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In-situ visualization for global hybrid simulations

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B. GeveciAuthors Info & Claims

XSEDE '13: Proceedings of the Conference on Extreme Science and Engineering Discovery Environment: Gateway to Discovery

Article No.: 57, Pages 1 - 8

https://doi.org/10.1145/2484762.2484822

Published: 22 July 2013 Publication History

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Abstract

Petascale simulations have become mission critical in diverse areas of science and engineering. Knowledge discovery from such simulations remains a major challenge and is becoming more urgent as the march towards ultra-scale computing with millions of cores continues. One major issue with the current paradigm of running the simulations and saving the data to disk for post-processing is that it is only feasible to save the data at a small number of time slices. This low temporal resolution of the saved data is a serious handicap in many studies where the time evolution of the system is of principle interest. One way to address this I/O issue is through in-situ visualization strategies. The idea is to minimize data storage by extracting important features of the data and saving them, rather than raw data, at high temporal resolution. Parallel file systems of current petascale and future exascale systems are expensive shared resources and need to be utilized effectively, and similarly archival storage can be limited and both of these will benefit from in-situ visualization as it will lead to intelligent way of utilizing storage. In this paper, we present preliminary results from our in-situ visualization for global hybrid (electron fluid, kinetic ions) simulations which are used to study the interaction of the solar wind with planetary magnetospheres such as the Earth and Mercury. In particular, we examine the overhead and effect on code performance associated with the inline computations associated with in-situ visualization.

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Cited By

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Karimabadi HWilkes JRoberts D(2023)The need for adoption of neural HPC (NeuHPC) in space sciencesFrontiers in Astronomy and Space Sciences10.3389/fspas.2023.112038910Online publication date: 21-Feb-2023
https://doi.org/10.3389/fspas.2023.1120389
Usman SMehmood RKatib IAlbeshri A(2022)Data Locality in High Performance Computing, Big Data, and Converged Systems: An Analysis of the Cutting Edge and a Future System ArchitectureElectronics10.3390/electronics1201005312:1(53)Online publication date: 23-Dec-2022
https://doi.org/10.3390/electronics12010053
Liu JAgrawal G(2017)Supporting Fault-Tolerance in Presence of In-Situ AnalyticsProceedings of the 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing10.5555/3101112.3101155(304-313)Online publication date: 14-May-2017
https://dl.acm.org/doi/10.5555/3101112.3101155
Show More Cited By

Index Terms

In-situ visualization for global hybrid simulations
1. Applied computing
  1. Physical sciences and engineering
    1. Physics
2. Computing methodologies
  1. Modeling and simulation
    1. Simulation types and techniques
      1. Massively parallel and high-performance simulations

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Published In

XSEDE '13: Proceedings of the Conference on Extreme Science and Engineering Discovery Environment: Gateway to Discovery

July 2013

433 pages

ISBN:9781450321709

DOI:10.1145/2484762

General Chair:
Nancy Wilkins-Diehr
San Diego Supercomputer Center

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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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 22 July 2013

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U.S. Department of Energy

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XSEDE '13

XSEDE '13: Extreme Science and Engineering Discovery Environment: Gateway to Discovery

July 22 - 25, 2013

California, San Diego, USA

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Overall Acceptance Rate 129 of 190 submissions, 68%

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Cited By

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Karimabadi HWilkes JRoberts D(2023)The need for adoption of neural HPC (NeuHPC) in space sciencesFrontiers in Astronomy and Space Sciences10.3389/fspas.2023.112038910Online publication date: 21-Feb-2023
https://doi.org/10.3389/fspas.2023.1120389
Usman SMehmood RKatib IAlbeshri A(2022)Data Locality in High Performance Computing, Big Data, and Converged Systems: An Analysis of the Cutting Edge and a Future System ArchitectureElectronics10.3390/electronics1201005312:1(53)Online publication date: 23-Dec-2022
https://doi.org/10.3390/electronics12010053
Liu JAgrawal G(2017)Supporting Fault-Tolerance in Presence of In-Situ AnalyticsProceedings of the 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing10.5555/3101112.3101155(304-313)Online publication date: 14-May-2017
https://dl.acm.org/doi/10.5555/3101112.3101155
Champsaur ALofstead JDayal JWolf MEisenhauer GWidener PGavrilovska A(2017)SmartBlock: An Approach to Standardizing In Situ Workflow Components2017 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)10.1109/IPDPSW.2017.149(1301-1308)Online publication date: May-2017
https://doi.org/10.1109/IPDPSW.2017.149
Adhinarayanan VFeng WRogers DAhrens JPakin S(2017)Characterizing and Modeling Power and Energy for Extreme-Scale In-Situ Visualization2017 IEEE International Parallel and Distributed Processing Symposium (IPDPS)10.1109/IPDPS.2017.113(978-987)Online publication date: May-2017
https://doi.org/10.1109/IPDPS.2017.113
Dimmock ANykyri KOsmane AKarimabadi HPulkkinen T(2017)Dawn‐Dusk Asymmetries of the Earth's Dayside Magnetosheath in the Magnetosheath Interplanetary Medium Reference FrameDawn‐Dusk Asymmetries in Planetary Plasma Environments10.1002/9781119216346.ch5(49-72)Online publication date: 20-Oct-2017
https://doi.org/10.1002/9781119216346.ch5
Schunk R(2016)Modeling Magnetosphere-Ionosphere Coupling via Ion OutflowMagnetosphere-Ionosphere Coupling in the Solar System10.1002/9781119066880.ch13(167-177)Online publication date: 1-Oct-2016
https://doi.org/10.1002/9781119066880.ch13
Ayachit UBauer AGeveci BO'Leary PMoreland KFabian NMauldin JWeber G(2015)ParaView CatalystProceedings of the First Workshop on In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization10.1145/2828612.2828624(25-29)Online publication date: 15-Nov-2015
https://dl.acm.org/doi/10.1145/2828612.2828624
Wang YAgrawal GBicer TJiang WKern JVetter J(2015)SmartProceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis10.1145/2807591.2807650(1-12)Online publication date: 15-Nov-2015
https://dl.acm.org/doi/10.1145/2807591.2807650
Adhinarayanan VFeng WWoodring JRogers DAhrens J(2015)On the Greenness of In-Situ and Post-Processing Visualization PipelinesProceedings of the 2015 IEEE International Parallel and Distributed Processing Symposium Workshop10.1109/IPDPSW.2015.132(880-887)Online publication date: 25-May-2015
https://dl.acm.org/doi/10.1109/IPDPSW.2015.132
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