Search Results for author: Yangjie Zhou

Found 4 papers, 0 papers with code

Accelerating Generic Graph Neural Networks via Architecture, Compiler, Partition Method Co-Design

no code implementations16 Aug 2023 Shuwen Lu, Zhihui Zhang, Cong Guo, Jingwen Leng, Yangjie Zhou, Minyi Guo

However, designing GNN accelerators faces two fundamental challenges: the high bandwidth requirement of GNN models and the diversity of GNN models.

Graph Learning graph partitioning

AdaptGear: Accelerating GNN Training via Adaptive Subgraph-Level Kernels on GPUs

no code implementations27 May 2023 Yangjie Zhou, Yaoxu Song, Jingwen Leng, Zihan Liu, Weihao Cui, Zhendong Zhang, Cong Guo, Quan Chen, Li Li, Minyi Guo

Graph neural networks (GNNs) are powerful tools for exploring and learning from graph structures and features.

Balancing Efficiency and Flexibility for DNN Acceleration via Temporal GPU-Systolic Array Integration

no code implementations18 Feb 2020 Cong Guo, Yangjie Zhou, Jingwen Leng, Yuhao Zhu, Zidong Du, Quan Chen, Chao Li, Bin Yao, Minyi Guo

We propose Simultaneous Multi-mode Architecture (SMA), a novel architecture design and execution model that offers general-purpose programmability on DNN accelerators in order to accelerate end-to-end applications.

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