4 papers
DS-CIM: Digital Stochastic Computing-In-Memory Featuring Accurate OR-Accumulation via Sample Region Remapping for Edge AI Models
Kunming Shao, Liang Zhao, Jiangnan Yu +5
Stochastic computing (SC) offers hardware simplicity but suffers from low throughput, while high-throughput Digital Computing-in-Memory (DCIM) is bottlenecked by costly adder logic…
A Memory-Efficient Retrieval Architecture for RAG-Enabled Wearable Medical LLMs-Agents
Zhipeng Liao, Kunming Shao, Jiangnan Yu +5
With powerful and integrative large language models (LLMs), medical AI agents have demonstrated unique advantages in providing personalized medical consultations, continuous health…
DIRC-RAG: Accelerating Edge RAG with Robust High-Density and High-Loading-Bandwidth Digital In-ReRAM Computation
Kunming Shao, Zhipeng Liao, Jiangnan Yu +9
Retrieval-Augmented Generation (RAG) enhances large language models (LLMs) by integrating external knowledge retrieval but faces challenges on edge devices due to high storage, ene…
A Flexible Precision Scaling Deep Neural Network Accelerator with Efficient Weight Combination
Liang Zhao, Kunming Shao, Fengshi Tian +3
Deploying mixed-precision neural networks on edge devices is friendly to hardware resources and power consumption. To support fully mixed-precision neural network inference, it is…