Deep Learning on Mobile Devices With Neural Processing Units

Tianxiang Tan; Guohong Cao

doi:10.1109/MC.2022.3215780

Deep Learning on Mobile Devices With Neural Processing Units

Tianxiang Tan, Guohong Cao

Computer Science and Engineering

Research output: Contribution to specialist publication › Article

4 Scopus citations

Abstract

Although deep neural networks (DNNs) can require less processing time when running on neural processing units (NPUs) instead of CPUs, their accuracy can degrade. We point out three research directions to improve DNN performance on mobile devices with NPUs.

Original language	English (US)
Pages	48-57
Number of pages	10
Volume	56
No	8
Specialist publication	Computer
DOIs	https://doi.org/10.1109/MC.2022.3215780
State	Published - Aug 1 2023

All Science Journal Classification (ASJC) codes

General Computer Science

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10.1109/MC.2022.3215780

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title = "Deep Learning on Mobile Devices With Neural Processing Units",

abstract = "Although deep neural networks (DNNs) can require less processing time when running on neural processing units (NPUs) instead of CPUs, their accuracy can degrade. We point out three research directions to improve DNN performance on mobile devices with NPUs.",

author = "Tianxiang Tan and Guohong Cao",

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year = "2023",

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doi = "10.1109/MC.2022.3215780",

language = "English (US)",

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AB - Although deep neural networks (DNNs) can require less processing time when running on neural processing units (NPUs) instead of CPUs, their accuracy can degrade. We point out three research directions to improve DNN performance on mobile devices with NPUs.

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JO - Computer

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Deep Learning on Mobile Devices With Neural Processing Units

Abstract

All Science Journal Classification (ASJC) codes

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