2 citations · 4 across the 8 of their papers we have counts for
4 papers · 1 filter
GCoDE: Efficient Device-Edge Co-Inference for GNNs via Architecture-Mapping Co-Search
Ao Zhou, Jianlei Yang, Tong Qiao +4
Graph Neural Networks (GNNs) have emerged as the state-of-the-art graph learning method. However, achieving efficient GNN inference on edge devices poses significant challenges, li…
ACE-GNN: Adaptive GNN Co-Inference with System-Aware Scheduling in Dynamic Edge Environments
Ao Zhou, Jianlei Yang, Tong Qiao +5
The device-edge co-inference paradigm effectively bridges the gap between the high resource demands of Graph Neural Networks (GNNs) and limited device resources, making it a promis…
Towards Affordable, Adaptive and Automatic GNN Training on CPU-GPU Heterogeneous Platforms
Tong Qiao, Ao Zhou, Yingjie Qi +4
Graph Neural Networks (GNNs) have been widely adopted due to their strong performance. However, GNN training often relies on expensive, high-performance computing platforms, limiti…
Finesse: An Agile Design Framework for Pairing-based Cryptography via Software/Hardware Co-Design
Tianwei Pan, Tianao Dai, Jianlei Yang +6
Pairing-based cryptography (PBC) is crucial in modern cryptographic applications. With the rapid advancement of adversarial research and the growing diversity of application requir…