Parallel implementation for SAM algorithm based on GPU and distributed computing

Author

Qu, Haicheng ; Zhang, Junping ; Chen, Yushi ; Chen, Hao ; Lin, Zhouhan

Author_Institution

Dept. of Inf. Eng., Harbin Inst. of Technol., Harbin, China

fYear

2012

fDate

22-27 July 2012

Firstpage

4074

Lastpage

4077

Abstract

Advances in sensor and computer technology are revolutionizing the way that remote sensing data with hundreds or even thousands of channels for the same area on the surface of the earth is collected, managed and analyzed. In this paper, the classical Spectral Angle Mapper (SAM) algorithm, which is fit for parallel and distributed computing, is implemented by using Graphic Processing Units (GPU) and distributed cluster respectively to accelerate the computations. A quantitative performance comparison between Compute Unified Device Architecture (CUDA) and Matlab platform is given by analyzing result of different parallel architectures´ implementation of the same SAM algorithm.

Keywords

geophysical image processing; graphics processing units; parallel architectures; remote sensing; CUDA; Earth surface; GPU; Matlab platform; SAM algorithm; compute unified device architecture; computer technology; distributed cluster; distributed computing; graphic processing unit; parallel architecture; parallel computing; remote sensing data; sensor technology; spectral angle mapper; Acceleration; Algorithm design and analysis; Clustering algorithms; Graphics processing units; Hyperspectral imaging; MATLAB; GPU; SAM; distributed computing; high-performance computing;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International

Conference_Location

Munich

ISSN

2153-6996

Print_ISBN

978-1-4673-1160-1

Electronic_ISBN

2153-6996

Type

conf

DOI

10.1109/IGARSS.2012.6350514

Filename

6350514