NASA NTRS · 20180005471
Optimization of Selected Remote Sensing Algorithms for Embedded NVIDIA Kepler GPU Architecture
Abstract
This paper evaluates the potential of embedded Graphic Processing Units (GPUs) in Nvidia's Tegra K1 (based on Kepler (TM) hardware) for onboard processing. The performance is compared to a general purpose multi-core CPU (Central Processing Unit) and a fully-fledged GPU accelerator. This study uses two algorithms: Wavelet Spectral Dimension Reduction of Hyperspectral Imagery and Automated Cloud-Cover Assessment (ACCA) Algorithm. Tegra K1 achieved 51 for the ACCA algorithm and 20 for the dimension reduction algorithm, as compared to the performance of the high-end 8-core server Intel Xeon CPU with 13.5 times higher power consumption.
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Riha, Lubomir, Le Moigne, Jacqueline, El-Ghazawi, Tarek. 2015-07-26. Optimization of Selected Remote Sensing Algorithms for Embedded NVIDIA Kepler GPU Architecture. https://ntrs.nasa.gov/citations/20180005471
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