@inproceedings{558119585e474a28952bce784f1b320b,
title = "Scaling GIS analysis tasks from the desktop to the cloud utilizing contemporary distributed computing and data management approaches: A case study of project-based learning and cyberinfrastructure concepts",
abstract = "In this paper we present the experience of scaling in parallel a geographic information system modeling framework to hundreds of processors. The project began in an active learning cyberinfrastructure course which was followed by an XSEDE ECSS effort in collaboration across multiple-institutions.",
keywords = "CyberGIS, GDAL, GRASS, Makeflow, Work Queue",
author = "Swetnam, {T. L.} and Pelletier, {J. D.} and C. Rasmussen and Callahan, {N. R.} and N. Merchant and E. Lyons and M. Rynge and Y. Liu and V. Nandigam and C. Crosby",
note = "Publisher Copyright: {\textcopyright} 2016 ACM.; Conference on Diversity, Big Data, and Science at Scale, XSEDE 2016 ; Conference date: 17-07-2016 Through 21-07-2016",
year = "2016",
month = jul,
day = "17",
doi = "10.1145/2949550.2949573",
language = "English",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery",
booktitle = "Proceedings of XSEDE 2016",
}