基于云平台CPU与GPU协同处理的光学卫星遥感影像正射融合方法
Optical Satellite Remote Sensing Image Orthographic Fusion Method Based on Coprocessing of CPU and GPU in Domestic Cloud Platform
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系统探讨了基于国产云平台调度下自主可控CPU和GPU协同处理的光学卫星遥感影像正射融合方法执行效率问题, 通过数据流配置、中间数据存储访问优化等手段进一步提高了该方法执行效率. 在云平台调度下, 使用飞腾S2500和英伟达A100对高分二号卫星多光谱影像进行正射融合的试验, 结果表明, 该方法可很大程度提高光学卫星遥感影像正射融合效率, 与传统X86架构CPU与GPU协同的正射融合算法相比, 加速比为14.3倍以上, 数据处理时间压缩至8.4 s内, 其中GPU运算耗时仅1 s, 可满足并优化大数据量的光学卫星遥感影像快速正射融合的要求.Abstract: The processing efficiency of optical satellite remote sensing image orthographic fusion method based on coprocessing of CPU and GPU in domestic cloud platform is discussed systematically and is improved by data flow configuration and the intermediate data storage access optimization. The Phytium S2500 and NVIDIA A100 are used in the cloud platform to do the orthographic fusion experiment. The experiment results show that the method can greatly improve the fusion efficiency of optical satellite remote sensing image, and the acceleration ratio is more than 14.3 times of the traditional X86 architecture CPU and GPU collaborative orthographic fusion algorithm., and the corresponding processing time is reduced to less than 8.4 s, and the GPU operation time is only 1 s, which can meet the requirements of rapid orthographic correction of the large data of optical satellite remote sensing image.
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