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PAPER DOI: 10.1109/IRPS48228.2024.10529386

technical paper

IRPS 2024 Main Conference

April 17, 2024

Dallas, United States

Machine Learning Unleashes Aging and Self-Heating Effects: From Transistors to Full Processor

keywords:

cell libraries

processor

aging

self-heating

machine learning

reliability

This talk focuses on aging and self-heating effects in transistors. As technology nodes shrinks, 3D structures become more confined and less reliable. We showcase how deep learning and machine learning techniques offer innovative solutions for the EDA industry. These techniques enable designers to estimate the impact of these phenomena without the need for divulging confidential models. We demonstrate the seamless integration of sign-off tools to estimate self-heating in an entire processor at the GDS level.

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