1 citations · 1 across the 4 of their papers we have counts for
5 papers
HDA-MoE: Hybrid Parallelism and Dynamic, Adaptive Scheduling for Mixture-of-Experts with 3D Near-Memory Processing
Haochen Huang, Shuzhang Zhong, Shengxuan Qiu +8
Mixture-of-Experts (MoE) architectures have become a key technique for scaling Large Language Models (LLMs), enabling high model capacity with reduced computational cost. However,…
C2C-Explorer: An Exploration Framework for Chip-to-Chip Interconnect Architectures in LLM Cloud Computing Systems
Jiayi Li, Di Wu, Qingxu Li +10
The scaling-up of large language models (LLMs) necessitates computing systems to have multi-processor-chip architectures, elevating the importance of chip-to-chip (C2C) communicati…
CODA: Algorithm-Hardware Co-design for Edge Video Diffusion via NMP-Enabled Compute-Cache Operator Disaggregation
Yuanpeng Zhang, YuXuan Wu, Yitong Xiao +6
Deploying Video Diffusion Models (VDMs) on edge devices is appealing for localized and privacy-preserving generation, but their iterative Transformer-based denoising remains too sl…
Enabling Efficient Transaction Processing on CXL-Based Memory Sharing
Zhao Wang, Yiqi Chen, Cong Li +5
Transaction processing systems are the crux for modern data-center applications, yet current multi-node systems are slow due to network overheads. This paper advocates for Compute…
Unicorn: Unified Neural Image Compression with One Number Reconstruction
Qi Zheng, Haozhi Wang, Zihao Liu +8
Prevalent lossy image compression schemes can be divided into: 1) explicit image compression (EIC), including traditional standards and neural end-to-end algorithms; 2) implicit im…