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Donglin Zhuang
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Randomness in neural network training: Characterizing the impact of tooling
D Zhuang, X Zhang, S Song, S Hooker
Proceedings of Machine Learning and Systems 4, 316-336, 2022
622022
Clicktrain: Efficient and accurate end-to-end deep learning training via fine-grained architecture-preserving pruning
C Zhang, G Yuan, W Niu, J Tian, S Jin, D Zhuang, Z Jiang, Y Wang, B Ren, ...
Proceedings of the ACM international conference on supercomputing, 266-278, 2021
172021
η-lstm: Co-designing highly-efficient large lstm training via exploiting memory-saving and architectural design opportunities
X Zhang, H Xia, D Zhuang, H Sun, X Fu, MB Taylor, SL Song
2021 ACM/IEEE 48th Annual International Symposium on Computer Architecture …, 2021
132021
Flash-llm: Enabling cost-effective and highly-efficient large generative model inference with unstructured sparsity
H Xia, Z Zheng, Y Li, D Zhuang, Z Zhou, X Qiu, Y Li, W Lin, SL Song
arXiv preprint arXiv:2309.10285, 2023
122023
Enabling highly efficient capsule networks processing through software-hardware co-design
X Zhang, X Fu, D Zhuang, C Xie, SL Song
IEEE Transactions on Computers 70 (4), 495-510, 2021
62021
An efficient uncertain graph processing framework for heterogeneous architectures
H Zhang, L Li, D Zhuang, R Liu, S Song, D Tao, Y Wu, SL Song
Proceedings of the 26th ACM SIGPLAN Symposium on Principles and Practice of …, 2021
22021
Bring orders into uncertainty: enabling efficient uncertain graph processing via novel path sampling on multi-accelerator systems
H Zhang, L Li, H Liu, D Zhuang, R Liu, C Huan, S Song, D Tao, Y Liu, ...
Proceedings of the 36th ACM International Conference on Supercomputing, 1-14, 2022
12022
FP6-LLM: Efficiently Serving Large Language Models Through FP6-Centric Algorithm-System Co-Design
H Xia, Z Zheng, X Wu, S Chen, Z Yao, S Youn, A Bakhtiari, M Wyatt, ...
arXiv preprint arXiv:2401.14112, 2024
2024
DynamAP: Architectural Support for Dynamic Graph Traversal on the Automata Processor
Y Liu, X Zhang, D Zhuang, X Fu, S Song
ACM Transactions on Architecture and Code Optimization (TACO) 19 (4), 1-26, 2022
2022
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