Accelerating TauDEM for extracting hydrology information from national-scale high resolution topographic dataset

Ahmet Artu Yildirim; David Tarboton; Yan Liu; Nazmus Shams Sazib; Shaowen Wang

doi:10.1145/2949550.2949582

Accelerating TauDEM for extracting hydrology information from national-scale high resolution topographic dataset

Ahmet Artu Yildirim, David Tarboton, Yan Liu, Nazmus Shams Sazib, Shaowen Wang

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

We present performance improvements on parallel hydrology algorithms in TauDEM suite that allowed us to process the 10m USGS 3DEP topographic dataset (667GB, 180 billion raster cells) by adopting a block-wise data decomposition feature and maximazing the disk parallelism.

Original language	English
Title of host publication	Proceedings of XSEDE 2016
Subtitle of host publication	Diversity, Big Data, and Science at Scale
Publisher	Association for Computing Machinery
ISBN (Electronic)	9781450347556
DOIs	https://doi.org/10.1145/2949550.2949582
State	Published - Jul 17 2016
Externally published	Yes
Event	Conference on Diversity, Big Data, and Science at Scale, XSEDE 2016 - Miami, United States Duration: Jul 17 2016 → Jul 21 2016

Publication series

Name	ACM International Conference Proceeding Series
Volume	17-21-July-2016

Conference

Conference	Conference on Diversity, Big Data, and Science at Scale, XSEDE 2016
Country/Territory	United States
City	Miami
Period	07/17/16 → 07/21/16

Keywords

HPC
Parallel pitremove algorithm
TauDEM

Access to Document

10.1145/2949550.2949582

Cite this

Yildirim, A. A., Tarboton, D., Liu, Y., Sazib, N. S., & Wang, S. (2016). Accelerating TauDEM for extracting hydrology information from national-scale high resolution topographic dataset. In Proceedings of XSEDE 2016: Diversity, Big Data, and Science at Scale Article a3 (ACM International Conference Proceeding Series; Vol. 17-21-July-2016). Association for Computing Machinery. https://doi.org/10.1145/2949550.2949582

@inproceedings{78d6a5c61c174c0fbb622726093b25a0,

title = "Accelerating TauDEM for extracting hydrology information from national-scale high resolution topographic dataset",

abstract = "We present performance improvements on parallel hydrology algorithms in TauDEM suite that allowed us to process the 10m USGS 3DEP topographic dataset (667GB, 180 billion raster cells) by adopting a block-wise data decomposition feature and maximazing the disk parallelism.",

keywords = "HPC, Parallel pitremove algorithm, TauDEM",

author = "Yildirim, {Ahmet Artu} and David Tarboton and Yan Liu and Sazib, {Nazmus Shams} and Shaowen Wang",

year = "2016",

month = jul,

day = "17",

doi = "10.1145/2949550.2949582",

language = "English",

series = "ACM International Conference Proceeding Series",

publisher = "Association for Computing Machinery",

booktitle = "Proceedings of XSEDE 2016",

note = "Conference on Diversity, Big Data, and Science at Scale, XSEDE 2016 ; Conference date: 17-07-2016 Through 21-07-2016",

}

Yildirim, AA, Tarboton, D, Liu, Y, Sazib, NS & Wang, S 2016, Accelerating TauDEM for extracting hydrology information from national-scale high resolution topographic dataset. in Proceedings of XSEDE 2016: Diversity, Big Data, and Science at Scale., a3, ACM International Conference Proceeding Series, vol. 17-21-July-2016, Association for Computing Machinery, Conference on Diversity, Big Data, and Science at Scale, XSEDE 2016, Miami, United States, 07/17/16. https://doi.org/10.1145/2949550.2949582

Accelerating TauDEM for extracting hydrology information from national-scale high resolution topographic dataset. / Yildirim, Ahmet Artu; Tarboton, David; Liu, Yan et al.
Proceedings of XSEDE 2016: Diversity, Big Data, and Science at Scale. Association for Computing Machinery, 2016. a3 (ACM International Conference Proceeding Series; Vol. 17-21-July-2016).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Accelerating TauDEM for extracting hydrology information from national-scale high resolution topographic dataset

AU - Yildirim, Ahmet Artu

AU - Tarboton, David

AU - Liu, Yan

AU - Sazib, Nazmus Shams

AU - Wang, Shaowen

PY - 2016/7/17

Y1 - 2016/7/17

N2 - We present performance improvements on parallel hydrology algorithms in TauDEM suite that allowed us to process the 10m USGS 3DEP topographic dataset (667GB, 180 billion raster cells) by adopting a block-wise data decomposition feature and maximazing the disk parallelism.

AB - We present performance improvements on parallel hydrology algorithms in TauDEM suite that allowed us to process the 10m USGS 3DEP topographic dataset (667GB, 180 billion raster cells) by adopting a block-wise data decomposition feature and maximazing the disk parallelism.

KW - HPC

KW - Parallel pitremove algorithm

KW - TauDEM

UR - http://www.scopus.com/inward/record.url?scp=84989195916&partnerID=8YFLogxK

U2 - 10.1145/2949550.2949582

DO - 10.1145/2949550.2949582

M3 - Conference contribution

AN - SCOPUS:84989195916

T3 - ACM International Conference Proceeding Series

BT - Proceedings of XSEDE 2016

PB - Association for Computing Machinery

T2 - Conference on Diversity, Big Data, and Science at Scale, XSEDE 2016

Y2 - 17 July 2016 through 21 July 2016

ER -

Accelerating TauDEM for extracting hydrology information from national-scale high resolution topographic dataset

Abstract

Publication series

Conference

Keywords

Access to Document

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