3 papers
cs.AR2026
CapBench: A Multi-PDK Dataset for Machine-Learning-Based Post-Layout Capacitance Extraction
Hector R. Rodriguez, Jiechen Huang, Wenjian Yu
We present CapBench, a fully reproducible, multi-PDK dataset for capacitance extraction. The dataset is derived from open-source designs, including single-core CPUs, systems-on-chi…
cs.LG2025
DeepRWCap: Neural-Guided Random-Walk Capacitance Solver for IC Design
Hector R. Rodriguez, Jiechen Huang, Wenjian Yu
Monte Carlo random walk methods are widely used in capacitance extraction for their mesh free formulation and inherent parallelism. However, modern semiconductor technologies with…
cs.LG2025
Few-shot Learning on AMS Circuits and Its Application to Parasitic Capacitance Prediction
Shan Shen, Yibin Zhang, Hector Rodriguez Rodriguez +1
Graph representation learning is a powerful method to extract features from graph-structured data, such as analog/mixed-signal (AMS) circuits. However, training deep learning model…