Ji, Z, Xue, Y, Ren, P, Ye, J, Li, Y, Wu, Y, Wang, D, Wang, S, Wu, J, Wang, Z, Wen, Y, Xia, S, Zhang, L, Zhang, J, Liu, J, Luo, J, Deng, H, Wang, R, Yang, L and Huang, R (2023) Towards Reliability- & Variability-aware Design-Technology Co-optimization in Advanced Nodes: Defect Characterization, Industry-friendly Modelling and ML-assisted Prediction. IEEE Transactions on Electron Devices, 71 (1). pp. 138-150. ISSN 0018-9383

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Abstract

Reliability- & variability-aware Design Technology co-optimization (RV-DTCO) becomes indispensable with advanced nodes. However, four key issues hinder its practical adoption: the lack of characterization technique that offer both accuracy and efficiency, the lack of defect model with long-term prediction capability, the lack of compact model compatible with most EDA platforms, and the low efficiency in circuit-level prediction to support frequent iterations during co-optimization. Demonstrating with 7nm technology, this work tackles these issues by developing an efficient characterization method for separating defects, introducing a comprehensive test-data-verified defect-centric physical-based model & an industry-friendly OMI-based compact model, and proposing a machine learning-assisted approach to accelerate circuit-level prediction. With these achievements, a RV-DTCO flow is established and demonstrated on 3nm GAA technology to bridge the material level to the circuit level. The work paves ways in boosting adoption of RV-DTCO in both circuit design & process development for ultimate nodes. Index Terms— Design Technology co-optimization (DTCO), FinFET, reliability, variability, Discharging-based multi-pulse technique (DMP), OMI, ST-GNN

Item Type:	Article
Additional Information:	© 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Uncontrolled Keywords:	0906 Electrical and Electronic Engineering; Applied Physics
Subjects:	T Technology > TA Engineering (General). Civil engineering (General)
Divisions:	Engineering
Publisher:	Institute of Electrical and Electronics Engineers
SWORD Depositor:	A Symplectic
Date Deposited:	06 Nov 2023 12:00
Last Modified:	11 Jan 2024 16:45
DOI or ID number:	10.1109/TED.2023.3330834
URI:	https://researchonline.ljmu.ac.uk/id/eprint/21795

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