Vertical Metal-Oxide Electrochemical Memory for High-Density Synaptic Array Based High-Performance Neuromorphic Computing,Advanced Electronic Materials

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Vertical Metal-Oxide Electrochemical Memory for High-Density Synaptic Array Based High-Performance Neuromorphic Computing
Advanced Electronic Materials ( IF 5.3 ) Pub Date : 2022-08-04 , DOI: 10.1002/aelm.202200378
Hyunjoon Lee ₁ , Da Gil Ryu ₁ , Giho Lee ₁ , Min‐Kyu Song ₂ , Hyungjin Moon ₁ , Jaehyeong Lee ₁ , Jongchan Ryu ₁ , Ji‐Hoon Kang ₃ , Junmin Suh ₂ , Sangbum Kim ₄ , Jongwoo Lim ₅ , Dongsuk Jeon ₆ , Seyoung Kim ₇ , Jeehwan Kim _{2,

3} , Yun Seog Lee ₁

Affiliation

Cross-point arrays of analog synaptic devices are expected to realize neuromorphic computing hardware for neural network computations with compelling speed boost and superior energy efficiency, as opposed to the conventional hardware based on the von Neumann architecture. To achieve desired characteristics of analog synaptic devices for fully parallel vector–matrix multiplication and vector–vector outer-product updates, metal-oxide based electrochemical random-access memory (ECRAM) is proposed as a promising synaptic device due to its complementary metal-oxide-semiconductor-compatibility and outstanding synaptic characteristics over other non-volatile memory candidates. In this work, ECRAM devices with 3D vertical structure is fabricated to demonstrate a minimal 4F² cell size, highly scalable channel volume and low programming energy, providing optimized synaptic device performance and characteristics as well as high integrity as a cross-point array. Various weight-update profiles of the vertical ECRAM devices are obtained by adjusting programming voltage pulses, exhibiting trade-offs among dynamic range, linearity, symmetry, and update deviation. Based on simulation with advanced algorithms for analog cross-point array and neural network designs, the potential of vertical ECRAM for high-density array is evaluated. Simulation studies suggest that the neuromorphic computing performance can be improved further by balancing the weight update characteristics of vertical ECRAM.

中文翻译：

用于基于高密度突触阵列的高性能神经形态计算的垂直金属氧化物电化学存储器

与基于冯诺依曼架构的传统硬件相比，模拟突触设备的交叉点阵列有望实现神经网络计算的神经形态计算硬件，具有引人注目的速度提升和卓越的能源效率。为了实现模拟突触器件的完全并行向量-矩阵乘法和向量-向量外积更新所需的特性，基于金属氧化物的电化学随机存取存储器 (ECRAM) 因其互补金属氧化物被提出作为一种有前途的突触器件- 与其他非易失性存储器候选者相比，半导体兼容性和突出的突触特性。在这项工作中，制造了具有 3D 垂直结构的 ECRAM 器件以展示最小的 4 F ²单元尺寸、高度可扩展的通道体积和低编程能量，提供优化的突触设备性能和特性以及作为交叉点阵列的高完整性。通过调整编程电压脉冲获得垂直 ECRAM 器件的各种权重更新曲线，在动态范围、线性度、对称性和更新偏差之间进行权衡。基于模拟交叉点阵列和神经网络设计的高级算法的仿真，评估了垂直 ECRAM 用于高密度阵列的潜力。仿真研究表明，通过平衡垂直 ECRAM 的权重更新特性，可以进一步提高神经形态计算性能。

更新日期：2022-08-04

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