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Parallel implementation for SAM algorithm based on GPU and distributed computing

  • Harbin Institute of Technology
  • Liaoning Technical University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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.

Original languageEnglish
Title of host publicationIGARSS 2012 - 2012 IEEE International Geoscience and Remote Sensing Symposium
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4074-4077
Number of pages4
ISBN (Electronic)9781467311595
DOIs
StatePublished - 2012
Event32nd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2012 - Munich, Germany
Duration: 22 Jul 201227 Jul 2012

Publication series

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)
ISSN (Print)2153-6996
ISSN (Electronic)2153-7003

Conference

Conference32nd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2012
Country/TerritoryGermany
CityMunich
Period22/07/1227/07/12

Keywords

  • distributed computing
  • GPU
  • high-performance computing
  • SAM

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