Scipediacontent: Scipediacontent moved page Draft Content 729539987 to Turilli et al 2019a

2021-02-01T19:00:57Z

Scipediacontent moved page Draft Content 729539987 to Turilli et al 2019a

Scipediacontent: Created page with " == Abstract == Ecological sciences are using imagery from a variety of sources to monitor and survey populations and ecosystems. Very High Resolution (VHR) satellite imagery..."

2021-02-01T19:00:52Z

Created page with " == Abstract == Ecological sciences are using imagery from a variety of sources to monitor and survey populations and ecosystems. Very High Resolution (VHR) satellite imagery..."

New page

== Abstract ==

Ecological sciences are using imagery from a variety of sources to monitor and survey populations and ecosystems. Very High Resolution (VHR) satellite imagery provide an effective dataset for large scale surveys. Convolutional Neural Networks have successfully been employed to analyze such imagery and detect large animals. As the datasets increase in volume, O(TB), and number of images, O(1k), utilizing High Performance Computing (HPC) resources becomes necessary. In this paper, we investigate a task-parallel data-driven workflows design to support imagery analysis pipelines with heterogeneous tasks on HPC. We analyze the capabilities of each design when processing a dataset of 3,000 VHR satellite images for a total of 4~TB. We experimentally model the execution time of the tasks of the image processing pipeline. We perform experiments to characterize the resource utilization, total time to completion, and overheads of each design. Based on the model, overhead and utilization analysis, we show which design approach to is best suited in scientific pipelines with similar characteristics.

Comment: 10 page

== Original document ==

The different versions of the original document can be found in:

* [http://arxiv.org/abs/1905.09766 http://arxiv.org/abs/1905.09766]

* [http://arxiv.org/pdf/1905.09766 http://arxiv.org/pdf/1905.09766]

* [http://xplorestaging.ieee.org/ielx7/9036011/9041688/09041805.pdf?arnumber=9041805 http://xplorestaging.ieee.org/ielx7/9036011/9041688/09041805.pdf?arnumber=9041805],
: [http://dx.doi.org/10.1109/escience.2019.00013 http://dx.doi.org/10.1109/escience.2019.00013]

* [https://dblp.uni-trier.de/db/journals/corr/corr1905.html#abs-1905-09766 https://dblp.uni-trier.de/db/journals/corr/corr1905.html#abs-1905-09766],
: [https://arxiv.org/abs/1905.09766 https://arxiv.org/abs/1905.09766],
: [http://arxiv.org/pdf/1905.09766.pdf http://arxiv.org/pdf/1905.09766.pdf],
: [https://academic.microsoft.com/#/detail/3012308615 https://academic.microsoft.com/#/detail/3012308615]

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Scipediacontent: Scipediacontent moved page Draft Content 729539987 to Turilli et al 2019a

Scipediacontent: Created page with " == Abstract == Ecological sciences are using imagery from a variety of sources to monitor and survey populations and ecosystems. Very High Resolution (VHR) satellite imagery..."