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Published VersionCC BY V4.0, Open Access
Journal article
GPU-Based Embedded Intelligence Architectures and Applications
Electronics, Vol.10(952), pp.1-20
2021
Abstract
This paper present contributions to the state-of-the art for graphics processing unit (GPU-based) embedded intelligence (EI) research for architectures and applications. This paper gives a comprehensive review and representative studies of the emerging and current paradigms for GPU-based EI with the focus on the architecture, technologies and applications: (1) First, the overview and classifications of GPU-based EI research are presented to give the full spectrum in this area that also serves as a concise summary of the scope of the paper; (2) Second, various architecture technologies for GPU-based deep learning techniques and applications are discussed in detail; and (3) Third, various architecture technologies for machine learning techniques and applications are discussed. This paper aims to give useful insights for the research area and motivate researchers towards the development of GPU-based EI for practical deployment and applications.
Details
- Title
- GPU-Based Embedded Intelligence Architectures and Applications
- Authors
- Li Minn Ang (Author) - University of the Sunshine Coast, Queensland, School of Science and Engineering - LegacyKah Phooi Seng (Author) - UNSW Australia
- Publication details
- Electronics, Vol.10(952), pp.1-20
- Publisher
- MDPI AG
- Date published
- 2021
- DOI
- 10.3390/electronics10080952
- ISSN
- 2079-9292
- Copyright note
- Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/)
- Organisation Unit
- University of the Sunshine Coast, Queensland; School of Science, Technology and Engineering; Engage Research Lab
- Language
- English
- Record Identifier
- 99526508502621
- Output Type
- Journal article
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- Domestic collaboration
- Web Of Science research areas
- Computer Science, Information Systems
- Engineering, Electrical & Electronic
- Physics, Applied
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