Zobrazeno 1 - 10
of 1 120
pro vyhledávání: '"Wang, LingLi"'
We propose an open-source end-to-end logic optimization framework for large-scale boolean network with reinforcement learning.
Comment: 5 pages, 4 figures, 1 table
Comment: 5 pages, 4 figures, 1 table
Externí odkaz:
http://arxiv.org/abs/2403.17395
Approximate computing is a promising approach to reduce the power, delay, and area in hardware design for many error-resilient applications such as machine learning (ML) and digital signal processing (DSP) systems, in which multipliers usually are ke
Externí odkaz:
http://arxiv.org/abs/2310.15495
Autor:
Wang, Lingli1,2,3,4 (AUTHOR), Wan, Jiawu1,2,3,4 (AUTHOR), He, Wenna1,2,3,4 (AUTHOR), Wang, Zongmei1,2,3,4 (AUTHOR), Wu, Qiong1,2,3,4 (AUTHOR), Zhou, Ming1,2,3,4 (AUTHOR), Fu, Zhen F.1,2,3,4 (AUTHOR), Zhao, Ling1,2,3,4 (AUTHOR) zling604@outlook.com
Publikováno v:
Journal of Nanobiotechnology. 11/16/2024, Vol. 22 Issue 1, p1-19. 19p.
We present a efficient multi-view inverse rendering method for large-scale real-world indoor scenes that reconstructs global illumination and physically-reasonable SVBRDFs. Unlike previous representations, where the global illumination of large scene
Externí odkaz:
http://arxiv.org/abs/2211.10206
In this paper, two approximate 3*3 multipliers are proposed and the synthesis results of the ASAP-7nm process library justify that they can reduce the area by 31.38% and 36.17%, and the power consumption by 36.73% and 35.66% compared with the exact m
Externí odkaz:
http://arxiv.org/abs/2210.03916
Publikováno v:
In Fuzzy Sets and Systems 15 February 2025 502
Publikováno v:
Journal of Laboratory Medicine, Vol 48, Iss 1, Pp 37-43 (2024)
To evaluate the extent of agreement between two blood collection methods for electrolytes, central venous blood sampling by the push-pull technique versus venipuncture, and to mitigate errors in blood sampling by a potassium-based quality control pro
Externí odkaz:
https://doaj.org/article/81d9b221e3934237818d7a1ae3f1e44a
We propose an optimization method for the automatic design of approximate multipliers, which minimizes the average error according to the operand distributions. Our multiplier achieves up to 50.24% higher accuracy than the best reproduced approximate
Externí odkaz:
http://arxiv.org/abs/2201.08022
Publikováno v:
In Journal of Natural Pesticide Research June 2024 8
Publikováno v:
In Science of the Total Environment 1 June 2024 927