Power- and area-efficient analog-to-digital conversion for in-memory computing

In-memory computing is an emerging trend in Industrial Revolution 4.0 that focuses in artificial intelligent and machine learning. By moving the computation to the edge, in-memory computing reduces energy consumption and data size that needs to be processed further. To enable an efficient in-memory...

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Main Author: Hans, Michael
Other Authors: Kim Tae Hyoung
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2023
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Online Access:https://hdl.handle.net/10356/167799
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1677992023-07-07T15:44:13Z Power- and area-efficient analog-to-digital conversion for in-memory computing Hans, Michael Kim Tae Hyoung School of Electrical and Electronic Engineering THKIM@ntu.edu.sg Engineering::Electrical and electronic engineering::Integrated circuits In-memory computing is an emerging trend in Industrial Revolution 4.0 that focuses in artificial intelligent and machine learning. By moving the computation to the edge, in-memory computing reduces energy consumption and data size that needs to be processed further. To enable an efficient in-memory computing, analog-to-digital converters (ADC) are required to have high linearity, low power, and low area to store the computed data in digital form. The ADC used in this report is based on monotonic successive approximate register (SAR) that has been reported to have low switching power consumption and low area. This project further lowers the area and power consumption by reducing the resolution from 10-bit to 8-bit. The ADC is designed and simulated using TSMCn65LP CMOS technology node. Simulation results show the performance of 100MS/s with power consumption of 0.162mW Bachelor of Engineering (Electrical and Electronic Engineering) 2023-06-05T02:03:54Z 2023-06-05T02:03:54Z 2023 Final Year Project (FYP) Hans, M. (2023). Power- and area-efficient analog-to-digital conversion for in-memory computing. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/167799 https://hdl.handle.net/10356/167799 en application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Electrical and electronic engineering::Integrated circuits
spellingShingle Engineering::Electrical and electronic engineering::Integrated circuits
Hans, Michael
Power- and area-efficient analog-to-digital conversion for in-memory computing
description In-memory computing is an emerging trend in Industrial Revolution 4.0 that focuses in artificial intelligent and machine learning. By moving the computation to the edge, in-memory computing reduces energy consumption and data size that needs to be processed further. To enable an efficient in-memory computing, analog-to-digital converters (ADC) are required to have high linearity, low power, and low area to store the computed data in digital form. The ADC used in this report is based on monotonic successive approximate register (SAR) that has been reported to have low switching power consumption and low area. This project further lowers the area and power consumption by reducing the resolution from 10-bit to 8-bit. The ADC is designed and simulated using TSMCn65LP CMOS technology node. Simulation results show the performance of 100MS/s with power consumption of 0.162mW
author2 Kim Tae Hyoung
author_facet Kim Tae Hyoung
Hans, Michael
format Final Year Project
author Hans, Michael
author_sort Hans, Michael
title Power- and area-efficient analog-to-digital conversion for in-memory computing
title_short Power- and area-efficient analog-to-digital conversion for in-memory computing
title_full Power- and area-efficient analog-to-digital conversion for in-memory computing
title_fullStr Power- and area-efficient analog-to-digital conversion for in-memory computing
title_full_unstemmed Power- and area-efficient analog-to-digital conversion for in-memory computing
title_sort power- and area-efficient analog-to-digital conversion for in-memory computing
publisher Nanyang Technological University
publishDate 2023
url https://hdl.handle.net/10356/167799
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