Neuro-CIM: A 310.4 TOPS/W Neuromorphic Computing-in-Memory Processor with Low WL/BL activity and Digital-Analog Mixed-mode Neuron Firing

An energy-efficient neuromorphic computing-in-memory (CIM) processor is proposed with four key features: 1) Most significant bit (MSB) Word Skipping to reduce the BL activity; 2) Early Stopping to enable lower BL activity; 3) Mixed-mode firing for multi-macro aggregation; 4) Voltage Folding to exten...

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Bibliographic Details
Main Authors: Kim, Sangyeob, Kim, Sangjin, Um, Soyeon, Kim, Soyeon, Kim, Kwantae, Yoo, Hoi-Jun
Format: Conference Proceeding
Language:English
Subjects:
Digital-analog conversion
Dynamic range
Energy efficiency
Firing
Neuromorphics
Neurons
Voltage
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Summary:An energy-efficient neuromorphic computing-in-memory (CIM) processor is proposed with four key features: 1) Most significant bit (MSB) Word Skipping to reduce the BL activity; 2) Early Stopping to enable lower BL activity; 3) Mixed-mode firing for multi-macro aggregation; 4) Voltage Folding to extend the dynamic range. The proposed CIM achieves state-of-the-art energy efficiency of 62.1 TOPS/W (I=4b, W=8b) and 310.4 TOPS/W (I=4b, W=1b).
ISSN:2158-9682
DOI:10.1109/VLSITechnologyandCir46769.2022.9830276