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Performance Portability of Earth System Models with User-Controlled GGDML Code Translation

  • Nabeeh Jum’ahEmail author
  • Julian Kunkel
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11203)

Abstract

The increasing need for performance of earth system modeling and other scientific domains pushes the computing technologies in diverse architectural directions. The development of models needs technical expertise and skills of using tools that are able to exploit the hardware capabilities. The heterogeneity of architectures complicates the development and the maintainability of the models.

To improve the software development process of earth system models, we provide an approach that simplifies the code maintainability by fostering separation of concerns while providing performance portability. We propose the use of high-level language extensions that reflect scientific concepts. The scientists can use the programming language of their own choice to develop models, however, they can use the language extensions optionally wherever they need. The code translation is driven by configurations that are separated from the model source code. These configurations are prepared by scientific programmers to optimally use the machine’s features.

The main contribution of this paper is the demonstration of a user-controlled source-to-source translation technique of earth system models that are written with higher-level semantics. We discuss a flexible code translation technique that is driven by the users through a configuration input that is prepared especially to transform the code, and we use this technique to produce OpenMP or OpenACC enabled codes besides MPI to support multi-node configurations.

Keywords

DSL Meta-Compiler Earth system modeling Software development Performance portability 

Notes

Acknowledgements

This work was supported in part by the German Research Foundation (DFG) through the Priority Programme 1648 “Software for Exascale Computing” (SPPEXA) (GZ: LU 1353/11-1). We would like to thank NVIDIA who supported this work with allowing to run some tests on their PSG cluster, and the German Climate Computing-Center (DKRZ) where we also have run some tests on the Mistral supercomputer.

References

  1. 1.
  2. 2.
  3. 3.
    van Engelen, R.A.: Atmol: a domain-specific language for atmospheric modeling. CIT. J. Comput. Inf. Technol. 9(4), 289–303 (2001)CrossRefGoogle Scholar
  4. 4.
    DeVito, Z., et al.: Liszt: a domain specific language for building portable mesh-based PDE solvers. In: Proceedings of 2011 International Conference for High Performance Computing, Networking, Storage and Analysis, p. 9. ACM (2011)Google Scholar
  5. 5.
    Dolbeau, R., Bihan, S., Bodin, F.: HMPP: a hybrid multi-core parallel programming environment. In: Workshop on General Purpose Processing on Graphics Processing Units (GPGPU 2007), vol. 28 (2007)Google Scholar
  6. 6.
    Dongarra, J.J., Croz, J.D., Hammarling, S., Duff, I.S.: A set of level 3 basic linear algebra subprograms. ACM Trans. Math. Softw. (TOMS) 16(1), 1–17 (1990)MathSciNetCrossRefGoogle Scholar
  7. 7.
    Ford, R., et al.: Gung Ho: a code design for weather and climate prediction on exascale machines. In: Proceedings of the Exascale Applications and Software Conference (2013)Google Scholar
  8. 8.
    Gysi, T., Fuhrer, O., Osuna, C., Cumming, B., Schulthess, T.: Stella: a domain-specific embedded language for stencil codes on structured grids. In: EGU General Assembly Conference Abstracts, vol. 16 (2014)Google Scholar
  9. 9.
    MKL Intel. Intel Math Kernel Library (2007)Google Scholar
  10. 10.
    Jumah, N., Kunkel, J., Zängl, G., Yashiro, H., Dubos, T., Meurdesoif, Y.: GGDML: icosahedral models language extensions. J. Comput. Sci. Technol. Updates 4(1), 1–10 (2017)CrossRefGoogle Scholar
  11. 11.
    Maruyama, N., Sato, K., Nomura, T., Matsuoka, S.: Physis: an implicitly parallel programming model for stencil computations on large-scale GPU-accelerated supercomputers. In: 2011 International Conference for High Performance Computing, Networking, Storage and Analysis (SC), pp. 1–12. IEEE (2011)Google Scholar
  12. 12.
    Mudalige, G.R., Giles, M.B., Reguly, I., Bertolli, C., Kelly, P.H.J.: Op2: an active library framework for solving unstructured mesh-based applications on multi-core and many-core architectures. In: Innovative Parallel Computing (InPar), pp. 1–12. IEEE (2012)Google Scholar
  13. 13.
    Müller, M., Aoki, T.: Hybrid Fortran: high productivity GPU porting framework applied to Japanese weather prediction model. arXiv preprint arXiv:1710.08616 (2017)
  14. 14.
    Reguly, I.Z., Mudalige, G.R., Giles, M.B., Curran, D., McIntosh-Smith, S.: The OPS domain specific abstraction for multi-block structured grid computations. In: 2014 Fourth International Workshop on Domain-Specific Languages and High-Level Frameworks for High Performance Computing (WOLFHPC), pp. 58–67. IEEE (2014)Google Scholar
  15. 15.
    Rice, J.R., Boisvert, R.F.: Solving Elliptic Problems Using ELLPACK, vol. 2. Springer, New York (2012).  https://doi.org/10.1007/978-1-4612-5018-0CrossRefzbMATHGoogle Scholar
  16. 16.
    Torres, R., Linardakis, L., Kunkel, T.L.J., Ludwig, T.: ICON DSL: a domain-specific language for climate modeling. In: International Conference for High Performance Computing, Networking, Storage and Analysis, Denver, Colo (2013). http://sc13.supercomputing.org/sites/default/files/WorkshopsArchive/track139.html
  17. 17.
    Unat, D., Cai, X., Baden, S.B.: Mint: realizing CUDA performance in 3D stencil methods with annotated C. In: Proceedings of the International Conference on Supercomputing, pp. 214–224. ACM (2011)Google Scholar
  18. 18.
    Wang, L., Wu, W., Xu, Z., Xiao, J., Yang, Y.: BLASX: a high performance level-3 BLAS library for heterogeneous multi-GPU computing. In: Proceedings of the 2016 International Conference on Supercomputing, p. 20. ACM (2016)Google Scholar
  19. 19.
    Yount, C.: Vector folding: improving stencil performance via multi-dimensional SIMD-vector representation. In: 2015 IEEE 17th International Conference on High Performance Computing and Communications (HPCC), 2015 IEEE 7th International Symposium on Cyberspace Safety and Security (CSS), 2015 IEEE 12th International Conferen on Embedded Software and Systems (ICESS), pp. 865–870. IEEE (2015)Google Scholar
  20. 20.
    Yount, C.: Recipe: building and running YASK (yet another stencil kernel) on Intel® processors (2016). https://software.intel.com/en-us/articles/recipe-building-and-running-yask-yet-another-stencil-kernel-on-intel-processors. Accessed 22 Dec 2017

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Universität HamburgHamburgGermany
  2. 2.University of ReadingReadingUK

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