Presentation
A Crosstalk-Aware Timing Prediction Method in Routing
DescriptionWith interconnect spacing shrinking in advanced technology nodes, the precision of existing timing predictions worsens as crosstalk-induced delay is hard to quantify. During the routing process, the crosstalk effect is usually modeled by predicting coupling capacitance with congestion information. However, the timing estimation is overly pessimistic since the crosstalk-induced delay depends not only on the coupling capacitance but also on the signal arrival time. In this work, a crosstalk-aware timing estimation method is presented using a two-step machine learning approach. Interconnects that are physically adjacent and overlap in signal timing windows are filtered first. Secondly, crosstalk delay is predicted by integrating physical topology features and timing features without the post-routing result and the parasitic extraction flow. Experimental results demonstrate that the match rate of identified crosstalk-critical nets is over 99\% compared to a commercial tool. The delay prediction results are more accurate than other state-of-the-art methods.
Event Type
Work-in-Progress Poster
TimeWednesday, June 265:00pm - 6:00pm PDT
LocationLevel 2 Lobby
AI
Autonomous Systems
Cloud
Design
EDA
Embedded Systems
IP
Security