Northwestern University

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Filtering by: Keyword compute in memory (CIM) Resource type Dissertation

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Low-Power Mixed-Signal Time-Domain Hardware Accelerator Design for Edge Computing and Machine Learning

Description:

While the entire silicon industry has been blooming under Moore’s Law for decades, conventional digital implementation is approaching the “stall” of Moore’s Law due to many physical design limitations. Technology innovation now is going to take a different direction. Given the increasing demand for emerging applications' computational capacity, it is...

Keyword:

computer architecture, mixed-signal time-domain computing, analog computing, machine learning , compute in memory (CIM), and image processing

Subject:

Electrical engineering, Computer engineering, and Engineering

Creator:

Chen, Zhengyu

Owner:

Scholarly Digital Publishing

Language:

en

Date Uploaded:

02/01/2021

Date Created:

2020-01-01

Resource Type:

Dissertation

Alternate Identifier:

http://dissertations.umi.com/northwestern:15414 and etdadmin_upload_780953