Please use this identifier to cite or link to this item:
Full metadata record
DC FieldValueLanguage
dc.contributor.authorYang, Chufengen_US
dc.identifier.citationYang, C. (2022). Energy-efficient analog-to-digital conversion for in-memory computing. Master's thesis, Nanyang Technological University, Singapore.
dc.description.abstractIn-Memory Computing is a trending approach tackling power overhead and latency from the conventional von Neumann architecture. ADC is a commonly utilized power-hungry component that converts analog intermediate computing results to digital form for further operations. However, it is challenging to achieve energy-efficient ADCs for IMC with high accuracy. Moreover, low-supply devices usually suffer from PVT variations which degrades performance. In this study, an 8-bit SAR ADC is implemented, which utilizes a monotonic set-and-down switching method with a PVT-variation compensation system. Adaptations to IMC-specific requirements are adopted, such as using transmission gates as input switches, inverted StrongARM comparator with pMOS as input transistors, improved digital control circuit for lower power and higher accuracy, and adapted locking criteria for local supply generation. Simulated using 65nm CMOS technology at 27°C under 1V supply voltage and sampling at 50 MS/s, the circuit achieves ENOB of 7.75 bits, FOM of 38.87 fJ/Conv.-step, RMSE of 0.3515 standalone. When connected in IMC and under favorable conditions of 80°C or +5% supply voltage, the power is comparable to the same ADC structure without compensation. Under unfavorable conditions such as -20°C or -5% supply, the accuracy is maintained while power increases.en_US
dc.publisherNanyang Technological Universityen_US
dc.subjectEngineering::Electrical and electronic engineering::Electronic circuitsen_US
dc.titleEnergy-efficient analog-to-digital conversion for in-memory computingen_US
dc.typeThesis-Master by Courseworken_US
dc.contributor.supervisorKim Tae Hyoungen_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.degreeMaster of Science (Electronics)en_US
item.fulltextWith Fulltext-
Appears in Collections:EEE Theses
Files in This Item:
File Description SizeFormat 
  Restricted Access
2.43 MBAdobe PDFView/Open

Page view(s)

Updated on Dec 2, 2022


Updated on Dec 2, 2022

Google ScholarTM


Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.