Assessing the Performance-Energy Balance of Graphics Processors for Spectral Unmixing
Impact
![Google Scholar](/xmlui/themes/Mirage2/images/uji/logo_google.png)
![Microsoft Academico](/xmlui/themes/Mirage2/images/uji/logo_microsoft.png)
Metadata
Show full item recordcomunitat-uji-handle:10234/9
comunitat-uji-handle2:10234/7036
comunitat-uji-handle3:10234/8620
comunitat-uji-handle4:
INVESTIGACIONThis resource is restricted
http://dx.doi.org/10.1109/JSTARS.2014.2322035 |
Metadata
Title
Assessing the Performance-Energy Balance of Graphics Processors for Spectral UnmixingDate
2014Publisher
IEEEISSN
1939-1404Type
info:eu-repo/semantics/articlePublisher version
http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6841607&filter%3DAND% ...Subject
Abstract
Remotely sensed hyperspectral imaging missions are often limited by onboard power restrictions while, simultaneously, require high computing power in order to address applications with relevant constraints in terms ... [+]
Remotely sensed hyperspectral imaging missions are often limited by onboard power restrictions while, simultaneously, require high computing power in order to address applications with relevant constraints in terms of processing times. In recent years, graphics processing units (GPUs) have emerged as a commodity computing platform suitable to meet real-time processing requirements in hyperspectral image processing. On the other hand, GPUs are power-hungry devices, which result in the need to explore the tradeoff between the expected high performance and the significant power consumption of computing architectures suitable to perform fast processing of hyperspectral images. In this paper, we explore the balance between computing performance and power consumption of GPUs in the context of a popular hyperspectral imaging application, such as spectral unmixing. Specifically, we investigate several processing chains for spectral unmixing and evaluate them on three different GPUs, corresponding to the two latest generations of GPUs from NVIDIA (“Fermi” and “Kepler”), as well as an alternative low-power system more suitable for embedded appliances. Our paper provides some observations about the possibility to use GPUs as effective onboard devices in hyperspectral imaging applications. [-]
Is part of
Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of, 2014, vol. 7, nº 6, p. 2305-2316.Rights
"(c) 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works."
http://rightsstatements.org/vocab/InC/1.0/
info:eu-repo/semantics/restrictedAccess
http://rightsstatements.org/vocab/InC/1.0/
info:eu-repo/semantics/restrictedAccess
This item appears in the folowing collection(s)
- ICC_Articles [427]