Publications

First-author Papers

[ASPLOS’24] EVT: Accelerating Deep Learning Training with Epilogue Visitor Tree

Zhaodong Chen, Andrew Kerr, Richard Cai, Jack Kosaian, Haicheng Wu, Yufei Ding, and Yuan Xie. EVT: Accelerating deep learning training with epilogue visitor tree. In Proceedings of the 27th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2024

[PPoPP’23] Dynamic N:M Fine-grained Structured Sparse Attention Mechanism

Zhaodong Chen, Zheng Qu, Yuying Quan, Liu Liu, Yufei Ding, and Yuan Xie. Dynamic n: M fine-grained structured sparse attention mechanism. In Proceedings of the 28th ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming, pages 369–379, 2023

[SC’21] Efficient tensor core-based gpu kernels for structured sparsity under reduced precision

Zhaodong Chen*, Zheng Qu*, Liu Liu, Yufei Ding, and Yuan Xie. Efficient tensor core-based gpu kernels for structured sparsity under reduced precision. In Proceedings of the International Conference for High-Performance Computing, Networking, Storage and Analysis, pages 1–14, 2021

[ICCAD’20] fuseGNN: Accelerating Graph Convolutional Neural Network Training on GPGPU

Zhaodong Chen, Mingyu Yan, Maohua Zhu, Lei Deng, Guoqi Li, Shuangchen Li, and Yuan Xie. fusegnn: Accelerating graph convolutional neural network training on gpgpu. In Proceedings of the 39th International Conference on Computer-Aided Design, pages 1–9, 2020

[TPAMI] A Comprehensive and Modularized Statistical Framework for Gradient Norm Equality in Deep Neural Networks

Zhaodong Chen*, Lei Deng*, Bangyan Wang, Guoqi Li, and Yuan Xie. A comprehensive and modularized statistical framework for gradient norm equality in deep neural networks. IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(1):13–31, 2020

[TNNLS] Effective and Efficient Batch Normalization Using a Few Uncorrelated Data for Statistics Estimation

Zhaodong Chen*, Lei Deng*, Guoqi Li, Jiawei Sun, Xing Hu, Ling Liang, Yufei Ding, and Yuan Xie. Effective and efficient batch normalization using a few uncorrelated data for statistics estimation. IEEE Transactions on Neural Networks and Learning Systems, 32(1):348–362, 2020

Co-authored Papers

[TC] Dynamic Sparse Attention for Scalable Transformer Acceleration

Liu Liu, Zheng Qu, Zhaodong Chen, Fengbin Tu, Yufei Ding, and Yuan Xie. Dynamic sparse attention for scalable transformer acceleration. IEEE Transactions on Computers, 71(12):3165–3178, 2022

[DATE’22] Accelerating Spatiotemporal Supervised Training of Large-scale Spiking Neural Networks on GPU

Ling Liang, Zhaodong Chen, Lei Deng, Fengbin Tu, Guoqi Li, and Yuan Xie. Accelerating spatiotemporal supervised training of large-scale spiking neural networks on gpu. In 2022 Design, Automation & Test in Europe Conference & Exhibition (DATE), pages 658–663. IEEE, 2022

[ASPLOS’22] Dota: Detect and Omit Weak Attentions for Scalable Transformer Acceleration

Zheng Qu, Liu Liu, Fengbin Tu, Zhaodong Chen, Yufei Ding, and Yuan Xie. Dota: detect and omit weak attentions for scalable transformer acceleration. In Proceedings of the 27th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, pages 14–26, 2022

[ATC’22] Faith: An Efficient Framework for Transformer Verification on GPUs

Boyuan Feng, Tianqi Tang, Yuke Wang, Zhaodong Chen, Zheng Wang, Shu Yang, Yuan Xie, and Yufei Ding. Faith: An efficient framework for transformer verification on {GPUs}. In 2022 USENIX Annual Technical Conference (USENIX ATC 22), pages 167–182, 2022

[TCAD] H2learn: High-efficiency Learning Accelerator for High-accuracy Spiking Neural Networks

Ling Liang, Zheng Qu, Zhaodong Chen, Fengbin Tu, Yujie Wu, Lei Deng, Guoqi Li, Peng Li, and Yuan Xie. H2learn: High-efficiency learning accelerator for high-accuracy spiking neural networks. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 41(11):4782–4796, 2021

[ICML’20] Boosting Deep Neural Network Efficiency with Dual-module Inference

Liu Liu, Lei Deng, Zhaodong Chen, Yuke Wang, Shuangchen Li, Jingwei Zhang, Yihua Yang, Zhenyu Gu, Yufei Ding, and Yuan Xie. Boosting deep neural network efficiency with dual-module inference. In International Conference on Machine Learning, pages 6205–6215. PMLR, 2020

[CAL] Characterizing and Understanding GCNs on GPU

Mingyu Yan, Zhaodong Chen, Lei Deng, Xiaochun Ye, Zhimin Zhang, Dongrui Fan, and Yuan Xie. Characterizing and understanding gcns on gpu. IEEE Computer Architecture Letters, 19(1):22–25, 2020

[CVPR’19 Oral] Hardness-aware Deep Metric Learning

Wenzhao Zheng, Zhaodong Chen, Jiwen Lu, and Jie Zhou. Hardness-aware deep metric learning. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 72–81, 2019

^* Equal authorship