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Donglin Zhuang
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2020 – today
- 2024
- [c7]Donglin Zhuang, Zhen Zheng, Haojun Xia, Xiafei Qiu, Junjie Bai, Wei Lin, Shuaiwen Leon Song:
MonoNN: Enabling a New Monolithic Optimization Space for Neural Network Inference Tasks on Modern GPU-Centric Architectures. OSDI 2024: 989-1005 - [c6]Haojun Xia, Zhen Zheng, Xiaoxia Wu, Shiyang Chen, Zhewei Yao, Stephen Youn, Arash Bakhtiari, Michael Wyatt, Donglin Zhuang, Zhongzhu Zhou, Olatunji Ruwase, Yuxiong He, Shuaiwen Leon Song:
Quant-LLM: Accelerating the Serving of Large Language Models via FP6-Centric Algorithm-System Co-Design on Modern GPUs. USENIX ATC 2024: 699-713 - [i4]Haojun Xia, Zhen Zheng, Xiaoxia Wu, Shiyang Chen, Zhewei Yao, Stephen Youn, Arash Bakhtiari, Michael Wyatt, Donglin Zhuang, Zhongzhu Zhou, Olatunji Ruwase, Yuxiong He, Shuaiwen Leon Song:
FP6-LLM: Efficiently Serving Large Language Models Through FP6-Centric Algorithm-System Co-Design. CoRR abs/2401.14112 (2024) - 2023
- [j3]Haojun Xia, Zhen Zheng, Yuchao Li, Donglin Zhuang, Zhongzhu Zhou, Xiafei Qiu, Yong Li, Wei Lin, Shuaiwen Leon Song:
Flash-LLM: Enabling Low-Cost and Highly-Efficient Large Generative Model Inference With Unstructured Sparsity. Proc. VLDB Endow. 17(2): 211-224 (2023) - [i3]Haojun Xia, Zhen Zheng, Yuchao Li, Donglin Zhuang, Zhongzhu Zhou, Xiafei Qiu, Yong Li, Wei Lin, Shuaiwen Leon Song:
Flash-LLM: Enabling Cost-Effective and Highly-Efficient Large Generative Model Inference with Unstructured Sparsity. CoRR abs/2309.10285 (2023) - 2022
- [j2]Yiding Liu, Xingyao Zhang, Donglin Zhuang, Xin Fu, Shuaiwen Song:
DynamAP: Architectural Support for Dynamic Graph Traversal on the Automata Processor. ACM Trans. Archit. Code Optim. 19(4): 60:1-60:26 (2022) - [c5]Heng Zhang, Lingda Li, Hang Liu, Donglin Zhuang, Rui Liu, Chengying Huan, Shuang Song, Dingwen Tao, Yongchao Liu, Charles He, Yanjun Wu, Shuaiwen Leon Song:
Bring orders into uncertainty: enabling efficient uncertain graph processing via novel path sampling on multi-accelerator systems. ICS 2022: 11:1-11:14 - [c4]Donglin Zhuang, Xingyao Zhang, Shuaiwen Song, Sara Hooker:
Randomness in Neural Network Training: Characterizing the Impact of Tooling. MLSys 2022 - 2021
- [j1]Xingyao Zhang, Xin Fu, Donglin Zhuang, Chenhao Xie, Shuaiwen Leon Song:
Enabling Highly Efficient Capsule Networks Processing Through Software-Hardware Co-Design. IEEE Trans. Computers 70(4): 495-510 (2021) - [c3]Chengming Zhang, Geng Yuan, Wei Niu, Jiannan Tian, Sian Jin, Donglin Zhuang, Zhe Jiang, Yanzhi Wang, Bin Ren, Shuaiwen Leon Song, Dingwen Tao:
ClickTrain: efficient and accurate end-to-end deep learning training via fine-grained architecture-preserving pruning. ICS 2021: 266-278 - [c2]Xingyao Zhang, Haojun Xia, Donglin Zhuang, Hao Sun, Xin Fu, Michael B. Taylor, Shuaiwen Leon Song:
η-LSTM: Co-Designing Highly-Efficient Large LSTM Training via Exploiting Memory-Saving and Architectural Design Opportunities. ISCA 2021: 567-580 - [c1]Heng Zhang, Lingda Li, Donglin Zhuang, Rui Liu, Shuang Song, Dingwen Tao, Yanjun Wu, Shuaiwen Leon Song:
An efficient uncertain graph processing framework for heterogeneous architectures. PPoPP 2021: 477-479 - [i2]Donglin Zhuang, Xingyao Zhang, Shuaiwen Leon Song, Sara Hooker:
Randomness In Neural Network Training: Characterizing The Impact of Tooling. CoRR abs/2106.11872 (2021) - 2020
- [i1]Chengming Zhang, Geng Yuan, Wei Niu, Jiannan Tian, Sian Jin, Donglin Zhuang, Zhe Jiang, Yanzhi Wang, Bin Ren, Shuaiwen Leon Song, Dingwen Tao:
An Efficient End-to-End Deep Learning Training Framework via Fine-Grained Pattern-Based Pruning. CoRR abs/2011.10170 (2020)
Coauthor Index
aka: Shuaiwen Leon Song
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