Skip to main content
SpringerLink
Log in
Book cover

In Situ Visualization for Computational Science pp 255–279Cite as

Ascent: A Flyweight In Situ Library for Exascale Simulations

  • Conference paper
  • First Online:

Part of the book series: Mathematics and Visualization ((MATHVISUAL))

Abstract

This chapter describes Ascent, a production library for in situ visualization and analysis on exascale architectures. It begins by describing the library’s focal points: minimizing encumbrance on simulation codes and enabling diverse and powerful capabilities. The chapter then describes Ascent’s abstractions, interface, and design. It concludes with success stories that highlight its capabilities: in situ visualization of a 97.8 billion element inertial confinement fusion simulation using 16,384 GPUs, delivering radiography capabilities for a Kelvin-Helmholtz simulation, and native rendering of higher-order elements.

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

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   99.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   129.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   199.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Devil ray: A high-order element ray tracer. https://github.com/LLNL/devil_ray/. Accessed: 2020-1-31

  2. extensible data model and format, http://www.xdmf.org

  3. Mfem: Finite element discretization library. https://github.com/mfem/mfem/. Accessed: 2020-1-30

  4. MFEM: Modular finite element methods (2017), http://mfem.org

  5. Agranovsky, A., Camp, D., Garth, C., Bethel, E.W., Joy, K.I., Childs, H.: Improved Post Hoc Flow Analysis via Lagrangian Representations. In: Proceedings of the IEEE Symposium on Large Data Visualization and Analysis (LDAV), pp. 67–75. Paris, France (2014)

    Google Scholar 

  6. Ahrens, J., et al.: An image-based approach to extreme scale in situ visualization and analysis. In: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, pp. 424–434. SC ’14. IEEE Press, Piscataway, NJ, USA (2014). https://doi.org/10.1109/SC.2014.40

  7. Alexander, F., Almgren, A., Bell, J., Bhattacharjee, A., Chen, J., Colella, P., Daniel, D., DeSlippe, J., Diachin, L., Draeger, E., et al.: Exascale applications: skin in the game. Philos. Trans. R. Soc. A 378(2166), 20190056 (2020)

    Article  MathSciNet  Google Scholar 

  8. 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 

  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. CRC Press/Francis–Taylor Group (2012)

    Google Scholar 

  10. Dorier, M., Sisneros, R., Peterka, T., Antoniu, G., Semeraro, D.: Damaris/viz: A nonintrusive, adaptable and user-friendly in situ visualization framework. In: 2013 IEEE Symposium on Large-Scale Data Analysis and Visualization (LDAV), pp. 67–75 (2013). https://doi.org/10.1109/LDAV.2013.6675160

  11. Harrison, C., Navratil, P., Moussalem, M., Jiang, M., Childs, H.: Efficient dynamic derived field generation on many-core architectures using python. In: Proceedings of the 2012 SC Companion: High Performance Computing, Networking Storage and Analysis. p. 583–592. SCC ’12, IEEE Computer Society, USA (2012). https://doi.org/10.1109/SC.Companion.2012.82

  12. Hurricane, O., Hansen, J., Robey, H., Remington, B., Bono, M., Harding, E., Drake, R., Kuranz, C.: A high energy density shock driven kelvin-helmholtz shear layer experiment. Phys. Plasmas 16(5), 056305 (2009)

    Google Scholar 

  13. Ibrahim, S., Stitt, T., Larsen, M., Harrison, C.: Interactive in situ visualization and analysis using ascent and jupyter. In: Proceedings of the Workshop on In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization, pp. 44–48. ISAV ’19, Association for Computing Machinery, New York, NY, USA (2019). https://doi.org/10.1145/3364228.3364232

  14. Kluyver, T., Ragan-Kelley, B., Pérez, F., Granger, B., Bussonnier, M., Frederic, J., Kelley, K., Hamrick, J., Grout, J., Corlay, S., Ivanov, P., Avila, D., Abdalla, S., Willing, C.: Jupyter notebooks - a publishing format for reproducible computational workflows. In: Loizides, F., Schmidt, B. (eds.) Positioning and Power in Academic Publishing: Players, Agents and Agendas, pp. 87–90. IOS Press (2016). https://doi.org/10.3233/978-1-61499-649-1-87

  15. Laboratory, L.L.N.: Conduit: Simplified data exchange for hpc simulations (2017., https://llnl-conduit.readthedocs.io

  16. Laboratory, L.L.N.: Conduit: Simplified data exchange for hpc simulations - conduit blueprint (2017). https://llnl-conduit.readthedocs.io/en/latest/blueprint.html

  17. Larsen, M., Woods, A., Marsaglia, N., Biswas, A., Dutta, S., Harrison, C., Childs, H.: A Flexible System for In Situ Triggers. In: Proceedings of the Workshop on In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization (ISAV), pp. 1–6. Dallas, TX (2018)

    Google Scholar 

  18. Larsen, M., et al.: The alpine in situ infrastructure: Ascending from the ashes of strawman. In: Proceedings of the In Situ Infrastructures on Enabling Extreme-Scale Analysis and Visualization, pp. 42–46. ISAV’17, ACM, New York, NY, USA (2017). https://doi.org/10.1145/3144769.3144778

  19. Lofstead, J.F., Klasky, S., Schwan, K., Podhorszki, N., Jin, C.: Flexible io and integration for scientific codes through the adaptable io system (adios). In: Proceedings of the 6th International Workshop on Challenges of Large Applications in Distributed Environments, pp. 15–24. CLADE ’08, ACM, New York, NY, USA (2008). https://doi.org/10.1145/1383529.1383533

  20. Meredith, J.S., Ahern, S., Pugmire, D., Sisneros, R.: EAVL: The Extreme-scale Analysis and Visualization Library. In: Eurographics Symposium on Parallel Graphics and Visualization. The Eurographics Association (2012)

    Google Scholar 

  21. Moreland, K., et al.: VTK-m: Accelerating the visualization toolkit for massively threaded architectures. IEEE Comput. Gr. Appl. (CG&A) 36(3), 48–58 (2016)

    Google Scholar 

  22. Petruzza, S., Treichler, S., Pascucci, V., Bremer, P.T.: Babelflow: An embedded domain specific language for parallel analysis and visualization. In: 2018 IEEE International Parallel and Distributed Processing Symposium (IPDPS), pp. 463–473. IEEE (2018)

    Google Scholar 

  23. Sane, S., Childs, H., Bujack, R.: An Interpolation Scheme for VDVP Lagrangian Basis Flows. In: Eurographics Symposium on Parallel Graphics and Visualization (EGPGV), pp. 109–118. Porto, Portugal (2019)

    Google Scholar 

  24. Schroeder, W.J., Martin, K.M., Lorensen, W.E.: The design and implementation of an object-oriented toolkit for 3d graphics and visualization. In: Proceedings of Seventh Annual IEEE Visualization ’96, pp. 93–100 (1996)

    Google Scholar 

Download references

Acknowledgements

This research was supported by the Exascale Computing Project (17-SC-20-SC), a collaborative effort of the U.S. Department of Energy Office of Science and the National Nuclear Security Administration. This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344 (LLNL-BOOK-814190).

Author information

Authors and Affiliations

  1. Lawrence Livermore National Laboratory, Livermore, CA, USA

    Matthew Larsen, Eric Brugger & Cyrus Harrison

  2. University of Oregon, Eugene, OR, USA

    Hank Childs

Authors
  1. Matthew Larsen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Eric Brugger
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Hank Childs
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Cyrus Harrison
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Matthew Larsen .

Editor information

Editors and Affiliations

  1. Computer and Information Science, University of Oregon, Eugene, OR, USA

    Hank Childs

  2. Extreme-Scale Data Science and Analytics, Sandia National Laboratories, Livermore, CA, USA

    Janine C. Bennett

  3. Scientific Visualization Lab, University of Kaiserslautern, Kaiserslautern, Germany

    Christoph Garth

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Larsen, M., Brugger, E., Childs, H., Harrison, C. (2022). Ascent: A Flyweight In Situ Library for Exascale Simulations. In: Childs, H., Bennett, J.C., Garth, C. (eds) In Situ Visualization for Computational Science. Mathematics and Visualization. Springer, Cham. https://doi.org/10.1007/978-3-030-81627-8_12

Download citation

Publish with us

Policies and ethics

Search

Navigation