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Hyperspectral Aquatic Radiative Transfer Modeling Using a High-Performance Cluster Computing-Based Approach
- Source :
- GIScience & Remote Sensing. 49:275-298
- Publication Year :
- 2012
- Publisher :
- Informa UK Limited, 2012.
-
Abstract
- For aquatic studies, radiative transfer (RT) modeling can be used to compute hyperspectral above-surface remote sensing reflectance that can be utilized for inverse model development. Inverse models can provide bathymetry and inherent-and bottom-optical property estimation. Because measured oceanic field/organic datasets are often spatio-temporally sparse, synthetic data generation is useful in yielding sufficiently large datasets for inversion model development; however, these forward-modeled data are computationally expensive and time-consuming to generate. This study establishes the magnitude of wall-clock-time savings achieved for performing large, aquatic RT batch-runs using parallel computing versus a sequential approach. Given 2,600 simulations and identical compute-node characteristics, sequential architecture required ~100 hours until termination, whereas a parallel approach required only ~2.5 hours (42 compute nodes)—a 40x speed-up. Tools developed for this parallel execution are discussed.
Details
- ISSN :
- 19437226 and 15481603
- Volume :
- 49
- Database :
- OpenAIRE
- Journal :
- GIScience & Remote Sensing
- Accession number :
- edsair.doi...........1bb677ac19803a4779f4198bd8203d63