Fusion of memristor and digital compute-in-memory processing for energy-efficient edge computing
Tai-Hao Wen,
Je-Min Hung,
Wei-Hsing Huang
et al.
Abstract:Artificial intelligence (AI) edge devices prefer employing high-capacity nonvolatile compute-in-memory (CIM) to achieve high energy efficiency and rapid wakeup-to-response with sufficient accuracy. Most previous works are based on either memristor-based CIMs, which suffer from accuracy loss and do not support training as a result of limited endurance, or digital static random-access memory (SRAM)–based CIMs, which suffer from large area requirements and volatile storage. We report an AI edge processor that use… Show more
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