Deep learning acceleration: from quantization to in-memory computing

Deep learning acceleration: from quantization to in-memory computing

Deep learning has demonstrated high accuracy and efficiency in various applications. For example, Convolutional Neural Networks (CNNs) widely adopted in Computer Vision (CV) and Transformers broadly applied in Natural Language Processing (NLP) are representative deep learning models. Deep learning m...

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Bibliographic Details
Main Author: Zhu, Shien
Other Authors: Weichen Liu
Format: Thesis-Doctor of Philosophy
Language:English
Published: Nanyang Technological University 2022
Subjects:
Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
Engineering::Computer science and engineering::Hardware::Arithmetic and logic structures
Engineering::Computer science and engineering::Computer systems organization::Special-purpose and application-based systems
Online Access:https://hdl.handle.net/10356/163448

Internet

https://hdl.handle.net/10356/163448

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