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|Title:||Parallel computing in experimental mechanics and optical measurement : a review (II)||Authors:||Wang, Tianyi
|Keywords:||Engineering::Computer science and engineering||Issue Date:||2017||Source:||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||Journal:||Optics and Lasers in Engineering||Abstract:||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.||URI:||https://hdl.handle.net/10356/138746||ISSN:||0143-8166||DOI:||10.1016/j.optlaseng.2017.06.002||Rights:||© 2017 Elsevier Ltd. All rights reserved.||Fulltext Permission:||none||Fulltext Availability:||No Fulltext|
|Appears in Collections:||SCSE Journal Articles|
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