AMED: Automatic Mixed-Precision Quantization for Edge Devices

AMED: Automatic Mixed-Precision Quantization for Edge Devices

Quantized neural networks are well known for reducing the latency, power consumption, and model size without significant harm to the performance. This makes them highly appropriate for systems with limited resources and low power capacity. Mixed-precision quantization offers better utilization of cu...

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Bibliographic Details
Main Authors: Moshe Kimhi, Tal Rozen, Avi Mendelson, Chaim Baskin
Format: Article
Language:English
Published: MDPI AG 2024-06-01
Series:Mathematics
Subjects:
deep learning
quantization
CNN
latency optimization
Online Access:https://www.mdpi.com/2227-7390/12/12/1810

Internet

https://www.mdpi.com/2227-7390/12/12/1810

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