A Segmented DAC Using a-IGZO TFTs for Memristor Based Neural Network Accelerators

Sagar Das, Suyash Shrivastava, Pydi Ganga Bahubalindruni, Asal Kiazadeh

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper presents a pulse amplitude modulated signal generator to address inference in Memristor based Neural Network Accelerators. As a part of this system, a novel 8-bit capacitive segmented Digital to Analog Converter (DAC) using amorphous Indium Galium Zinc Oxide (a-IGZO) thin-film transistor (TFT) technology has been designed. The DAC employs 50% segmentation with binary coded least significant bits (LSBs) and unary coded most significant bits (MSBs). This circuit has shown an ENOB of 7.3 bits at a sampling frequency of 100 kHz and an input frequency of 50 kHz. The worst case INL and DNL were recorded as 0.047 LSB and 0.34 LSB, respectively. With a power supply voltage of 5 V for the operational amplifier and 3V as the DAC reference voltage, the power consumption of the complete DAC was around 1.25 mW. This circuit can find potential applications in different flexible electronics systems.
Original languageEnglish
Title of host publicationIFETC 2023 - 5th IEEE International Flexible Electronics Technology Conference
Place of PublicationMassachusetts
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages3
ISBN (Electronic)979-8-3503-3209-4
DOIs
Publication statusPublished - 2023
Event5th IEEE International Flexible Electronics Technology Conference, IFETC 2023 - San Jose, United States
Duration: 13 Aug 202316 Aug 2023

Publication series

NameInternational Flexible Electronics Technology Conference (IFETC)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)

Conference

Conference5th IEEE International Flexible Electronics Technology Conference, IFETC 2023
Country/TerritoryUnited States
CitySan Jose
Period13/08/2316/08/23

Keywords

  • DAC
  • Flexible electronics
  • Memristors crossbars
  • Oxide TFTs

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