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Optimization of Selected Remote Sensing Algorithms for Many-Core Architectures

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27740%2F16%3A86099011" target="_blank" >RIV/61989100:27740/16:86099011 - isvavai.cz</a>

  • Result on the web

    <a href="http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7471409" target="_blank" >http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7471409</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/JSTARS.2016.2558492" target="_blank" >10.1109/JSTARS.2016.2558492</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Optimization of Selected Remote Sensing Algorithms for Many-Core Architectures

  • Original language description

    This paper evaluates the potential of embedded graphic processing units (GPU) in the Nvidia's Tegra K1 for onboard processing. The performance is compared to a general purpose multicore central processing unit (CPU), a full-fledge GPU accelerator, and an Intel Xeon Phi coprocessor, for two representative potential applications, wavelet spectral dimension reduction of hyperspectral imagery and automated cloud-cover assessment (ACCA). For these applications, Tegra K1 achieved 51% performance for the ACCA algorithm and 20% performance for the dimension reduction algorithm, as compared to the performance of the high-end eight-core server Intel Xeon CPU which has a 13.5 times higher power consumption. This paper also shows the potential of modern high-performance computing accelerators for algorithms such as the ones for which the paper presents an optimized parallel implementation. The two algorithms that were tested mostly contain spatially localized computations, and one can assume that all image processing algorithms containing localized computations would exhibit similar speed-ups when implemented on these parallel architectures.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

    Result was created during the realization of more than one project. More information in the Projects tab.

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2016

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    IEEE Journal of selected topics in applied earth observations and remote sensing

  • ISSN

    1939-1404

  • e-ISSN

  • Volume of the periodical

    9

  • Issue of the periodical within the volume

    12

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    12

  • Pages from-to

    5576-5587

  • UT code for WoS article

    000391468900003

  • EID of the result in the Scopus database

    2-s2.0-84969555915