Accurate Sampling with Noisy Forces from Approximate Computing

V. Rengaraj, M. Lass, C. Plessl, T. Kühne, Computation 8 (2020).

Journal Article | English
Abstract
In scientific computing, the acceleration of atomistic computer simulations by means of custom hardware is finding ever-growing application. A major limitation, however, is that the high efficiency in terms of performance and low power consumption entails the massive usage of low precision computing units. Here, based on the approximate computing paradigm, we present an algorithmic method to compensate for numerical inaccuracies due to low accuracy arithmetic operations rigorously, yet still obtaining exact expectation values using a properly modified Langevin-type equation.
Publishing Year
Journal Title
Computation
Volume
8
Issue
2
Article Number
39
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Cite this

Rengaraj V, Lass M, Plessl C, Kühne T. Accurate Sampling with Noisy Forces from Approximate Computing. Computation. 2020;8(2). doi:10.3390/computation8020039
Rengaraj, V., Lass, M., Plessl, C., & Kühne, T. (2020). Accurate Sampling with Noisy Forces from Approximate Computing. Computation, 8(2), Article 39. https://doi.org/10.3390/computation8020039
@article{Rengaraj_Lass_Plessl_Kühne_2020, title={Accurate Sampling with Noisy Forces from Approximate Computing}, volume={8}, DOI={10.3390/computation8020039}, number={239}, journal={Computation}, publisher={MDPI}, author={Rengaraj, Varadarajan and Lass, Michael and Plessl, Christian and Kühne, Thomas}, year={2020} }
Rengaraj, Varadarajan, Michael Lass, Christian Plessl, and Thomas Kühne. “Accurate Sampling with Noisy Forces from Approximate Computing.” Computation 8, no. 2 (2020). https://doi.org/10.3390/computation8020039.
V. Rengaraj, M. Lass, C. Plessl, and T. Kühne, “Accurate Sampling with Noisy Forces from Approximate Computing,” Computation, vol. 8, no. 2, Art. no. 39, 2020, doi: 10.3390/computation8020039.
Rengaraj, Varadarajan, et al. “Accurate Sampling with Noisy Forces from Approximate Computing.” Computation, vol. 8, no. 2, 39, MDPI, 2020, doi:10.3390/computation8020039.
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