Shiyu Li
Shiyu Li
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Towards decentralized deep learning with differential privacy
HP Cheng, P Yu, H Hu, S Zawad, F Yan, S Li, H Li, Y Chen
International Conference on Cloud Computing, 130-145, 2019
LEASGD: An efficient and privacy-preserving decentralized algorithm for distributed learning
HP Cheng, P Yu, H Hu, F Yan, S Li, H Li, Y Chen
arXiv preprint arXiv:1811.11124, 2018
ESCALATE: Boosting the efficiency of sparse CNN accelerator with kernel decomposition
S Li, E Hanson, X Qian, HH Li, Y Chen
MICRO-54: 54th Annual IEEE/ACM International Symposium on Microarchitecture …, 2021
NASGEM: Neural architecture search via graph embedding method
HP Cheng, T Zhang, Y Zhang, S Li, F Liang, F Yan, M Li, V Chandra, H Li, ...
Proceedings of the AAAI Conference on Artificial Intelligence 35 (8), 7090-7098, 2021
PENNI: Pruned kernel sharing for efficient CNN inference
S Li, E Hanson, H Li, Y Chen
International Conference on Machine Learning, 5863-5873, 2020
Cascading structured pruning: enabling high data reuse for sparse dnn accelerators
E Hanson, S Li, HH Li, Y Chen
Proceedings of the 49th Annual International Symposium on Computer …, 2022
Swiftnet: Using graph propagation as meta-knowledge to search highly representative neural architectures
HP Cheng, T Zhang, Y Yang, F Yan, S Li, H Teague, H Li, Y Chen
arXiv preprint arXiv:1906.08305, 2019
DEEP: Developing extremely efficient runtime on-chip power meters
Z Xie, S Li, M Ma, CC Chang, J Pan, Y Chen, J Hu
Proceedings of the 41st IEEE/ACM International Conference on Computer-Aided …, 2022
Processing-in-memory technology for machine learning: From basic to asic
B Taylor, Q Zheng, Z Li, S Li, Y Chen
IEEE Transactions on Circuits and Systems II: Express Briefs 69 (6), 2598-2603, 2022
Inca: Input-stationary dataflow at outside-the-box thinking about deep learning accelerators
B Kim, S Li, H Li
2023 IEEE International Symposium on High-Performance Computer Architecture …, 2023
PANDA: Architecture-level power evaluation by unifying analytical and machine learning solutions
Q Zhang, S Li, G Zhou, J Pan, CC Chang, Y Chen, Z Xie
2023 IEEE/ACM International Conference on Computer Aided Design (ICCAD), 01-09, 2023
Accelerating Sparse Attention with a Reconfigurable Non-volatile Processing-In-Memory Architecture
Q Zheng, S Li, Y Wang, Z Li, Y Chen, HH Li
2023 60th ACM/IEEE Design Automation Conference (DAC), 1-6, 2023
Improving the robustness and efficiency of PIM-based architecture by SW/HW co-design
X Yang, S Li, Q Zheng, Y Chen
Proceedings of the 28th Asia and South Pacific Design Automation Conference …, 2023
In-Storage Acceleration of Graph-Traversal-Based Approximate Nearest Neighbor Search
Y Wang, S Li, Q Zheng, L Song, Z Li, A Chang, H Li, Y Chen
arXiv preprint arXiv:2312.03141, 2023
Si-Kintsugi: Towards Recovering Golden-Like Performance of Defective Many-Core Spatial Architectures for AI
E Hanson, S Li, G Zhou, F Cheng, Y Wang, R Bose, H Li, Y Chen
Proceedings of the 56th Annual IEEE/ACM International Symposium on …, 2023
Neural network training with acceleration
S Li, KT Malladi, A Chang, YS KI
US Patent App. 17/668,345, 2023
DyNNamic: Dynamically Reshaping, High Data-Reuse Accelerator for Compact DNNs
E Hanson, S Li, X Qian, HH Li, Y Chen
IEEE Transactions on Computers 72 (3), 880-892, 2022
Systems, methods, and devices for acceleration of merge join operations
S Li, Y Zhang, JH Lee, YS Ki, A Chang
US Patent 12,001,427, 2024
SiDA: Sparsity-Inspired Data-Aware Serving for Efficient and Scalable Large Mixture-of-Experts Models
Z Du, S Li, Y Wu, X Jiang, J Sun, Q Zheng, Y Wu, A Li, H Li, Y Chen
Proceedings of Machine Learning and Systems 6, 224-238, 2024
Joint Optimization of Algorithms, Hardware, and Systems for Efficient Deep Neural Networks
S Li
Duke University, 2024
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