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Yage Zhao

dblp:362/3504 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2023
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Integrated circuit design · 100%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Integrated circuit design › semiconductor device modeling
compact modeling
0.712023
A Combined N/PFET CFET-Based Design and Logic Technology Framework for CMOS Applications · IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 2023
Integrated circuit design › memory circuit design
SRAM design
0.212023
A Combined N/PFET CFET-Based Design and Logic Technology Framework for CMOS Applications · IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 2023
Integrated circuit design › VLSI design
standard cell library
0.212023
A Combined N/PFET CFET-Based Design and Logic Technology Framework for CMOS Applications · IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 2023

Methods — techniques the papers use, named apart from their topics

multigradient neural network · 0.7TCAD · 0.7
YearPublicationVenuePosition
2023 A Combined N/PFET CFET-Based Design and Logic Technology Framework for CMOS Applications
abstract
We propose a new technology and design platform using combined common gate (CG) N/PFET complementary field-effect transistor (CFET) as basic element for CMOS circuit applications. Two CFET unit structures, namely, CG and N-gate (NG), are identified to form base design elements. Through the two units, all circuit logic functions in standard cell library and SRAM can be realized without significant process complication. A multigradient neural network (MNN)-based SPICE compact modeling methodology is developed for these CFET units. As an example, MNN model generation is illustrated for CG with the output matching well with the TCAD data within and beyond the range of model extraction. Circuit simulations are exercised using the MNN models and demonstrated successfully the expected circuit functionalities. As the CFET technology be adopted as mainstream in future, this novel design framework proposed would enable efficient logic design.
Xiaona Zhu, Rongzheng Ding, Ouwen Tao, Yage Zhao, Peishun Tang, David Wei Zhang, Ye Lu 0005, Shaofeng Yu
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst.4