Frontiers in Physics (Oct 2022)
Edge GPU cluster processing system for laser interference image collection
Abstract
In order to realize the real-time processing and communication of multi-laser interference images, a GPU cluster processing system for laser interference images was designed. The measured target was illuminated by multiple lasers, and the image information of the multi-laser interference fringes was obtained by the CCD. The data of laser interference images from CPU was transmitted by the GPU cluster, and the image feature recognition and transmission were completed through the cluster image processing module. A multi-channel laser interference image transmission algorithm was designed by the multi-core and multi-buffer (MCMB) algorithm. In the experiment, the laser interference images were collected by the CPU, and then the real-time communication of multi-channel images data was completed by the GPU cluster. The packet loss rate experiment showed that when the data traffic reached 110, the data was lost with the traditional UDP communication algorithm, and the slope of the fitting curve was 0.6,053. When the data flow reached 160, the data was lost with MCMB algorithm, and the slope of the fitting curve was 0.2,181. In contrast, the GPU occupancy of this algorithm was improved, and it was still not saturated at 210 data streams. In a word, the system has better optimization effect in real-time processing and communication of multi-laser interference images.
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