Design Tools for Resistive Crossbar based Machine Learning Accelerators

2021 IEEE 3rd International Conference on Artificial Intelligence Circuits and Systems (AICAS)(2021)

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摘要
Resistive crossbar based accelerators for Machine Learning (ML) have attracted great interest as they offer the prospect of high density on-chip storage as well as efficient in-memory matrix-vector multiplication (MVM) operations. Despite their promises, they present several design challenges, such as high write costs, overhead of analog-to-digital and digital-to-analog converters and other periph...
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关键词
Performance evaluation,Machine learning algorithms,Digital-analog conversion,Estimation,Machine learning,Tools,System-on-chip
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