Shaoyi Huang

According to our database, Shaoyi Huang authored at least 27 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

ASPLOS 2024 Artifact for "MaxK-GNN: Extremely Fast GPU Kernel Design for Accelerating Graph Neural Networks Training".

Hongwu Peng, Xi Xie, Kaustubh Shivdikar, Amit Hasan, Jiahui Zhao, Shaoyi Huang, Omer Khan, David R. Kaeli, Caiwen Ding

Dataset, February, 2024

ASPLOS 2024 Artifact for "MaxK-GNN: Extremely Fast GPU Kernel Design for Accelerating Graph Neural Networks Training".

Hongwu Peng, Xi Xie, Kaustubh Shivdikar, Amit Hasan, Jiahui Zhao, Shaoyi Huang, Omer Khan, David R. Kaeli, Caiwen Ding

Dataset, February, 2024

Zero-Space Cost Fault Tolerance for Transformer-based Language Models on ReRAM.

Bingbing Li, Geng Yuan, Zigeng Wang, Shaoyi Huang, Hongwu Peng, Payman Behnam, Wujie Wen, Hang Liu, Caiwen Ding

CoRR, 2024

PruneGNN: Algorithm-Architecture Pruning Framework for Graph Neural Network Acceleration.

Deniz Gurevin, Mohsin Shan, Shaoyi Huang, Md Amit Hasan, Caiwen Ding, Omer Khan

Proceedings of the IEEE International Symposium on High-Performance Computer Architecture, 2024

MaxK-GNN: Extremely Fast GPU Kernel Design for Accelerating Graph Neural Networks Training.

Hongwu Peng, Xi Xie, Kaustubh Shivdikar, Md Amit Hasan, Jiahui Zhao, Shaoyi Huang, Omer Khan, David R. Kaeli, Caiwen Ding

Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2024

2023

MaxK-GNN: Towards Theoretical Speed Limits for Accelerating Graph Neural Networks Training.

Hongwu Peng, Xi Xie, Kaustubh Shivdikar, Md Amit Hasan, Jiahui Zhao, Shaoyi Huang, Omer Khan, David R. Kaeli, Caiwen Ding

CoRR, 2023

RRNet: Towards ReLU-Reduced Neural Network for Two-party Computation Based Private Inference.

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

CoRR, 2023

LinGCN: Structural Linearized Graph Convolutional Network for Homomorphically Encrypted Inference.

Hongwu Peng, Ran Ran, Yukui Luo, Jiahui Zhao, Shaoyi Huang, Kiran Thorat, Tong Geng, Chenghong Wang, Xiaolin Xu, Wujie Wen, Caiwen Ding

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Towards Lossless Head Pruning through Automatic Peer Distillation for Language Models.

Bingbing Li, Zigeng Wang, Shaoyi Huang, Mikhail A. Bragin, Ji Li, Caiwen Ding

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

AutoReP: Automatic ReLU Replacement for Fast Private Network Inference.

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

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Accel-GCN: High-Performance GPU Accelerator Design for Graph Convolution Networks.

Xi Xie, Hongwu Peng, Amit Hasan, Shaoyi Huang, Jiahui Zhao, Haowen Fang, Wei Zhang, Tong Geng, Omer Khan, Caiwen Ding

Proceedings of the IEEE/ACM International Conference on Computer Aided Design, 2023

Dynamic Sparse Training via Balancing the Exploration-Exploitation Trade-off.

Shaoyi Huang, Bowen Lei, Dongkuan Xu, Hongwu Peng, Yue Sun, Mimi Xie, Caiwen Ding

Proceedings of the 60th ACM/IEEE Design Automation Conference, 2023

Neurogenesis Dynamics-inspired Spiking Neural Network Training Acceleration.

Shaoyi Huang, Haowen Fang, Kaleel Mahmood, Bowen Lei, Nuo Xu, Bin Lei, Yue Sun, Dongkuan Xu, Wujie Wen, Caiwen Ding

Proceedings of the 60th ACM/IEEE Design Automation Conference, 2023

2022

Efficient Traffic State Forecasting using Spatio-Temporal Network Dependencies: A Sparse Graph Neural Network Approach.

Bin Lei, Shaoyi Huang, Caiwen Ding, Monika Filipovska

CoRR, 2022

An Automatic and Efficient BERT Pruning for Edge AI Systems.

Shaoyi Huang, Ning Liu, Yueying Liang, Hongwu Peng, Hongjia Li, Dongkuan Xu, Mimi Xie, Caiwen Ding

Proceedings of the 23rd International Symposium on Quality Electronic Design, 2022

Towards Sparsification of Graph Neural Networks.

Hongwu Peng, Deniz Gurevin, Shaoyi Huang, Tong Geng, Weiwen Jiang, Omer Khan, Caiwen Ding

Proceedings of the IEEE 40th International Conference on Computer Design, 2022

CoDG-ReRAM: An Algorithm-Hardware Co-design to Accelerate Semi-Structured GNNs on ReRAM.

Yixuan Luo, Payman Behnam, Kiran Thorat, Zhuo Liu, Hongwu Peng, Shaoyi Huang, Shu Zhou, Omer Khan, Alexey Tumanov, Caiwen Ding, Tong Geng

Proceedings of the IEEE 40th International Conference on Computer Design, 2022

A length adaptive algorithm-hardware co-design of transformer on FPGA through sparse attention and dynamic pipelining.

Hongwu Peng, Shaoyi Huang, Shiyang Chen, Bingbing Li, Tong Geng, Ang Li, Weiwen Jiang, Wujie Wen, Jinbo Bi, Hang Liu, Caiwen Ding

Proceedings of the DAC '22: 59th ACM/IEEE Design Automation Conference, San Francisco, California, USA, July 10, 2022

Analyzing and Defending against Membership Inference Attacks in Natural Language Processing Classification.

Yijue Wang, Nuo Xu, Shaoyi Huang, Kaleel Mahmood, Dan Guo, Caiwen Ding, Wujie Wen, Sanguthevar Rajasekaran

Proceedings of the IEEE International Conference on Big Data, 2022

Sparse Progressive Distillation: Resolving Overfitting under Pretrain-and-Finetune Paradigm.

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

Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

2021

Sparse Progressive Distillation: Resolving Overfitting under Pretrain-and-Finetune Paradigm.

Shaoyi Huang, Dongkuan Xu, Ian En-Hsu Yen, Sung-En Chang, Bingbing Li, Shiyang Chen, Mimi Xie, Hang Liu, Caiwen Ding

CoRR, 2021

E.T.: re-thinking self-attention for transformer models on GPUs.

Shiyang Chen, Shaoyi Huang, Santosh Pandey, Bingbing Li, Guang R. Gao, Long Zheng, Caiwen Ding, Hang Liu

Proceedings of the International Conference for High Performance Computing, 2021

Accelerating Transformer-based Deep Learning Models on FPGAs using Column Balanced Block Pruning.

Hongwu Peng, Shaoyi Huang, Tong Geng, Ang Li, Weiwen Jiang, Hang Liu, Shusen Wang, Caiwen Ding

Proceedings of the 22nd International Symposium on Quality Electronic Design, 2021

Accelerating Framework of Transformer by Hardware Design and Model Compression Co-Optimization.

Panjie Qi, Edwin Hsing-Mean Sha, Qingfeng Zhuge, Hongwu Peng, Shaoyi Huang, Zhenglun Kong, Yuhong Song, Bingbing Li

Proceedings of the IEEE/ACM International Conference On Computer Aided Design, 2021

Accommodating Transformer onto FPGA: Coupling the Balanced Model Compression and FPGA-Implementation Optimization.

Panjie Qi, Yuhong Song, Hongwu Peng, Shaoyi Huang, Qingfeng Zhuge, Edwin Hsing-Mean Sha

Proceedings of the GLSVLSI '21: Great Lakes Symposium on VLSI 2021, 2021

Co-Exploration of Graph Neural Network and Network-on-Chip Design Using AutoML.

Daniel Manu, Shaoyi Huang, Caiwen Ding, Lei Yang

Proceedings of the GLSVLSI '21: Great Lakes Symposium on VLSI 2021, 2021

HMC-TRAN: A Tensor-core Inspired Hierarchical Model Compression for Transformer-based DNNs on GPU.

Shaoyi Huang, Shiyang Chen, Hongwu Peng, Daniel Manu, Zhenglun Kong, Geng Yuan, Lei Yang, Shusen Wang, Hang Liu, Caiwen Ding

Proceedings of the GLSVLSI '21: Great Lakes Symposium on VLSI 2021, 2021