An In-Situ Visualization Approach for the K Computer Using Mesa 3D and KVS

  • Kengo HayashiEmail author
  • Naohisa Sakamoto
  • Jorji Nonaka
  • Motohiko Matsuda
  • Fumiyoshi Shoji
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11203)


Although K computer has been operational for more than five years, it is still ranked in the top 10 of the Top500 list, and in active use, especially in Japan. One of the peculiarity of this system is the use of SPARC64fx CPU, with no instruction set compatibility with other traditional CPU architecture, and the use of a two-staged parallel file system, where the necessary data is moved from the user accessible GFS (Global File System) to a faster LFS (Local File System) for enabling high performance I/O during the simulation run. Since the users have no access to the data during the simulation run, the tightly coupled (co-processing) in-situ visualization approach seems to be the most suitable approach for this HPC system. For the visualization purposes, the hardware developer (Fujitsu) did not provide or support the traditional Mesa 3D graphics library on their SPARC64fx CPU, and in exchange, it provided a non-OSS (Open Source Software) and non-OpenGL visualization library with Particle-Based Volume Rendering (PBVR) implementation, including an API for in-situ visualization. In order to provide a more traditional in-situ visualization alternative for the K computer users, we focused on the Mesa 3D graphics library, and on an OpenGL-based KVS (Kyoto Visualization System) library. We expect that this approach can also be useful on other SPARC64fx HPC environments because of the binary compatibility.


Mesa3D graphics library SPARC64fx CPU KVS library Particle-Based Volume Rendering (PBVR) K computer 



Some of the results were obtained using the K computer at RIKEN Center for Computational Science (R-CCS) in Kobe, Japan. This work is partially supported by the “Joint Usage/Research Center for Interdisciplinary Large-scale Information Infrastructures” in Japan (Project ID: jh180060-NAH), JSPS KAKENHI Grant Number JP17K00169 and Social Implementation Program on Climate Change Adaptation Technology (SI-CAT) from the Ministry of Education, Culture, Sports, Science and Technology (MEXT) in Japan.


  1. 1.
    Ayachit, U., et al.: ParaView catalyst: enabling in situ data analysis and visualization. In: Proceedings of In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization, ISAV 2015 (2015)Google Scholar
  2. 2.
    FORUM8: HPCI Project ID (hp130034): Building of High Speed Rendering Environment by Using Photorealistic Rendering Engine.
  3. 3.
    Fujita, M., Nonaka, J., Ono, K.: LSGL: large-scale graphics library for peta-scale computing environments. In: HPG 2014: High Performance Graphics 2014 (Poster) (2014)Google Scholar
  4. 4.
    Johnson, C., Hansen, C.: Visualization Handbook. Academic Press Inc., Orlando (2004)Google Scholar
  5. 5.
    Kawamura, T., Noda, T., Idomura, Y.: In-situ visual exploration of multivariate volume data based on particle based volume rendering. In: Proceedings of the 2nd Workshop on In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization, ISAV 2016, pp. 18–22 (2016)Google Scholar
  6. 6.
    Kawamura, T., Noda, T., Idomura, Y.: Performance evaluation of runtime data exploration framework based on in-situ particle based volume rendering. Supercomput. Front. Innov. 4(3), 43–54 (2017)Google Scholar
  7. 7.
    Kitware Inc.: ParaView.
  8. 8.
    Kitware Inc.: ParaView and Mesa3D.
  9. 9.
  10. 10.
    Maruyama, T., Motokurumada, T., Morita, K., Aoki, N.: Past, present, and future of SPARC64 processors. Fujitsu Sci. Tech. J. 47(2), 130–135 (2011)Google Scholar
  11. 11.
    Mesa: Mesa 3D Graphics Library.
  12. 12.
    Miyazaki, H., Kusano, Y., Shinjou, N., Shoji, F., Yokokawa, M., Watanabe, T.: Overview of the K computer system. Fujitsu Sci. Tech. J. 48(3), 255–265 (2012)Google Scholar
  13. 13.
    Nonaka, J., et al.: A study on open source software for large-scale data visualization on SPARC64fx based HPC systems. In: Proceedings of the International Conference on High Performance Computing in Asia-Pacific Region, HPC Asia 2018, pp. 278–288. ACM, New York (2018)Google Scholar
  14. 14.
    Nonaka, J., Ono, K., Fujita, M.: 234Compositor: a flexible parallel image compositing framework for massively parallel visualization environments. Future Gener. Comput. Syst. 82, 647–655 (2018)CrossRefGoogle Scholar
  15. 15.
    Ogasa, A., Maesaka, H., Sakamoto, K., Otagiri, S.: Visualization technology for the K computer. Fujitsu Sci. Tech. J. 48(3), 348–356 (2012)Google Scholar
  16. 16.
    Onishi, K., Jansson, N., Bale, R., Wang, W.H., Li, C.G., Tsubokura, M.: A deployment of HPC algorithm into pre/post-processing for industrial CFD on K-computer. In: The International Conference for High Performance Computing, Networking, Storage and Analysis (SC 2017) Poster (2017)Google Scholar
  17. 17.
    Rowley, T.: Software Rasterizer (SWR). Intel HPC Developers Conference at SC 2014Google Scholar
  18. 18.
    Sakamoto, N., Kawamura, T., Koyamada, K.: Improvement of particle-based volume rendering for visualizing irregular volume data sets. Comput. Graph. 34(1), 34–42 (2010)CrossRefGoogle Scholar
  19. 19.
    Sakamoto, N., Koyamada, K.: Stochastic approach for integrated rendering of volumes and semi-transparent surfaces. In: SC Companion: High Performance Computing, Networking Storage and Analysis (UltraVis2012), pp. 176–185 (2012)Google Scholar
  20. 20.
    Sakamoto, N., Koyamada, K.: KVS: a simple and effective framework for scientific visualization. J. Adv. Simul. Sci. Eng. 2(1), 76–95 (2015)CrossRefGoogle Scholar
  21. 21.
    Sakamoto, N., Nonaka, J., Koyamada, K., Tanaka, S.: Particle-based volume rendering. In: Proceedings of the IEEE Asia-Pacific Symposium on Visualization, pp. 129–132 (2007)Google Scholar
  22. 22.
    Schroeder, W., Martin, K., Lorensen, B.: The Visualization Toolkit: An Object-Oriented Approach to 3D Graphics. Kitware, Inc., New York (2006)Google Scholar
  23. 23.
    Top500: Top500 supercomputer sites.
  24. 24.
    Whitlock, B., Favre, J.M., Meredith, J.S.: Parallel in situ coupling of simulation with a fully featured visualization system. In: Proceedings of the 11th Eurographics Conference on Parallel Graphics and Visualization, GPGV 2011, pp. 101–109 (2011)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Kobe UniversityKobeJapan
  2. 2.RIKEN Center for Computational ScienceKobeJapan

Personalised recommendations