Name
Title | ||
|---|---|---|
Optimization Of Selected Remote Sensing Algorithms For Embedded Nvidia Kepler Gpu Architecture |
Abstract | ||
|---|---|---|
This paper evaluates the potential of embedded Graphic Processing Units in the Nvidia's Tegra K1 for onboard processing. The performance is compared to a general purpose multi-core CPU and full fledge 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 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. |
Year | Venue | Keywords |
|---|---|---|
2015 | 2015 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) | remote sensing, GPU, Tegra K1, ACCA, dimension reduction |
Field | DocType | ISSN |
Central processing unit,Dimensionality reduction,System on a chip,Algorithm design,Computer science,Remote sensing,Parallel computing,Algorithm,Hyperspectral imaging,Xeon,Wavelet,Data reduction | Conference | 2153-6996 |
Citations | PageRank | References |
0 | 0.34 | 1 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lubomir Riha | 1 | 39 | 14.31 |
| Jacqueline Le Moigne | 2 | 253 | 32.19 |
| tarek elghazawi | 3 | 697 | 84.30 |