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- Title
A multi-device version of the HYFMGPU algorithm for hyperspectral scenes registration.
- Authors
Fernández-Fabeiro, Jorge; Gonzalez-Escribano, Arturo; Ordóñez, Álvaro; Heras, Dora B.
- Abstract
Hyperspectral image registration is a relevant task for real-time applications like environmental disasters management or search and rescue scenarios. Traditional algorithms were not really devoted to real-time performance, even when ported to GPUs or other parallel devices. Thus, the HYFMGPU algorithm arose as a solution to such a lack. Nevertheless, as sensors are expected to evolve and thus generate images with finer resolutions and wider wavelength ranges, a multi-GPU implementation of this algorithm seems to be necessary in a near future. This work presents a multi-device MPI + CUDA implementation of the HYFMGPU algorithm that distributes all its stages among several GPUs. This version has been validated testing it for 5 different real hyperspectral images, with sizes from about 80 MB to nearly 2 GB, achieving speedups for the whole execution of the algorithm from 1.18 × to 1.59 × in 2 GPUs and from 1.26 × to 2.58 × in 4 GPUs. The parallelization efficiencies obtained are stable around 86 % and 78 % for 2 and 4 GPUs, respectively, which proves the scalability of this multi-device version.
- Subjects
GRAPHICS processing units; COMPUTER algorithms; HYPERSPECTRAL imaging systems; IMAGE registration; REAL-time computing; FOURIER transforms; REMOTE-sensing images
- Publication
Journal of Supercomputing, 2019, Vol 75, Issue 3, p1551
- ISSN
0920-8542
- Publication type
Article
- DOI
10.1007/s11227-018-2689-7