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Deep Neural Networks to Correct Sub-Precision Errors in CFD. (arXiv:2202.04233v1 [physics.flu-dyn])
Feb. 10, 2022, 2:11 a.m. | Akash Haridas, Nagabhushana Rao Vadlamani, Yuki Minamoto
cs.LG updates on arXiv.org arxiv.org
Loss of information in numerical simulations can arise from various sources
while solving discretized partial differential equations. In particular,
precision-related errors can accumulate in the quantities of interest when the
simulations are performed using low-precision 16-bit floating-point arithmetic
compared to an equivalent 64-bit simulation. Here, low-precision computation
requires much lower resources than high-precision computation. Several machine
learning (ML) techniques proposed recently have been successful in correcting
the errors arising from spatial discretization. In this work, we extend these
techniques to …
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