Design Tools for Resistive Crossbar based Machine Learning Accelerators
2021 IEEE 3rd International Conference on Artificial Intelligence Circuits and Systems (AICAS)(2021)
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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