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Hardware Acceleration for GCNs via Bidirectional Fusion., , , , , , , and . IEEE Comput. Archit. Lett., 20 (1): 66-69 (2021)Rethinking Efficiency and Redundancy in Training Large-scale Graphs., , , , , , and . CoRR, (2022)A Transfer Learning Framework for High-Accurate Cross-Workload Design Space Exploration of CPU., , , , , , and . ICCAD, page 1-9. IEEE, (2023)Cyber-Physical Interdependent Restoration Scheduling for Active Distribution Network via Ad Hoc Wireless Communication., , , , and . IEEE Trans. Smart Grid, 14 (5): 3413-3426 (September 2023)GDR-HGNN: A Heterogeneous Graph Neural Networks Accelerator Frontend with Graph Decoupling and Recoupling., , , , , , and . CoRR, (2024)Accelerating Mini-batch HGNN Training by Reducing CUDA Kernels., , , , , , , and . CoRR, (2024)fuseGNN: Accelerating Graph Convolutional Neural Network Training on GPGPU., , , , , , and . ICCAD, page 60:1-60:9. IEEE, (2020)Simple and Efficient Heterogeneous Graph Neural Network., , , , and . AAAI, page 10816-10824. AAAI Press, (2023)A High-accurate Multi-objective Exploration Framework for Design Space of CPU., , , , , , , and . DAC, page 1-6. IEEE, (2023)HiHGNN: Accelerating HGNNs Through Parallelism and Data Reusability Exploitation., , , , , , , , , and 1 other author(s). IEEE Trans. Parallel Distributed Syst., 35 (7): 1122-1138 (July 2024)