Parallel computing in experimental mechanics and optical measurement : a review (II)

With advantages such as non-destructiveness, high sensitivity and high accuracy, optical techniques have successfully integrated into various important physical quantities in experimental mechanics (EM) and optical measurement (OM). However, in pursuit of higher image resolutions for higher accuracy...

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Main Authors: Wang, Tianyi, Qian, Kemao
Other Authors: School of Computer Science and Engineering
Format: Article
Language:English
Published: 2020
Subjects:
CPU
Online Access:https://hdl.handle.net/10356/138746
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1387462020-05-12T06:14:02Z Parallel computing in experimental mechanics and optical measurement : a review (II) Wang, Tianyi Qian, Kemao School of Computer Science and Engineering Engineering::Computer science and engineering Parallel Computing CPU With advantages such as non-destructiveness, high sensitivity and high accuracy, optical techniques have successfully integrated into various important physical quantities in experimental mechanics (EM) and optical measurement (OM). However, in pursuit of higher image resolutions for higher accuracy, the computation burden of optical techniques has become much heavier. Therefore, in recent years, heterogeneous platforms composing of hardware such as CPUs and GPUs, have been widely employed to accelerate these techniques due to their cost-effectiveness, short development cycle, easy portability, and high scalability. In this paper, we analyze various works by first illustrating their different architectures, followed by introducing their various parallel patterns for high speed computation. Next, we review the effects of CPU and GPU parallel computing specifically in EM & OM applications in a broad scope, which include digital image/volume correlation, fringe pattern analysis, tomography, hyperspectral imaging, computer-generated holograms, and integral imaging. In our survey, we have found that high parallelism can always be exploited in such applications for the development of high-performance systems. MOE (Min. of Education, S’pore) 2020-05-12T06:14:02Z 2020-05-12T06:14:02Z 2017 Journal Article Wang, T., & Qian, K. (2018). Parallel computing in experimental mechanics and optical measurement : a review (II). Optics and Lasers in Engineering, 104, 181-191. doi:10.1016/j.optlaseng.2017.06.002 0143-8166 https://hdl.handle.net/10356/138746 10.1016/j.optlaseng.2017.06.002 2-s2.0-85020122206 104 181 191 en Optics and Lasers in Engineering © 2017 Elsevier Ltd. All rights reserved.
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic Engineering::Computer science and engineering
Parallel Computing
CPU
spellingShingle Engineering::Computer science and engineering
Parallel Computing
CPU
Wang, Tianyi
Qian, Kemao
Parallel computing in experimental mechanics and optical measurement : a review (II)
description With advantages such as non-destructiveness, high sensitivity and high accuracy, optical techniques have successfully integrated into various important physical quantities in experimental mechanics (EM) and optical measurement (OM). However, in pursuit of higher image resolutions for higher accuracy, the computation burden of optical techniques has become much heavier. Therefore, in recent years, heterogeneous platforms composing of hardware such as CPUs and GPUs, have been widely employed to accelerate these techniques due to their cost-effectiveness, short development cycle, easy portability, and high scalability. In this paper, we analyze various works by first illustrating their different architectures, followed by introducing their various parallel patterns for high speed computation. Next, we review the effects of CPU and GPU parallel computing specifically in EM & OM applications in a broad scope, which include digital image/volume correlation, fringe pattern analysis, tomography, hyperspectral imaging, computer-generated holograms, and integral imaging. In our survey, we have found that high parallelism can always be exploited in such applications for the development of high-performance systems.
author2 School of Computer Science and Engineering
author_facet School of Computer Science and Engineering
Wang, Tianyi
Qian, Kemao
format Article
author Wang, Tianyi
Qian, Kemao
author_sort Wang, Tianyi
title Parallel computing in experimental mechanics and optical measurement : a review (II)
title_short Parallel computing in experimental mechanics and optical measurement : a review (II)
title_full Parallel computing in experimental mechanics and optical measurement : a review (II)
title_fullStr Parallel computing in experimental mechanics and optical measurement : a review (II)
title_full_unstemmed Parallel computing in experimental mechanics and optical measurement : a review (II)
title_sort parallel computing in experimental mechanics and optical measurement : a review (ii)
publishDate 2020
url https://hdl.handle.net/10356/138746
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