@inproceedings{f614fc10331340beac5b8db46732b84b,
title = "Data-Intensive Supercomputing in the Cloud: Global Analytics for Satellite Imagery",
abstract = "We present our experiences using cloud computing to support data-intensive analytics on satellite imagery for commercial applications. Drawing from our background in highperformance computing, we draw parallels between the early days of clustered computing systems and the current state of cloud computing and its potential to disrupt the HPC market. Using our own virtual file system layer on top of cloud remote object storage, we demonstrate aggregate read bandwidth of 230 gigabytes per second using 512 Google Compute Engine (GCE) nodes accessing a USA multi-region standard storage bucket. This figure is comparable to the best HPC storage systems in existence. We also present several of our application results, including the identification of field boundaries in Ukraine, and the generation of a global cloud-free base layer from Landsat imagery.",
author = "Warren, {Michael S.} and Skillman, {Samuel W.} and Rick Chartrand and Tim Kelton and Ryan Keisler and David Raleigh and Matthew Turk",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 7th International Workshop on Data-Intensive Computing in the Clouds, DataCloud 2016 ; Conference date: 14-11-2016",
year = "2017",
month = feb,
day = "6",
doi = "10.1109/DataCloud.2016.007",
language = "English (US)",
series = "Proceedings of DataCloud 2016: 7th International Workshop on Data-Intensive Computing in the Clouds - Held in conjunction with SC 2016: The International Conference for High Performance Computing, Networking, Storage and Analysis",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "24--31",
booktitle = "Proceedings of DataCloud 2016",
address = "United States",
}