3D Reservoir Computing with High Area Efficiency (5.12 TOPS/mm<sup>2</sup>) Implemented by 3D Dynamic Memristor Array for Temporal Signal Processing

Wenxuan Sun, Woyu Zhang, Jie Yu, Yi Li, Zeyu Guo, Jinru Lai, Danian Dong, Xu Zheng, Fei Wang, Shaoyang Fan, Xiaoxin Xu, Dashan Shang, Ming Liu

20222022 IEEE Symposium on VLSI Technology and Circuits (VLSI Technology and Circuits)17 citationsDOI

Abstract

In this work, we realized a three-dimensional (3D) reservoir computing (RC) by utilizing the I-V nonlinearity and short-term memory of the dynamic memristor in 4-layer vertical array. The cycle-to-cycle variation of the dynamic reservoir is improved by parallel memristor configuration. The dimensionality of the reservoir space is increased by input strategy design. After the hardware-software co-optimization, the proposed 3D RC system exhibits high recognition accuracy (90%), low energy consumption (~0.78 pJ /operation), and high area efficiency (5.12 TOPS/mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ).

Topics & Concepts

MemristorReservoir computingTOPSCurse of dimensionalityComputer scienceSIGNAL (programming language)Nonlinear systemSignal processingWork (physics)Parallel computingComputational scienceComputer hardwareAlgorithmArtificial intelligenceDigital signal processingElectronic engineeringMathematicsPhysicsEngineeringArtificial neural networkGeometryRecurrent neural networkThermodynamicsQuantum mechanicsAzimuthProgramming languageNeural Networks and Reservoir ComputingAdvanced Memory and Neural ComputingNeural dynamics and brain function