[HTML][HTML] Deep-learning cell-delay modeling for static timing analysis

W Raslan, Y Ismail - Ain Shams Engineering Journal, 2023 - Elsevier
Delay and transition timetables plus voltage waveforms are used to characterize standard
cell delays. More accurate models explode cell library size and degrades design flow …

Logical Resolving-Based Methodology for Efficient Reliability Analysis

Z Tang, C Li, H You, X Liu, Y Wang, Y Dai, G Bai, X Lin - Micromachines, 2023 - mdpi.com
With the CMOS technology downscaling to the deep nanoscale, the aging effects of devices
degrade circuit performance and even lead to functional failure. The stress analysis is critical …

Efficient and Effective Digital Waveform Compression for Large-scale Logic Simulation of Integrated Circuit

Z Gao, Y Xie, W Yu - Proceedings of the Great Lakes Symposium on …, 2023 - dl.acm.org
Efficient and lossless digital waveform compression is essentially important for large-scale
IC design. In this paper, a compression and storage scheme with detailed-encoding is …

Deep Learning Autoencoder-based Compression for Current Source Model Waveforms

W Raslan, Y Ismail - 2021 28th IEEE International Conference …, 2021 - ieeexplore.ieee.org
Modeling complex cell behavior is critical for accurate static timing analysis. Huge waveform
data needed for current source models explodes technology file size and degrades design …

More Efficient Accuracy-Ensured Waveform Compression for Circuit Simulation Supporting Asynchronous Waveforms

L Li, W Yu, G Guo, Z Zhou - Proceedings of the Great Lakes Symposium …, 2023 - dl.acm.org
Efficient and accurate waveform compression is critical for analog circuit simulation. In this
work, we propose a waveform compression scheme which supports asynchronous …

Machine Learning Applications to Static Timing Analysis

WM Raslan - 2022 - fount.aucegypt.edu
Modeling complex cell behavior is critical for accurate static timing analysis. Effective current
source model, ECSM, and composite current source, CCS, waveform data compression …