Neuromorphic computing with spintronics

Christopher H. Marrows, Joseph Barker, Thomas A. Moore, Timothy Moorsom
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Abstract

Spintronics and magnetic materials exhibit many physical phenomena that are promising for implementing neuromorphic computing natively in hardware. Here, we review the current state-of-the-art, focusing on the areas of spintronic synapses, neurons, and neural networks. Many current implementations are based on the paradigm of reservoir computing, where the details of the network do not need to be known but where significant post-processing is needed. Benchmarks are given where possible. We discuss the scientific and technological advances needed to bring about spintronic neuromorphic computing that could be useful to an end-user in the medium term.

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利用自旋电子学的神经形态计算
自旋电子学和磁性材料表现出许多物理现象,有望在硬件中实现神经形态计算。在此,我们回顾了当前的先进技术,重点关注自旋电子突触、神经元和神经网络领域。目前的许多实现都基于存储计算的范例,在这种范例中,不需要知道网络的细节,但需要进行大量的后处理。我们尽可能给出基准。我们讨论了在中期内实现对终端用户有用的自旋电子神经形态计算所需的科学和技术进步。
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