基于CPU/GPU异构模式的高光谱遥感影像数据处理研究与实现

近年来,基于GPU的新型异构高性能计算模式的蓬勃发展为众多领域应用提供了良好的发展机遇,国内外遥感专家开始引入高性能异构计算来解决高光谱遥感影像高维空间特点所带来的数据计算量大、实时处理难等问题。在此简要介绍了高光谱遥感和CPU/GPU异构计算模式,总结了近几年国内外基于CPU/GPU异构模式的高光谱遥感数据处理研究现状和问题；并面向共享存储型小型桌面超级计算机,基于CPU/GPU异构模式实现了高光谱遥感影像MNF降维的并行化,通过与串行程序和共享存储的OpenMP同构模式对比,验证了异构模式在高光谱遥感处理领域的发展潜力。

Hyperspectral Remote Sensing Image Data Processing Research and Realization Based on CPU/GPU Heterogeneous Model

In recent years,the development of new high-performance heterogeneous computing based on GPU provides good oppotunities in many application areas.Domestic and foreign remote sensing experts have started to introduce it to solve the issues like computation intensive and difficult real-time processing caused by high-dimensional space features of hyperspectral image.In this brief introduction to hyperspectral remote sensing and CPU/GPU heterogeneous computing model,we summarized hyperspectral data processing status and problems based on CPU/GPU heterogeneous pattern in recent years,and for small desktop supercomputer with shared storage,realized parallelization of hyperspectral imaging MNF dimensionality reduction on CPU/GPU heterogeneous model,and verified the development potential of heterogeneous patterns in the field of hyperspectral remote sensing processing by contrasting with the sequential program and OpenMP.