Worst-case Power Integrity Prediction Using Convolutional Neural Network | Zendy

Xiao Dong | Zendy; Yufei Chen | Zendy; Jun Chen | Zendy; Yu-Cheng Wang | Zendy; Ji Li | Zendy; Tianming Ni | Zendy; Zhiguo Shi | Zendy; Xunzhao Yin | Zendy; Cheng Zhuo | Zendy

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Worst-case Power Integrity Prediction Using Convolutional Neural Network

Author(s) -

Xiao Dong,

Yufei Chen,

Jun Chen,

Yu-Cheng Wang,

Ji Li,

Tianming Ni,

Zhiguo Shi,

Xunzhao Yin,

Cheng Zhuo

Publication year - 2022

Publication title -

acm transactions on design automation of electronic systems

Language(s) - Uncategorized

Resource type - Journals

SCImago Journal Rank - 0.266

H-Index - 51

eISSN - 1557-7309

pISSN - 1084-4309

DOI - 10.1145/3564932

Subject(s) - computer science , speedup , power integrity , convolutional neural network , scalability , signal integrity , redundancy (engineering) , reliability (semiconductor) , artificial neural network , overhead (engineering) , noise (video) , power (physics) , robustness (evolution) , artificial intelligence , parallel computing , computer network , biochemistry , physics , chemistry , quantum mechanics , database , interconnection , image (mathematics) , gene , operating system

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