Effects of round-to-nearest and stochastic rounding in the numerical solution of the heat equation in low precision
Motivated by the advent of machine learning, the last few years have seen the return of hardware-supported low-precision computing. Computations with fewer digits are faster and more memory and energy efficient but can be extremely susceptible to rounding errors. As shown by recent studies into redu...
主要な著者: | Croci, M, Giles, MB |
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フォーマット: | Journal article |
言語: | English |
出版事項: |
Oxford University Press
2022
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