SRAM based computing-in-memory for tiny machine learning

This dissertation investigates the potential of Computing-In-Memory (CIM) using Static Random-Access Memory (SRAM) to address the limitations of the Von Neumann architecture and to increase miniaturisation. This research aims to overcome this bottleneck by enabling in-memory computation for tiny mac...

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Bibliographic Details
Main Author: Gupta, Shini
Other Authors: Kim Tae Hyoung
Format: Thesis-Master by Coursework
Language:English
Published: Nanyang Technological University 2024
Subjects:
Online Access:https://hdl.handle.net/10356/175498
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Institution: Nanyang Technological University
Language: English