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Real-Time Implementation of the Vertex Component Analysis Algorithm on GPUs

机译:GPU上顶点分量分析算法的实时实现

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In this letter, we present a new parallel implementation of the vertex component analysis (VCA) algorithm for spectral unmixing of remotely sensed hyperspectral data on commodity graphics processing units. We first developed a C serial version of the VCA algorithm and three parallel versions: one using NVIDIA's Compute Unified Device Architecture (CUDA), another using CUDA basic linear algebra subroutines library CUBLAS, and the last using the CUDA linear algebra library CULA. Experimental results, based on the analysis of hyperspectral images acquired by a variety of hyperspectral imaging sensors, show the effectiveness of our implementation, which satisfies the real-time constraints given by the data acquisition rate.
机译:在这封信中,我们提出了一种新的并行实现的顶点分量分析(VCA)算法,用于对商品图形处理单元上的遥感高光谱数据进行光谱分解。我们首先开发了VCA算法的C串行版本和三个并行版本:一个使用NVIDIA的Compute Unified Device Architecture(CUDA),另一个使用CUDA基本线性代数子例程库CUBLAS,最后一个使用CUDA线性代数库CULA。基于对各种高光谱成像传感器采集的高光谱图像的分析,实验结果表明了我们实施的有效性,它满足了数据采集速率所给出的实时约束。

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