Hardware-aware GNN NAS paper is accepted by DAC 2023!

👏 Paper title: Hardware-Aware Graph Neural Network Automated Design for Edge Computing Platforms. We explore a hardware-aware GNN architecture design for edge devices, leveraging the novel idea of “predicting GNNs with GNNs” to efficiently estimate the performance of candidate architectures during the NAS process. By thoroughly analyzing the impact of device heterogeneity on GNN performance and integrating hardware awareness into the exploration, our method achieves significant improvements in both accuracy and efficiency. [related project]