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School of Integrated Circuits, Peking University
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CODA redefines edge video diffusion by achieving up to 1.80x faster inference and 1.74x better energy efficiency without sacrificing output quality.
By intelligently managing resource contention, ADS-Tile slashes processing waste to below 1.2%, revolutionizing how DNNs are scheduled in autonomous driving systems.
Unlocking the potential of compute-in-memory accelerators for LLMs requires carefully navigating a complex dataflow design space, and AccelCIM provides the first systematic framework to do so.
Open-source ATLAS unlocks rapid, accurate co-design of 3D-DRAM memory systems and LLM accelerators, previously hindered by closed-source tools and customized designs.
A hybrid-bonding-based LLM serving accelerator, Helios, tackles the dynamic nature of KV cache management in LLM serving, achieving significant speedup and energy efficiency gains over existing GPU/NMP designs.
