Skip to main content

In Situ Visualization of WRF Data Using Universal Data Junction

  • Conference paper
  • First Online:
High Performance Computing (ISC High Performance 2021)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12761))

Included in the following conference series:

Abstract

An in situ co-processing visualization pipeline based on the Universal Data Junction (UDJ) library and Inshimtu is presented and used for processing data from Weather Research and Forecasting (WRF) simulations. For the common case of analyzing just a number of fields during simulation, UDJ transfers and redistributes the data in approximately \(6\%\) of the time needed by WRF for a MPI-IO output of all variables upon which a previous method with Inshimtu is based. The relative cost of transport and redistribution compared to IO remains approximately constant up to the highest considered node count without obvious impediments to scale further.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Ayachit, U., et al.: Paraview catalyst: enabling in situ data analysis and visualization. In: ISAV2015: Proceedings of the First Workshop on In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization, vol. 1, no. (1), pp. 25–29, November 2015. https://doi.org/10.1145/2828612.2828624. https://dl.acm.org/doi/10.1145/2828612.2828624

  2. Bauer, A.C., et al.: In situ methods, infrastructures, and applications on high performance computing platforms. Comput. Graph. Forum 35(3), 577–597 (2016)

    Article  Google Scholar 

  3. Boyuka, D.A., et al.: Transparent in situ data transformations in adios. In: Proceedings of the 14th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing, CCGRID 2014, pp. 256–266. IEEE Press (2014). https://doi.org/10.1109/CCGrid.2014.73

  4. Godoy, W.F., et al.: ADIOS 2: the adaptable input output system. A framework for high-performance data management. SoftwareX 12, 100561 (2020). https://doi.org/10.1016/j.softx.2020.100561. https://www.sciencedirect.com/science/article/pii/S2352711019302560

  5. Holst, G., Dasari, H.P., Markomanolis, G., Hoteit, I., Theussl, T.: Inshimtu - a lightweight in-situ visualization “shim” (2017). https://woiv.gitlab.io/woiv17/ISC_WOIV_Holst.pdf

  6. Loring, B., et al.: Improving performance of m-to-n processing and data redistribution in in transit analysis and visualization. Technical report, Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States) (2020)

    Google Scholar 

  7. Moreland, K.: The tensions of in situ visualization. IEEE Comput. Graphics Appl. 36(2), 5–9 (2016). https://doi.org/10.1109/MCG.2016.35

    Article  Google Scholar 

  8. Skamarock, W.C., et al.: A description of the advanced research WRF version 3. National Center for Atmospheric Research: Boulder, CO, USA, June 2008. https://doi.org/10.5065/D68S4MVH

  9. Skamarock, W.C., et al.: A description of the advanced research WRF model version 4. National Center for Atmospheric Research: Boulder, CO, USA, p. 145 (2019). https://doi.org/10.5065/1dfh-6p97

Download references

Acknowledgment

This work is part of the HPE/Cray center of excellence collaboration at KAUST. UDJ development has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 773897. We want to thank Hari Dasari colleagues for helping with the test case as well as Tim Dykes and Utz Uwe Haus from the HPE EMEA research lab for support with UDJ.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Aniello Esposito .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Esposito, A., Holst, G. (2021). In Situ Visualization of WRF Data Using Universal Data Junction. In: Jagode, H., Anzt, H., Ltaief, H., Luszczek, P. (eds) High Performance Computing. ISC High Performance 2021. Lecture Notes in Computer Science(), vol 12761. Springer, Cham. https://doi.org/10.1007/978-3-030-90539-2_32

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-90539-2_32

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-90538-5

  • Online ISBN: 978-3-030-90539-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics