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Heterogeneous parallel computing accelerated iterative subpixel digital image correlation
Huang JW; Zhang LQ; Jiang ZY; Dong SB; Chen W; Liu YP; Liu ZJ; Zhou LC; Tang LQ
AbstractParallel computing techniques have been introduced into digital image correlation (DIC) in recent years and leads to a surge in computation speed. The graphics processing unit (GPU)-based parallel computing demonstrated a surprising effect on accelerating the iterative subpixel DIC, compared with CPU-based parallel computing. In this paper, the performances of the two kinds of parallel computing techniques are compared for the previously proposed path-independent DIC method, in which the initial guess for the inverse compositional Gauss-Newton (IC-GN) algorithm at each point of interest (POI) is estimated through the fast Fourier transform-based cross-correlation (FFT-CC) algorithm. Based on the performance evaluation, a heterogeneous parallel computing (HPC) model is proposed with hybrid mode of parallelisms in order to combine the computing power of GPU and multicore CPU. A scheme of trial computation test is developed to optimize the configuration of the HPC model on a specific computer. The proposed HPC model shows excellent performance on a middle-end desktop computer for real-time subpixel DIC with high resolution of more than 10000 POIs per frame.
Keyworddigital image correlation (DIC) inverse compositional Gauss-Newton (IC-GN) algorithm heterogeneous parallel computing graphics processing unit (GPU) multicore CPU real-time DIC
Indexed BySCI ; EI ; CSCD
WOS IDWOS:000422911200008
WOS Research AreaEngineering, Multidisciplinary ; Materials Science, Multidisciplinary
WOS SubjectEngineering ; Materials Science
Funding OrganizationNational Natural Science Foundation of China [11772131, 11772132, 11772134, 11472109] ; Natural Science Foundation of Guangdong Province, China [2015A030308017, 2015A030311046, 2015B010131009] ; Opening fund of State Key Laboratory of Nonlinear Mechanics (LNM), CAS ; State Key Lab of Subtropical Building Science, South China University of Technology [2014ZC17, 2017ZD096]
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Document Type期刊论文
Affiliation1.South China Univ Technol, Sch Civil Engn & Transportat, State Key Lab Subtrop Bldg Sci, Guangzhou 510640, Guangdong, Peoples R China
2.South China Univ Technol, Sch Comp Sci, Guangzhou 510640, Guangdong, Peoples R China
3.Chinese Acad Sci, Inst Mech, State Key Lab Nonlinear Mech, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Huang JW,Zhang LQ,Jiang ZY,et al. Heterogeneous parallel computing accelerated iterative subpixel digital image correlation[J]. SCIENCE CHINA-TECHNOLOGICAL SCIENCES,2018,61(1):74-85.
APA Huang JW.,Zhang LQ.,Jiang ZY.,Dong SB.,Chen W.,...&Tang LQ.(2018).Heterogeneous parallel computing accelerated iterative subpixel digital image correlation.SCIENCE CHINA-TECHNOLOGICAL SCIENCES,61(1),74-85.
MLA Huang JW,et al."Heterogeneous parallel computing accelerated iterative subpixel digital image correlation".SCIENCE CHINA-TECHNOLOGICAL SCIENCES 61.1(2018):74-85.
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