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Wei Zhao

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#edge computing Nov 2026

DIAMM: A Distributed Inference Acceleration Framework for Multimodal Edge Applications

Multimodal applications such as educational assistants and medical diagnosis demand high concurrency and low latency, and are increasingly served by edge inference enhanced with Retrieval-Augmented Generation (RAG). However, heterogeneous multimodal models and fragmented edge resources couple three problems that prior...

Zhi Yao, Zhi-Qing Tang, Han-Shuai Cui et al. · 0 citations
Sep 2026

Efficient LLM Coserving at the Edge via Resource-Aware Cooperative Scheduling

Large language models (LLMs) are increasingly deployed on edge nodes to support edge intelligence applications. To overcome limited GPU memory, offloading-based methods partition model parameters between the GPU and host memory, enabling inference on commodity hardware. However, deploying a single model instance using...

Zhen-Zheng Li, Zhi-Qing Tang, Jian-Xiong Guo et al. · 0 citations
#edge computing Sep 2026

Efficient Layer-Granularity Unloading for LLMs in Edge Computing

Advancements in edge computing and container technology have made it increasingly popular and convenient to deploy Large Language Models (LLMs) through containers at the edge. However, the limited GPU resources of edge servers make it impractical to retain the model in GPU memory for long periods due to the high memory...

Zhenzheng Li, Zhiqing Tang, Jianxiong Guo et al. · 1 citation

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