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ORCIDShaoyi Huang
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2020 – today
- 2024
[c20]Hongwu Peng
, Xi Xie, Kaustubh Shivdikar, Md Amit Hasan, Jiahui Zhao, Shaoyi Huang, Omer Khan, David R. Kaeli, Caiwen Ding:
MaxK-GNN: Extremely Fast GPU Kernel Design for Accelerating Graph Neural Networks Training. ASPLOS (2) 2024: 683-698- [c19]Deniz Gurevin, Mohsin Shan, Shaoyi Huang, Md Amit Hasan, Caiwen Ding, Omer Khan:
PruneGNN: Algorithm-Architecture Pruning Framework for Graph Neural Network Acceleration. HPCA 2024: 108-123 - [d2]Hongwu Peng, Xi Xie, Kaustubh Shivdikar, Amit Hasan, Jiahui Zhao, Shaoyi Huang, Omer Khan, David R. Kaeli, Caiwen Ding:
ASPLOS 2024 Artifact for "MaxK-GNN: Extremely Fast GPU Kernel Design for Accelerating Graph Neural Networks Training". Version 1. Zenodo, 2024 [all versions]
- [d1]Hongwu Peng, Xi Xie, Kaustubh Shivdikar, Amit Hasan, Jiahui Zhao, Shaoyi Huang, Omer Khan, David R. Kaeli, Caiwen Ding:
ASPLOS 2024 Artifact for "MaxK-GNN: Extremely Fast GPU Kernel Design for Accelerating Graph Neural Networks Training". Version 2. Zenodo, 2024 [all versions] - [i14]Bingbing Li, Geng Yuan, Zigeng Wang, Shaoyi Huang, Hongwu Peng, Payman Behnam, Wujie Wen, Hang Liu, Caiwen Ding:
Zero-Space Cost Fault Tolerance for Transformer-based Language Models on ReRAM. CoRR abs/2401.11664 (2024) - 2023
- [c18]Shaoyi Huang, Haowen Fang, Kaleel Mahmood, Bowen Lei, Nuo Xu, Bin Lei, Yue Sun, Dongkuan Xu, Wujie Wen, Caiwen Ding:
Neurogenesis Dynamics-inspired Spiking Neural Network Training Acceleration. DAC 2023: 1-6 - [c17]Shaoyi Huang, Bowen Lei, Dongkuan Xu, Hongwu Peng, Yue Sun, Mimi Xie, Caiwen Ding:
Dynamic Sparse Training via Balancing the Exploration-Exploitation Trade-off. DAC 2023: 1-6 - [c16]Xi Xie, Hongwu Peng, Amit Hasan, Shaoyi Huang, Jiahui Zhao, Haowen Fang, Wei Zhang, Tong Geng, Omer Khan, Caiwen Ding:
Accel-GCN: High-Performance GPU Accelerator Design for Graph Convolution Networks. ICCAD 2023: 1-9 - [c15]Hongwu Peng, Shaoyi Huang, Tong Zhou, Yukui Luo, Chenghong Wang, Zigeng Wang, Jiahui Zhao, Xi Xie, Ang Li, Tony Geng, Kaleel Mahmood, Wujie Wen, Xiaolin Xu, Caiwen Ding:
AutoReP: Automatic ReLU Replacement for Fast Private Network Inference. ICCV 2023: 5155-5165 - [c14]Bingbing Li, Zigeng Wang, Shaoyi Huang, Mikhail A. Bragin, Ji Li, Caiwen Ding:
Towards Lossless Head Pruning through Automatic Peer Distillation for Language Models. IJCAI 2023: 5113-5121 - [c13]Hongwu Peng, Ran Ran, Yukui Luo, Jiahui Zhao, Shaoyi Huang, Kiran Thorat, Tong Geng, Chenghong Wang, Xiaolin Xu, Wujie Wen, Caiwen Ding:
LinGCN: Structural Linearized Graph Convolutional Network for Homomorphically Encrypted Inference. NeurIPS 2023 - [i13]Hongwu Peng, Shanglin Zhou, Yukui Luo, Nuo Xu, Shijin Duan, Ran Ran, Jiahui Zhao, Shaoyi Huang, Xi Xie, Chenghong Wang, Tong Geng, Wujie Wen, Xiaolin Xu, Caiwen Ding:
RRNet: Towards ReLU-Reduced Neural Network for Two-party Computation Based Private Inference. CoRR abs/2302.02292 (2023) - [i12]Shaoyi Huang, Haowen Fang, Kaleel Mahmood, Bowen Lei, Nuo Xu, Bin Lei, Yue Sun, Dongkuan Xu, Wujie Wen, Caiwen Ding:
Neurogenesis Dynamics-inspired Spiking Neural Network Training Acceleration. CoRR abs/2304.12214 (2023) - [i11]Hongwu Peng, Shaoyi Huang, Tong Zhou, Yukui Luo, Chenghong Wang, Zigeng Wang, Jiahui Zhao, Xi Xie, Ang Li, Tony Geng, Kaleel Mahmood, Wujie Wen, Xiaolin Xu, Caiwen Ding:
AutoReP: Automatic ReLU Replacement for Fast Private Network Inference. CoRR abs/2308.10134 (2023) - [i10]Xi Xie, Hongwu Peng, Amit Hasan, Shaoyi Huang, Jiahui Zhao, Haowen Fang, Wei Zhang, Tong Geng, Omer Khan, Caiwen Ding:
Accel-GCN: High-Performance GPU Accelerator Design for Graph Convolution Networks. CoRR abs/2308.11825 (2023) - [i9]Hongwu Peng, Ran Ran, Yukui Luo, Jiahui Zhao, Shaoyi Huang, Kiran Thorat, Tong Geng, Chenghong Wang, Xiaolin Xu, Wujie Wen, Caiwen Ding:
LinGCN: Structural Linearized Graph Convolutional Network for Homomorphically Encrypted Inference. CoRR abs/2309.14331 (2023) - [i8]Hongwu Peng, Xi Xie, Kaustubh Shivdikar, Md Amit Hasan, Jiahui Zhao, Shaoyi Huang, Omer Khan, David R. Kaeli, Caiwen Ding:
MaxK-GNN: Towards Theoretical Speed Limits for Accelerating Graph Neural Networks Training. CoRR abs/2312.08656 (2023) - 2022
- [c12]Shaoyi Huang, Dongkuan Xu, Ian En-Hsu Yen, Yijue Wang, Sung-En Chang, Bingbing Li, Shiyang Chen, Mimi Xie, Sanguthevar Rajasekaran, Hang Liu, Caiwen Ding:
Sparse Progressive Distillation: Resolving Overfitting under Pretrain-and-Finetune Paradigm. ACL (1) 2022: 190-200 - [c11]Yijue Wang, Nuo Xu, Shaoyi Huang, Kaleel Mahmood, Dan Guo, Caiwen Ding, Wujie Wen, Sanguthevar Rajasekaran:
Analyzing and Defending against Membership Inference Attacks in Natural Language Processing Classification. IEEE Big Data 2022: 5823-5832 - [c10]Hongwu Peng, Shaoyi Huang, Shiyang Chen, Bingbing Li, Tong Geng, Ang Li, Weiwen Jiang, Wujie Wen, Jinbo Bi, Hang Liu, Caiwen Ding:
A length adaptive algorithm-hardware co-design of transformer on FPGA through sparse attention and dynamic pipelining. DAC 2022: 1135-1140 - [c9]Hongwu Peng, Deniz Gurevin, Shaoyi Huang, Tong Geng, Weiwen Jiang, Omer Khan, Caiwen Ding:
Towards Sparsification of Graph Neural Networks. ICCD 2022: 272-279 - [c8]Yixuan Luo, Payman Behnam, Kiran Thorat, Zhuo Liu, Hongwu Peng, Shaoyi Huang, Shu Zhou, Omer Khan, Alexey Tumanov, Caiwen Ding, Tong Geng:
CoDG-ReRAM: An Algorithm-Hardware Co-design to Accelerate Semi-Structured GNNs on ReRAM. ICCD 2022: 280-289 - [c7]Shaoyi Huang, Ning Liu, Yueying Liang, Hongwu Peng, Hongjia Li, Dongkuan Xu, Mimi Xie, Caiwen Ding:
An Automatic and Efficient BERT Pruning for Edge AI Systems. ISQED 2022: 1-6 - [i7]Shaoyi Huang, Ning Liu, Yueying Liang, Hongwu Peng, Hongjia Li, Dongkuan Xu, Mimi Xie, Caiwen Ding:
An Automatic and Efficient BERT Pruning for Edge AI Systems. CoRR abs/2206.10461 (2022) - [i6]Hongwu Peng, Shaoyi Huang, Shiyang Chen, Bingbing Li, Tong Geng, Ang Li, Weiwen Jiang, Wujie Wen, Jinbo Bi, Hang Liu, Caiwen Ding:
A Length Adaptive Algorithm-Hardware Co-design of Transformer on FPGA Through Sparse Attention and Dynamic Pipelining. CoRR abs/2208.03646 (2022) - [i5]Hongwu Peng, Deniz Gurevin, Shaoyi Huang, Tong Geng, Weiwen Jiang, Omer Khan, Caiwen Ding:
Towards Sparsification of Graph Neural Networks. CoRR abs/2209.04766 (2022) - [i4]Bin Lei, Shaoyi Huang, Caiwen Ding, Monika Filipovska:
Efficient Traffic State Forecasting using Spatio-Temporal Network Dependencies: A Sparse Graph Neural Network Approach. CoRR abs/2211.03033 (2022) - [i3]Shaoyi Huang, Bowen Lei, Dongkuan Xu, Hongwu Peng, Yue Sun, Mimi Xie, Caiwen Ding:
Dynamic Sparse Training via Balancing the Exploration-Exploitation Trade-off. CoRR abs/2211.16667 (2022) - 2021
- [c6]Panjie Qi, Yuhong Song, Hongwu Peng, Shaoyi Huang, Qingfeng Zhuge, Edwin Hsing-Mean Sha:
Accommodating Transformer onto FPGA: Coupling the Balanced Model Compression and FPGA-Implementation Optimization. ACM Great Lakes Symposium on VLSI 2021: 163-168 - [c5]Shaoyi Huang, Shiyang Chen, Hongwu Peng, Daniel Manu, Zhenglun Kong, Geng Yuan, Lei Yang, Shusen Wang, Hang Liu, Caiwen Ding:
HMC-TRAN: A Tensor-core Inspired Hierarchical Model Compression for Transformer-based DNNs on GPU. ACM Great Lakes Symposium on VLSI 2021: 169-174 - [c4]Daniel Manu, Shaoyi Huang, Caiwen Ding, Lei Yang:
Co-Exploration of Graph Neural Network and Network-on-Chip Design Using AutoML. ACM Great Lakes Symposium on VLSI 2021: 175-180 - [c3]Panjie Qi, Edwin Hsing-Mean Sha, Qingfeng Zhuge, Hongwu Peng, Shaoyi Huang, Zhenglun Kong, Yuhong Song, Bingbing Li:
Accelerating Framework of Transformer by Hardware Design and Model Compression Co-Optimization. ICCAD 2021: 1-9 - [c2]Hongwu Peng, Shaoyi Huang, Tong Geng, Ang Li, Weiwen Jiang, Hang Liu, Shusen Wang, Caiwen Ding:
Accelerating Transformer-based Deep Learning Models on FPGAs using Column Balanced Block Pruning. ISQED 2021: 142-148 - [c1]Shiyang Chen, Shaoyi Huang, Santosh Pandey, Bingbing Li, Guang R. Gao, Long Zheng, Caiwen Ding, Hang Liu:
E.T.: re-thinking self-attention for transformer models on GPUs. SC 2021: 25 - [i2]Shaoyi Huang, Dongkuan Xu, Ian En-Hsu Yen, Sung-En Chang, Bingbing Li, Shiyang Chen, Mimi Xie, Hang Liu, Caiwen Ding:
Sparse Progressive Distillation: Resolving Overfitting under Pretrain-and-Finetune Paradigm. CoRR abs/2110.08190 (2021) - [i1]Panjie Qi, Edwin Hsing-Mean Sha, Qingfeng Zhuge, Hongwu Peng, Shaoyi Huang, Zhenglun Kong, Yuhong Song, Bingbing Li:
Accelerating Framework of Transformer by Hardware Design and Model Compression Co-Optimization. CoRR abs/2110.10030 (2021)
Coauthor Index
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