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Advancing Neuromorphic Computing With Loihi: A Survey of Results and Outlook

Mike Davies, Andreas Wild, Garrick Orchard, Yulia Sandamirskaya, Gabriel A. Fonseca Guerra, Prasad Joshi, Philipp Plank, Sumedh R. Risbud
<span title="">2021</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="" style="color: black;">Proceedings of the IEEE</a> </i> &nbsp;
This article provides a survey of results obtained to date with Intel's Loihi across the major algorithmic domains under study, including deep-learning approaches as well as novel approaches that aim to  ...  This is now changing with the advent of Intel's Loihi, a neuromorphic research processor designed to support a broad range of spiking neural networks with sufficient scale, performance, and features to  ...  For example, our graph search algorithm described in Section V-B uses weight plasticity in conjunction with synaptic delays to identify the shortest path in a given weighted graph.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="">doi:10.1109/jproc.2021.3067593</a> <a target="_blank" rel="external noopener" href="">fatcat:krqdmy3u6jdvfl7btjglek5ag4</a> </span>
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