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检索条件："关键词=computation-in-memory "
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Architecture-circuit-technology co-optimization for resistive random access memory-based computation-in-memory chips
《Science China(Information Sciences)》2023年第10期148-157,共10页Yuyi LIU Bin GAO Jianshi TANG Huaqiang WU He QIAN 
supported by National Natural Science Foundation of China(Grant Nos.92064001,62025111,92264201);Beijing Advanced Innovation Center for Integrated Circuits。
Computation-in-memory(CIM)chips offer an energy-efficient approach to artificial intelligence computing workloads.Resistive random-access memory(RRAM)-based CIM chips have proven to be a promising solution for overcom...
关键词：resistive random-access memory computation-in-memory compact model device-architecture-algorithm co-design compiler 
Application of mathematical morphology operation with memristor-based computation-in-memory architecture for detecting manufacturing defects被引量：1
《Fundamental Research》2022年第1期123-130,共8页Ying Zhou Bin Gao Qingtian Zhang Peng Yao Yiwen Geng Xinyi Li Wen Sun Meiran Zhao Yue Xi Jianshi Tang He Qian Huaqiang Wu 
the National Natural Science Foundation of China(Grants No.92064001,61851404,and 61874169);the IoT Intelligent Microsystem Center of Tsinghua University-China Mobile Joint Research Institute.
Mathematical morphology operations are widely used in image processing such as defect analysis in semiconductor manufacturing and medical image analysis.These data-intensive applications have high requirements during ...
关键词：MEMRISTOR Computation-in-memory Mathematical morphology Defect detection 
Towards efficient allocation of graph convolutional networks on hybrid computation-in-memory architecture被引量：6
《Science China(Information Sciences)》2021年第6期108-121,共14页Jiaxian CHEN Guanquan LIN Jiexin CHEN Yi WANG 
supported in part by National Natural Science Foundation of China (Grant No. 61972259);Guangdong Basic and Applied Basic Research Foundation (Grant Nos. 2019B151502055, 2017B030314073, 2018B030325002)。
Graph convolutional networks(GCNs) have been applied successfully in social networks and recommendation systems to analyze graph data. Unlike conventional neural networks, GCNs introduce an aggregation phase, which is...
关键词：computation-in-memory graph convolutional networks hybrid architecture scheduling inference ACCELERATOR 
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