GPU-accelerated raster map reprojection

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21110%2F16%3A00301889" target="_blank" >RIV/68407700:21110/16:00301889 - isvavai.cz</a>

Výsledek na webu

<a href="https://ojs.cvut.cz/ojs/index.php/gi/article/view/gi.15.1.5" target="_blank" >https://ojs.cvut.cz/ojs/index.php/gi/article/view/gi.15.1.5</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.14311/gi.15.1.5" target="_blank" >10.14311/gi.15.1.5</a>

Jazyk výsledku

angličtina

Název v původním jazyce

GPU-accelerated raster map reprojection

Popis výsledku v původním jazyce

Reprojecting raster maps from one projection to another is an essential part of many cartographic processes (map comparison, overlays, data presentation, ...) and reducing the required computational time is desirable and often significantly decreases overall processing costs. The raster reprojection process operates per-pixel and is, therefore, a good candidate for GPU-based parallelization where the large number of processors can lead to a very high degree of parallelism. We have created an experimental implementation of the raster reprojection with GPU-based parallelization (using OpenCL API). During the evaluation, we compared the performance of our implementation to the optimized GDAL and showed that there is a class of problems where GPU-based parallelization can lead to more than sevenfold speedup.

Název v anglickém jazyce

GPU-accelerated raster map reprojection

Popis výsledku anglicky

Reprojecting raster maps from one projection to another is an essential part of many cartographic processes (map comparison, overlays, data presentation, ...) and reducing the required computational time is desirable and often significantly decreases overall processing costs. The raster reprojection process operates per-pixel and is, therefore, a good candidate for GPU-based parallelization where the large number of processors can lead to a very high degree of parallelism. We have created an experimental implementation of the raster reprojection with GPU-based parallelization (using OpenCL API). During the evaluation, we compared the performance of our implementation to the optimized GDAL and showed that there is a class of problems where GPU-based parallelization can lead to more than sevenfold speedup.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2016

Kód důvěrnosti údajů

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

Název periodika

Geoinformatics

ISSN

1802-2669

e-ISSN

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Svazek periodika

15

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

8

Strana od-do

61-68

Kód UT WoS článku

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EID výsledku v databázi Scopus

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