An efficient geosciences workflow on multi-core processors and GPUs: a case study for aerosol optical depth retrieval from MODIS satellite data
Journal article
Authors | Liu, Jia, Feld, Dustin, Xue, Yong, Garcke, Jochen, Soddemann, Thomas, Pan, Peiyuan and Fraunhofer Institute of Algorhithms and Scientific Computing |
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Abstract | Quantitative remote sensing retrieval algorithms help understanding the dynamic aspects of Digital Earth. However, the Big Data and complex models in Digital Earth pose grand challenges for computation infrastructures. In this article, taking the aerosol optical depth (AOD) retrieval as a study case, we exploit parallel computing methods for high efficient geophysical parameter retrieval. We present an efficient geocomputation workflow for the AOD calculation from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data. According to their individual potential for parallelization, several procedures were adapted and implemented for a successful parallel execution on multi-core processors and Graphics Processing Units (GPUs). The benchmarks in this paper validate the high parallel performance of the retrieval workflow with speedups of up to 5.x on a multi-core processor with 8 threads and 43.x on a GPU. To specifically address the time-consuming model retrieval part, hybrid parallel patterns which combine the multi-core processor’s and the GPU’s compute power were implemented with static and dynamic workload distributions and evaluated on two systems with different CPU–GPU configurations. It is shown that only the dynamic hybrid implementation leads to a greatly enhanced overall exploitation of the heterogeneous hardware environment in varying circumstances. |
Keywords | Digital earth; High performance computing; Graphics processing units (GPU); Multi-core; Hybrid parallel pattern; Aerosol optical depth; Retrieval workflow |
Year | 2016 |
Journal | International Journal of Digital Earth |
Publisher | Taylor & Francis |
ISSN | 17538947 |
17538955 | |
Digital Object Identifier (DOI) | https://doi.org/10.1080/17538947.2015.1130087 |
Web address (URL) | http://hdl.handle.net/10545/621605 |
hdl:10545/621605 | |
Publication dates | 25 Feb 2016 |
Publication process dates | |
Deposited | 10 May 2017, 15:06 |
Rights | Archived with thanks to International Journal of Digital Earth |
Contributors | Chinese Academy of Sciences, University of Cologne, London Metropolitan University and University of Bonn |
File | File Access Level Open |
https://repository.derby.ac.uk/item/9400q/an-efficient-geosciences-workflow-on-multi-core-processors-and-gpus-a-case-study-for-aerosol-optical-depth-retrieval-from-modis-satellite-data
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