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

In-Memory Computation has received a lot of attention in recent years as a method to solve the von Neumann bottleneck. In CIM operations, ADCs are often needed to convert the analog voltage to obtain digital codes. However, today's ADCs for CIM often require a large amount of silicon area in th...

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Main Author: Wu, Yiheng
Other Authors: Kim Tae Hyoung
Format: Thesis-Master by Coursework
Language:English
Published: Nanyang Technological University 2021
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Online Access:https://hdl.handle.net/10356/154402
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1544022023-07-04T15:07:50Z Power- and area-efficient analog-to-digital conversion for in-memory computing Wu, Yiheng Kim Tae Hyoung School of Electrical and Electronic Engineering THKIM@ntu.edu.sg Engineering::Electrical and electronic engineering::Electronic circuits In-Memory Computation has received a lot of attention in recent years as a method to solve the von Neumann bottleneck. In CIM operations, ADCs are often needed to convert the analog voltage to obtain digital codes. However, today's ADCs for CIM often require a large amount of silicon area in the structure and operating power consumption. Therefore, ADCs used in CIM structures often have high requirements for power consumption and silicon area. In this paper, a monotonic switching SAR ADC is implemented and some improvements are made to its comparator and control logic to reduce the power consumption and silicon area. The metal-insulator-metal structure is also used to reduce the parasitic capacitance at the top plate of the DAC capacitor array to reduce the gain error. Using 65-nm technology for simulation, the ENOB is 9.64 bits, SNR is 59.94 dB, SNDR is 59.81 dB, SFDR is 73.51 dB, power consumption is 18.7 μW, and FOM is 2.34 fJ/Conv.-step at a supply voltage of 0.8V and a sampling rate of 10 MS/s. Master of Science (Electronics) 2021-12-23T13:01:43Z 2021-12-23T13:01:43Z 2021 Thesis-Master by Coursework Wu, Y. (2021). Power- and area-efficient analog-to-digital conversion for in-memory computing. Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/154402 https://hdl.handle.net/10356/154402 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::Electronic circuits
spellingShingle Engineering::Electrical and electronic engineering::Electronic circuits
Wu, Yiheng
Power- and area-efficient analog-to-digital conversion for in-memory computing
description In-Memory Computation has received a lot of attention in recent years as a method to solve the von Neumann bottleneck. In CIM operations, ADCs are often needed to convert the analog voltage to obtain digital codes. However, today's ADCs for CIM often require a large amount of silicon area in the structure and operating power consumption. Therefore, ADCs used in CIM structures often have high requirements for power consumption and silicon area. In this paper, a monotonic switching SAR ADC is implemented and some improvements are made to its comparator and control logic to reduce the power consumption and silicon area. The metal-insulator-metal structure is also used to reduce the parasitic capacitance at the top plate of the DAC capacitor array to reduce the gain error. Using 65-nm technology for simulation, the ENOB is 9.64 bits, SNR is 59.94 dB, SNDR is 59.81 dB, SFDR is 73.51 dB, power consumption is 18.7 μW, and FOM is 2.34 fJ/Conv.-step at a supply voltage of 0.8V and a sampling rate of 10 MS/s.
author2 Kim Tae Hyoung
author_facet Kim Tae Hyoung
Wu, Yiheng
format Thesis-Master by Coursework
author Wu, Yiheng
author_sort Wu, Yiheng
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 2021
url https://hdl.handle.net/10356/154402
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