Skip to main content

In Situ Analysis and Visualization of Fusion Simulations: Lessons Learned

Part of the Lecture Notes in Computer Science book series (LNTCS,volume 11203)

Abstract

The trends in high performance computing, where far more data can be computed that can ever be stored, have made in situ techniques an important area of research and development. Simulation campaigns, where domain scientists work with computer scientists to run a simulation and perform in situ analysis and visualization are important, and complex undertakings. In this paper we report our experiences performing in situ analysis and visualization on two campaigns. The two campaigns were related, but had important differences in terms of the codes that were used, the types of analysis and visualization required, and the visualization tools used. Further, we report the lessons learned from each campaign.

Keywords

  • In situ
  • Scientific
  • Visualization

This is a preview of subscription content, access via your institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-3-030-02465-9_16
  • Chapter length: 13 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
USD   89.00
Price excludes VAT (USA)
  • ISBN: 978-3-030-02465-9
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD   119.99
Price excludes VAT (USA)
Fig. 1.
Fig. 2.
Fig. 3.
Fig. 4.
Fig. 5.
Fig. 6.

References

  1. Ahrens, J., Geveci, B., Law, C.: Visualization in the paraview framework. In: Hansen, C., Johnson, C. (eds.) The Visualization Handbook, pp. 162–170 (2005)

    Google Scholar 

  2. Ainsworth, M., Tugluk, O., Whitney, B., Klasky, S.: MGARD: a multilevel technique for compression of floating-point data. In: DRBSD-2 Workshop at Supercomputing 2017, Colorado, USA (2017)

    Google Scholar 

  3. Ainsworth, M., Tugluk, O., Whitney, B., Klasky, S.: Multilevel techniques for compression and reduction of scientific data-the univariate case. Comput. Vis. Sci. (2017, submitted)

    Google Scholar 

  4. Ayachit, U., et al.: The SENSEI generic in situ interface. In: 2016 Second Workshop on In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization (ISAV), pp. 40–44, November 2016. https://doi.org/10.1109/ISAV.2016.013

  5. Ayachit, U., et al.: ParaView catalyst: enabling in situ data analysis and visualization. In: Proceedings of the First Workshop on In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization, pp. 25–29. ACM (2015)

    Google Scholar 

  6. Bauer, A.C., et al.: In situ methods, infrastructures, and applications on high performance computing platforms, a state-of-the-art (STAR) report. In: Computer Graphics Forum, Proceedings of EuroVis 2016, vol. 35, no. 3, June 2016. LBNL-1005709

    Google Scholar 

  7. Bennett, J.C., et al.: Combining in-situ and in-transit processing to enable extreme-scale scientific analysis. In: Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis, SC 2012, pp. 49:1–49:9. IEEE Computer Society Press, Los Alamitos (2012). http://dl.acm.org/citation.cfm?id=2388996.2389063

  8. Chang, C., et al.: Compressed ion temperature gradient turbulence in diverted tokamak edgea. Phys. Plasmas (1994-present) 16(5), 056108 (2009)

    CrossRef  Google Scholar 

  9. Childs, H., et al.: VisIt: an end-user tool for visualizing and analyzing very large data. In: High Performance Visualization-Enabling Extreme-Scale Scientific Insight, pp. 357–372, October 2012

    Google Scholar 

  10. Dayal, J., et al.: Flexpath: type-based publish/subscribe system for large-scale science analytics. In: 2014 14th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid), pp. 246–255. IEEE (2014)

    Google Scholar 

  11. Di, S., Cappello, F.: Fast error-bounded lossy HPC data compression with SZ. In: 2016 IEEE International Parallel and Distributed Processing Symposium, IPDPS 2016, Chicago, IL, USA, 23–27 May 2016, pp. 730–739 (2016)

    Google Scholar 

  12. Docan, C., Parashar, M., Klasky, S.: Dataspaces: an interaction and coordination framework for coupled simulation workflows. Cluster Comput. 15(2), 163–181 (2012)

    CrossRef  Google Scholar 

  13. Dominski, J., et al.: A tight-coupling scheme sharing minimum information across a spatial interface between gyrokinetic turbulence codes. Phys. Plasmas 25(7), 072308 (2018). https://doi.org/10.1063/1.5044707

    CrossRef  Google Scholar 

  14. Dominski, J., Merlo, G., et al.: Gyrokinetic core-edge coupling of the continuum code GENE with the particle-in-cell code XGC (temporary title). (in preparation)

    Google Scholar 

  15. Foster, I., et al.: Computing just what you need: online data analysis and reduction at extreme scales. In: Rivera, F.F., Pena, T.F., Cabaleiro, J.C. (eds.) Euro-Par 2017. LNCS, vol. 10417, pp. 3–19. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-64203-1_1

    CrossRef  Google Scholar 

  16. Görler, T., et al.: The global version of the gyrokinetic turbulence code gene. J. Comput. Phys. 230(18), 7053–7071 (2011). https://doi.org/10.1016/j.jcp.2011.05.034. http://www.sciencedirect.com/science/article/pii/S0021999111003457

    MathSciNet  CrossRef  MATH  Google Scholar 

  17. Liu, Q., et al.: Hello ADIOS: the challenges and lessons of developing leadership class I/O frameworks. Concurrency Comput.: Pract. Exp. 26(7), 1453–1473 (2014). https://doi.org/10.1002/cpe.3125

    CrossRef  Google Scholar 

  18. Moreland, K., et al.: VTK-m: accelerating the visualization toolkit for massively threaded architectures. IEEE Comput. Graph. Appl. 36(3), 48–58 (2016)

    CrossRef  Google Scholar 

  19. Parker, S.G., Johnson, C.R.: SCIRun: a scientific programming environment for computational steering. In: Proceedings of the 1995 ACM/IEEE Conference on Supercomputing, p. 52. ACM (1995)

    Google Scholar 

  20. Shende, S.S., Malony, A.D.: The tau parallel performance system. Int. J. High Perform. Comput. Appl. 20(2), 287–311 (2006)

    CrossRef  Google Scholar 

  21. Tao, D., Di, S., Guo, H., Chen, Z., Cappello, F.: Z-checker: a framework for assessing lossy compression of scientific data. Int. J. High Perform. Comput. Appl. 1094342017737147 (2017). https://doi.org/10.1177/1094342017737147

  22. Tchoua, R., et al.: ADIOS visualization schema: a first step towards improving interdisciplinary collaboration in high performance computing. In: 2013 IEEE 9th International Conference on e-Science, pp. 27–34, October 2013. https://doi.org/10.1109/eScience.2013.24

  23. Whitlock, B., Favre, J., Meredith, J.: Parallel in situ coupling of simulation with a fully featured visualization system. In: Proceedings of the 11th Eurographics Conference on Parallel Graphics and Visualization, pp. 101–109 (2011)

    Google Scholar 

  24. Zhang, F., et al.: In-memory staging and data-centric task placement for coupled scientific simulation workflows. Concurrency Comput.: Pract. Exp. 29(12), e4147 (2017)

    CrossRef  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Mark Kim .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 2018 Springer Nature Switzerland AG

About this paper

Verify currency and authenticity via CrossMark

Cite this paper

Kim, M. et al. (2018). In Situ Analysis and Visualization of Fusion Simulations: Lessons Learned. In: Yokota, R., Weiland, M., Shalf, J., Alam, S. (eds) High Performance Computing. ISC High Performance 2018. Lecture Notes in Computer Science(), vol 11203. Springer, Cham. https://doi.org/10.1007/978-3-030-02465-9_16

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-02465-9_16

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-02464-2

  • Online ISBN: 978-3-030-02465-9

  • eBook Packages: Computer ScienceComputer Science (R0)