Heterogeneous parallel computing accelerated iterative subpixel digital image correlation

Parallel 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 accel- erating the iterative subpixel DIC, compared with...

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Veröffentlicht in:Science China. Technological sciences Jg. 61; H. 1; S. 74 - 85
Hauptverfasser: Huang, JianWen, Zhang, LingQi, Jiang, ZhenYu, Dong, ShouBin, Chen, Wei, Liu, YiPing, Liu, ZeJia, Zhou, LiCheng, Tang, LiQun
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Beijing Science China Press 2018
Springer Nature B.V
Schlagworte:
Computation
Cross correlation
Digital imaging
Engineering
Fast Fourier transformations
Fourier transforms
Graphics processing units
Iterative methods
Performance evaluation
Pixels
graphics processing unit (GPU)
heterogeneous parallel computing
digital image correlation (DIC)
real-time DIC
multicore CPU
inverse compositional Gauss-Newton (IC-GN) algorithm
ISSN:1674-7321, 1869-1900
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Zusammenfassung:Parallel 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 accel- erating 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.
Bibliographie:Parallel 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 accel- erating 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.
digital image correlation （DIC）, inverse compositional Gauss-Newton （IC-GN） algorithm, heterogeneous parallel com-puting, graphics processing unit （GPU）, multicore CPU, real-time DIC
11-5845/TH
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SourceType-Scholarly Journals-1
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ISSN:1674-7321
1869-1900
DOI:10.1007/s11431-017-9168-0