LMM-IR: Large-Scale Netlist-Aware Multimodal Framework for Static IR-Drop Prediction
Researchers have developed LMM-IR, a novel multimodal framework for predicting static IR-drop in chip design. This approach utilizes a large-scale netlist transformer to process netlist topology as 3D point cloud representations, enabling efficient handling of complex netlists. By integrating netlist and image data, the model achieves state-of-the-art performance, outperforming previous winning teams in the ICCAD 2023 contest. AI
IMPACT This framework could significantly reduce chip design time by enabling faster and more accurate IR-drop prediction.