VALIDATION AND ANALYSIS OF HIGH PERFORMANCE COMPUTATION ON HYPERSPECTRAL IMAGERY BASED ON GPU
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摘要:
高光谱遥感数据具有波段多、数据量大、处理复杂等特点, 基于GPU的高性能计算在遥感领域得到了快速发展, 为高光谱数据的快速处理提供了硬件和技术条件。采用GPU对高光谱遥感数据常用的SAM、PPI等处理算法进行应用实验, 验证基于GPU的高光谱遥感数据快速处理技术。实验采用新疆东天山地区的一景星载Hyperion数据, 利用支持IDL开发语言的GPULib、CUDA运行时API库进行算法效率的验证, 结果表明, 基于GPU的高光谱数据处理效率比常规的多核CPU主机处理效率有较大提升, 具有一定的应用推广价值。
Abstract:Hyperspectral imagery has many characteristics, such as plenty of bands, large volume of data, high computing complexity. In recent years, high performance computation has been making great progress in remote sensing based on GPU, providing the hardware and technical conditions for the rapid processing of hyperspectral data. We implemented the experiments on a hyperspectral image which was obtained by Hyperion of EO-1 satellite in East Tianshan area, Xinjiang, using SAM and PPI algorithms based on CPU and GPU, trying to study the fast processing technology on hyperspectral data.. Actually the GPULib and CUDA API were used through IDL language and the data was tested by different algorithms. The results show that the processing efficiency of hyperspectral data in GPU is greater than CPU and the technology can be used in remote sensing image processing.
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Key words:
- hyperspectral data /
- GPU /
- high performance computation /
- SAM /
- PPI
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表 1 CPU-GPU基本性能测试
Table 1. Basic performance comparison of CPU and GPU
测试项目 数据大小 测试结果 矩阵乘法 矩阵转置 FFT计算 Q6600时间/s 5000×5000 126.859 0.000 4.047 10000×10000 1626.453 0.001 23.121 C2050时间/s 5000×5000 0.157 0.016 0.125 10000×10000 0.452 0.032 0.405 处理时间对比 5000×5000 820.758 0.000 32.376 10000×10000 3598.347 0.031 57.089 
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表 2 CPU与GPU的SAM性能测试
Table 2. Performance comparison of SAM algorithm between CPU and GPU
测试项目 5条参考光谱 200条参考光谱 SAM计算时间 矩阵重列时间 SAM计算时间 矩阵重列时间 CPU/s 0.469 1.000 14.093 5.516 GPU/s 0.188 0.094 2.297 1.032 效率对比 2.500 10.638 6.135 5.345 平均效率 5.209 5.890
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表 3 测试程序PPI与ENVI性能测试(CPU)
Table 3. Performance comparison of PPI between test program and ENVI on CPU
测试项目 1000单位随机向量 10000单位随机向量 逐像元 分块优化 逐像元 分块优化 ENVI/s 245 13 2163 125 程序/s 501.641 183.200 5054.172 1320.618 效率对比 0.489 0.071 0.428 0.095
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表 4 CPU与GPU测试程序PPI性能对比
Table 4. Performance comparison of PPI using test program between CPU and GPU
测试项目 1000单位随机向量 10000单位随机向量 逐像元 分块优化 逐像元 分块优化 CPU/s 501.641 183.20 5054.172 1320.618 GPU/s 523.102 10.324 5128.320 95.682 效率对比 0.958974 17.745 0.985541 13.802
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