Next Article in Journal
Symbolic Computation to Solving an Irrational Equation on Based Symmetric Polynomials Method
Previous Article in Journal
Computational Analysis of Air Lubrication System for Commercial Shipping and Impacts on Fuel Consumption
Article

Accurate Sampling with Noisy Forces from Approximate Computing

1
Dynamics of Condensed Matter, Department of Chemistry, Paderborn University, Warburger Str. 100, 33098 Paderborn, Germany
2
Department of Computer Science, Paderborn University, Warburger Str. 100, 33098 Paderborn, Germany
3
Paderborn Center for Parallel Computing, Paderborn University, Warburger Str. 100, 33098 Paderborn, Germany
4
Center for Sustainable Systems Design, Paderborn University, Warburger Str. 100, 33098 Paderborn, Germany
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Received: 29 February 2020 / Revised: 14 April 2020 / Accepted: 24 April 2020 / Published: 28 April 2020
(This article belongs to the Section Computational Chemistry)
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. View Full-Text
Keywords: approximate computing; CP2K; fluctuation-dissipation theorem; FPGA; i-PI; low precision arithmetic approximate computing; CP2K; fluctuation-dissipation theorem; FPGA; i-PI; low precision arithmetic
Show Figures

Figure 1

MDPI and ACS Style

Rengaraj, V.; Lass, M.; Plessl, C.; Kühne, T.D. Accurate Sampling with Noisy Forces from Approximate Computing. Computation 2020, 8, 39. https://0-doi-org.brum.beds.ac.uk/10.3390/computation8020039

AMA Style

Rengaraj V, Lass M, Plessl C, Kühne TD. Accurate Sampling with Noisy Forces from Approximate Computing. Computation. 2020; 8(2):39. https://0-doi-org.brum.beds.ac.uk/10.3390/computation8020039

Chicago/Turabian Style

Rengaraj, Varadarajan, Michael Lass, Christian Plessl, and Thomas D. Kühne 2020. "Accurate Sampling with Noisy Forces from Approximate Computing" Computation 8, no. 2: 39. https://0-doi-org.brum.beds.ac.uk/10.3390/computation8020039

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop