Article

Visualizing Very Large-Scale Earthquake Simulations

Authors:

Aleksander Stompel,

Eui Joong KimAuthors Info & Claims

SC '03: Proceedings of the 2003 ACM/IEEE conference on Supercomputing

Page 48

https://doi.org/10.1145/1048935.1050198

Published: 15 November 2003 Publication History

Abstract

This paper presents a parallel adaptive rendering algorithm and its performance for visualizing time-varying unstructured volume data generated from large-scale earthquake simulations. The objective is to visualize 3D seismic wave propagation generated from a 0.5 Hz simulation of the Northridge earthquake, which is the highest resolution volume visualization of an earthquake simulation performed to date. This scalable high-fidelity visualization solution we provide to the scientists allows them to explore in the temporal, spatial, and visualization domain of their data at high resolution. This new high resolution explorability, likely not presently available to most computational science groups, will help lead to many new insights. The performance study we have conducted on a massively parallel computer operated at the Pittsburgh Supercomputing Center helps direct our design of a simulation-time visualization strategy for the higher-resolution, 1Hz and 2 Hz, simulations.

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cover image ACM Conferences

SC '03: Proceedings of the 2003 ACM/IEEE conference on Supercomputing

November 2003

859 pages

ISBN:1581136951

DOI:10.1145/1048935

General Chair:
James R. McGraw

Copyright © 2003 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 15 November 2003

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SC '03: International Conference for High Performance Computing, Networking, Storage and Analysis

November 15 - 21, 2003

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SC '03 Paper Acceptance Rate 60 of 207 submissions, 29%;

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Cited By

Chan KKwong CWongthongtham PJiang HFung CAbu-Salih BLiu ZWong TJain P(2018)Affective design using machine learning: a survey and its prospect of conjoining big dataInternational Journal of Computer Integrated Manufacturing10.1080/0951192X.2018.152641233:7(645-669)Online publication date: 4-Oct-2018
https://doi.org/10.1080/0951192X.2018.1526412
Potdar VChandan ABatool SPatel N(2018)Big Energy Data Management for Smart Grids—Issues, Challenges and Recent DevelopmentsSmart Cities10.1007/978-3-319-76669-0_8(177-205)Online publication date: 14-Apr-2018
https://doi.org/10.1007/978-3-319-76669-0_8
Tam NSong I(2016)Big Data Visualization:Information Science and Applications (ICISA) 201610.1007/978-981-10-0557-2_40(399-408)Online publication date: 16-Feb-2016
https://doi.org/10.1007/978-981-10-0557-2_40
Masuti SBarbot SKapre N(2014)Relax-Miracle: GPU parallelization of semi-analytic fourier-domain solvers for earthquake modeling2014 21st International Conference on High Performance Computing (HiPC)10.1109/HiPC.2014.7116901(1-10)Online publication date: Dec-2014
https://doi.org/10.1109/HiPC.2014.7116901
Wang JCheng LWang L(2013)Concentric layout, a new scientific data layout for matrix data-set in Hadoop file systemInternational Journal of Parallel, Emergent and Distributed Systems10.1080/17445760.2012.72098228:5(407-433)Online publication date: 1-Oct-2013
https://dl.acm.org/doi/10.1080/17445760.2012.720982
Lee S(2012)High-performance computing and visualization of earthquake simulations and ground-motion sensor network dataJournal of Applied Remote Sensing10.1117/1.JRS.6.0615016:1(061501)Online publication date: 3-Apr-2012
https://doi.org/10.1117/1.JRS.6.061501
Lipşa DLaramee RCox SRoberts JWalker RBorkin MPfister H(2012)Visualization for the Physical SciencesComputer Graphics Forum10.1111/j.1467-8659.2012.03184.x31:8(2317-2347)Online publication date: 1-Dec-2012
https://dl.acm.org/doi/10.1111/j.1467-8659.2012.03184.x
Hsieh TYang Y(2012)Visualizing the Seismic Spectral Response of the 1999 Chi-Chi Earthquake Using Volume Rendering TechniqueJournal of Computing in Civil Engineering10.1061/(ASCE)CP.1943-5487.000011226:2(225-235)Online publication date: Mar-2012
https://doi.org/10.1061/(ASCE)CP.1943-5487.0000112
Fogal TKrüger J(2011)Efficient I/O for parallel visualizationProceedings of the 11th Eurographics conference on Parallel Graphics and Visualization10.5555/2386230.2386243(81-90)Online publication date: 10-Apr-2011
https://dl.acm.org/doi/10.5555/2386230.2386243
Wu XDuan BTaylor V(2011)Parallel Earthquake Simulations on Large-Scale Multicore SupercomputersHandbook of Data Intensive Computing10.1007/978-1-4614-1415-5_21(539-562)Online publication date: 11-Nov-2011
https://doi.org/10.1007/978-1-4614-1415-5_21
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