Perspective: Uniform switching of artificial synapses for large-scale neuromorphic arrays
Perspective: Uniform switching of artificial synapses for large-scale neuromorphic arrays
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DOI：
10.1063/1.5049137
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发表时间：
2018-12-01
期刊：
影响因子：
6.1
通讯作者：
Kim, Jeehwan
中科院分区：
文献类型：
--
作者：
Tan, Scott H.;Lin, Peng;Kim, Jeehwan
阻性随机存取存储器是一种很有前途的模拟突触器件，可用于高效的生物启发神经形态计算阵列。在这里，我们首先描述相变随机存取存储器、氧化物随机存取存储器和用于人工突触的导电桥接随机存取存储器的工作原理。这些设备可以密集而高效地存储CMOS神经元电路之间的模拟突触连接。我们还讨论了模拟突触设备在实现被动神经形态计算阵列目标方面的挑战和机遇。最后，我们专注于减少空间和时间变化，这是实验实现强大和高效的神经形态计算系统的关键。(C)2018年作者(S)。
Resistive random-access memories are promising analog synaptic devices for efficient bio-inspired neuromorphic computing arrays. Here we first describe working principles for phase-change random-access memory, oxide random-access memory, and conductive-bridging random-access memory for artificial synapses. These devices could allow for dense and efficient storage of analog synapse connections between CMOS neuron circuits. We also discuss challenges and opportunities for analog synaptic devices toward the goal of realizing passive neuromorphic computing arrays. Finally, we focus on reducing spatial and temporal variations, which is critical to experimentally realize powerful and efficient neuromorphic computing systems. (C) 2018 Author(s).