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2020 – today
- 2024
[c7]Fangzhou Ye
, Lingxiang Yin, Amir Ghazizadeh Ahsaei, Hao Zheng:
EGMA: Enhancing Data Reuse and Workload Balancing in Message Passing GNN Acceleration via Gram Matrix Optimization. DAC 2024: 304:1-304:6- [c6]Lingxiang Yin, Sanjay Gandham, Mingjie Lin, Hao Zheng:
SCALE: A Structure-Centric Accelerator for Message Passing Graph Neural Networks. MICRO 2024: 580-593 - 2023
- [c5]Sanjay Gandham, Lingxiang Yin, Hao Zheng, Mingjie Lin:
OCMGen: Extended Design Space Exploration with Efficient FPGA Memory Inference. FCCM 2023: 225 - [c4]Lingxiang Yin, Jun Wang, Hao Zheng:
Exploring Architecture, Dataflow, and Sparsity for GCN Accelerators: A Holistic Framework. ACM Great Lakes Symposium on VLSI 2023: 489-495 - [c3]Sanjay Gandham, Lingxiang Yin, Hao Zheng, Mingjie Lin:
SAGA: Sparsity-Agnostic Graph Convolutional Network Acceleration with Near-Optimal Workload Balance. ICCAD 2023: 1-9 - [c2]Lingxiang Yin, Amir Ghazizadeh, Ahmed Louri, Hao Zheng:
ARIES: Accelerating Distributed Training in Chiplet-Based Systems via Flexible Interconnects. ICCAD 2023: 1-9 - [c1]Lingxiang Yin, Amir Ghazizadeh, Shilin Tian, Ahmed Louri, Hao Zheng:
Polyform: A Versatile Architecture for Multi-DNN Execution via Spatial and Temporal Acceleration. ICCD 2023: 166-169
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