Automatic IR-Informed Timing and Timing-Aware IR Optimization
Journal
Proceedings - 2025 IEEE International Test Conference in Asia, ITC-Asia 2025
Start Page
37
End Page
42
ISBN
[9798331571931]
Date Issued
2025-12-16
Author(s)
Yen, Po-Chieh
Wang, Wei-Shen
Wu, Shao-Yu
Li, Bing-Chen
Chang, Norman
Li, Ying-Shiun
Lin, Lang
Kumar, Akhilesh
Abstract
This paper presents an integrated IR-Informed Timing and Timing-Aware IR Optimization flow with an IR-drop predictor. The proposed flow couples an IR-Informed Timing Optimizer with a Timing-Aware IR Optimizer to consider the mutual impact between IR-drop and timing during optimization. Then, we leverage a fast ML-based IR-drop predictor to quickly estimate the IR-drop after each iteration of optimization, which enables fast switching between the IR optimizer and timing optimizer. We further propose Feature Approximation to speed up the inference time of the IR-drop predictor. On two 7nm designs, the proposed flow closes timing and eliminates at least 90.6% of IR-drop violations. The Feature Approximation achieves 67% speed up in the runtime of the overall flow. Our optimization flow can be applied to a 945k-cell design with 7,578 IR-drop violations within 3 hours, demonstrating its practicality.
Event(s)
9th IEEE International Test Conference in Asia, ITC-Asia 2025
Subjects
Dynamic IR-drop
Feature Approximation
IR Optimization
Machine Learning
Timing Optimization
Publisher
IEEE
Type
conference paper