Master Thesis Parallelizing Remote Sensing Image Geometric Correction by Gerard Bernabeu
Universitat Aut`onomade Barcelona Escola d'Enginyeria Computer Architecture and Operating Systems Department M.Sc. in High Performance Computing, Information Theory and Security Master Thesis Parallelizing remote sensing image geometric correction by Gerard Bernabeu Date: July 3, 2012 Directed by: Ana Cort´esFit´e Llu´ısPesquer Mayos Master Thesis M.Sc. in High Performance Computing, Information Theory and Security Course 2011-12 Parallelizing remote sensing image geometric correction Author: Gerard Bernabeu Altay´o Directors: Ana Cort´esFit´e Llu´ısPesquer Mayos Computer Architecture and Operating Systems Escola d'Enginyeria Universitat Aut`onomade Barcelona Signatures Author Directors Abstract Remote sensing spatial, spectral, and temporal resolutions of images, acquired over a reasonably sized image extent, result in imagery that can be processed to represent land cover over large areas with an amount of spatial detail that is very attractive for monitoring, management, and scientific activities. With Moore's Law alive and well, more and more parallelism is introduced into all computing platforms, at all levels of integration and programming to achieve higher performance and energy efficiency. Being the geometric calibration process one of the most time consuming processes when using remote sensing images, the aim of this work is to accelerate this process by taking advantage of new computing architectures and technologies, specially focusing in exploiting computation over shared memory multi-threading hardware. A parallel implementation of the most time consuming process in the remote sensing geometric correction has been implemented using OpenMP directives. This work compares the performance of the original serial binary versus the parallelized implementation, using several multi-threaded modern CPU architectures, discussing about the approach to find the optimum hardware for a cost-effective execution.
[Show full text]