Abstract
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 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.
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Huang, J., Zhang, L., Jiang, Z. et al. Heterogeneous parallel computing accelerated iterative subpixel digital image correlation. Sci. China Technol. Sci. 61, 74–85 (2018). https://doi.org/10.1007/s11431-017-9168-0
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DOI: https://doi.org/10.1007/s11431-017-9168-0