A memristive neural network based matrix equation solver with high versatility and high energy efficiency  

作　　者：Jiancong LI Houji ZHOU Yi LI Xiangshui MIAO 

机构地区：[1]School of Optical and Electronic Information,Huazhong University of Science and Technology,Wuhan 430074,China [2]School of Integrated Circuits,Huazhong University of Science and Technology,Wuhan 430074,China [3]Wuhan National Laboratory for Optoelectronics,Wuhan 430074,China

出　　处：《Science China(Information Sciences)》2023年第2期194-204,共11页中国科学（信息科学）（英文版）

基　　金：partly supported by National Key R&D Program of China(Grant No.2019YFB2205100);National Natural Science Foundation of China(Grant Nos.61874164,61841404);Hubei Key Laboratory of Advanced Memories,and Hubei Engineering Research Center on Microelectronics。

摘　　要：As the main topic in modern scientific computing and machine learning tasks,matrix equation solving is suffering high computational latency and tremendous power consumption due to the frequent data movement in traditional von Neumann computers.Although the in-memory computing paradigms have shown the potential to accelerate the execution of solving matrix equations,the existing memristive matrix equation solvers are still limited by the low system versatility and low computation precision of the memristor arrays.In this work,we demonstrate a hybrid architecture for accurate,as well as efficient,matrix equation solving problems,where the memristive crossbar arrays are used for the parallel vector-matrix multiplication and the digital computer for accuracy.The linear neural-network solving(NNS)method is adopted here and its versatility for various types of matrix equations is proved.The weight-slice computation method is developed to perform the analog matrix multiplication with high efficiency and high robustness in the array.The solution results confirmed that typical matrix equations can be solved by this memristive matrix equation solver with high accuracy.Further performance benchmarking demonstrates that the generalized memristive matrix equation solver has low solving time-complexity while outperforming the state-of-the-art CMOS and in-memory processors.

关 键 词：matrix equation solving MEMRISTOR linear neural network matrix-multiplication analog computing 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]