexity theory physical computing; analog computing; complexity theory
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MDPI and ACS Style

Hasler, J.; Black, E. Physical Computing: Unifying Real Number Computation to Enable Energy Efficient Computing. J. Low Power Electron. Appl. 2021, 11, 14. https://doi.org/10.3390/jlpea11020014

AMA Style

Hasler J, Black E. Physical Computing: Unifying Real Number Computation to Enable Energy Efficient Computing. Journal of Low Power Electronics and Applications. 2021; 11(2):14. https://doi.org/10.3390/jlpea11020014

Chicago/Turabian Style

Hasler, Jennifer, and Eric Black. 2021. "Physical Computing: Unifying Real Number Computation to Enable Energy Efficient Computing" Journal of Low Power Electronics and Applications 11, no. 2: 14. https://doi.org/10.3390/jlpea11020014

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