Three Papers Accepted by DAC'2024

Three papers on efficient and privacy-preserving deep learning are accepted by DAC'2024 as regular papers, includin “Alchemist: A Unified Accelerator Architecture for Cross-Scheme Fully Homomorphic Encryption”, “FastQuery: Communication-efficient Embedding Table Query for Private LLMs inference”, and “MoteNN: Memory Optimization via Fine-grained Scheduling for Deep Neural Networks on Tiny Devices”.

Last updated on Jun 29, 2024
Conference
Meng Li
Meng Li
Assistant Professor

I am currently a tenure-track assistant professor jointly affiliated with the Institute for Artificial Intelligence and School of Integrated Circuits in Peking University. My research interests focus on efficient and secure multi-modality AI acceleration algorithms and hardwares.

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