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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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. |
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Engineering::Computer science and engineering Parallel Computing CPU Wang, Tianyi Qian, Kemao Parallel computing in experimental mechanics and optical measurement : a review (II) |
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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. |
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School of Computer Science and Engineering |
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School of Computer Science and Engineering Wang, Tianyi Qian, Kemao |
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Wang, Tianyi Qian, Kemao |
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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) |
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Parallel computing in experimental mechanics and optical measurement : a review (II) |
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Parallel computing in experimental mechanics and optical measurement : a review (II) |
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parallel computing in experimental mechanics and optical measurement : a review (ii) |
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2020 |
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https://hdl.handle.net/10356/138746 |
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