Emerging nonvolatile memories (eNVMs) have demonstrated satisfactory accuracy on various applications in deep learning. Characterized by high density and low leakage power consumption, resistive random access memory (RRAM) becomes very attractive in synaptic devices for deep neural networks (DNNs). RRAM-based synaptic devices include both analog and discrete versions. Unlike analog RRAM synapses which suffer from nonlinearity, discrete but multistate RRAM synapses are better suited for neural network hardware implementation. In this article, the multistate operation in RRAM arrays has been proposed as a synaptic device for DNN inference. Four-state conductance has been achieved in HfO x -based RRAM synaptic arrays. The impact of total ionizing dose (TID) on the multistate behavior of HfO x -based RRAM is investigated by irradiating a one-transistor-one-resistor (1T1R) 64-kb array with CMOS peripheral decoding circuitry fabricated at the 90-nm technology node with Co-60 gamma rays ( 60 Co γ-ray irradiation).

中文翻译：

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总电离剂量对多态 HfO钪基 RRAM 突触阵列的影响


新兴的非易失性存储器（eNVM）在深度学习的各种应用中表现出了令人满意的准确性。电阻式随机存取存储器 (RRAM) 具有高密度和低泄漏功耗的特点，在深度神经网络 (DNN) 的突触设备中变得非常有吸引力。基于 RRAM 的突触器件包括模拟和离散版本。与遭受非线性影响的模拟 RRAM 突触不同，离散但多状态的 RRAM 突触更适合神经网络硬件实现。在本文中，RRAM 阵列中的多状态操作被提议作为 DNN 推理的突触设备。基于 HfO x 的 RRAM 突触阵列已实现四态电导。通过照射采用 90 nm 技术制造的 CMOS 外围解码电路的单晶体管一电阻 (1T1R) 64-kb 阵列，研究了总电离剂量 (TID) 对 HfO x 基 RRAM 多态行为的影响节点用Co-60 γ射线照射（ 60 Co γ射线照射）。