Optical Satellite Remote Sensing Image Orthographic Fusion Method based on Coprocessing of CPU and GPU in Domestic Cloud Platform
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摘要: 系统地探讨了基于国产云平台调度下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，并通过数据流配置、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：本文方法可大幅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，相应的处理时间压缩至8.4S以内，并且其中GPU运算耗时仅1s, 可满足对海量数据光学卫星遥感影像进行快速正射校正的要求。
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关键词:
- 正射融合 /
- 国产云平台 /
- CPU和GPU协同处理 /
- 数据流配置 /
- 存储访问优化
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 of the traditional x86 architecture CPU to the gpu is more than 14.3 times, and the corresponding processing time is reduced to less than 8.4s, and the GPU operation time is only 1s, which can meet the requirements of rapid orthographic correction of the large data of optical satellite remote sensing image. -
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