Towards a performance portable, architecture agnostic implementation strategy for weather and climate models

Supercomputing Frontiers and Innovations

Volumn 1, Issue 1, 2014, Pages 44-61

  Fuhrer, Oliver ^a   Osuna, Carlos ^b   Lapillonne, Xavier ^b   Gysi, Tobias ^b,c   Cumming, Ben ^b   Bianco, Mauro ^b   Arteaga, Andrea ^b   Schulthess, Thomas C ^b,d  

^a FEDERAL OFFICE OF METEOROLOGY AND CLIMATOLOGY METEOSWISS   (Switzerland)

^b ETH ZURICH   (Switzerland)

^c Supercomputing Systems AG   (Switzerland)

^d OAK RIDGE NATIONAL LABORATORY   (United States)

Author keywords

Climate modeling; Hybrid computing; Numerical weather prediction; Programming models

Indexed keywords

C++ (PROGRAMMING LANGUAGE); CLIMATOLOGY; CODES (SYMBOLS); DISTRIBUTED COMPUTER SYSTEMS; ELECTRONIC DATA INTERCHANGE; FORTRAN (PROGRAMMING LANGUAGE); MEMORY ARCHITECTURE; WEATHER FORECASTING;

DISTRIBUTED MEMORY SYSTEMS; HYBRID COMPUTING; IMPLEMENTATION STRATEGIES; NUMERICAL WEATHER PREDICTION; PROGRAMMING MODELS; SOFTWARE IMPLEMENTATION; TEMPLATE METAPROGRAMMING; WEATHER AND CLIMATE MODELS;

CLIMATE MODELS;

EID: 85038359780     PISSN: 24096008     EISSN: 23138734     Source Type: Journal    
DOI: 10.14529/jsfi140103     Document Type: Article

References (35)

1. I. Abrahams and A. Gurtovoy. C++ Template Metaprogramming: Concepts, Tools, And Techniques From Boost And Beyond. The C++ in-Depth Series. Addison Wesley Professional, 2005
2. A. Alexandrescu. Modern C++ Design: Generic Programming and Design Patterns Applied. Addison-Wesley Longman Publishing Co., Inc., Boston, MA, USA, 2001
3. M. Baldauf. Stability analysis for linear discretisations of the advection equation with runge-kutta time integration. Journal of Computational Physics, 227(13):6638-6659, 2008
4. M. Baldauf, A. Seifert, J. Förstner, D. Majewski, and M. Raschendorfer. Operational convective-scale numerical weather prediction with the cosmo model: Description and sensitivities. Monthly Weather Review, 139:3387-3905, 2011
5. M. Bianco. An interface for halo exchange pattern, 2012
6. F. Cappelo and D. Etiemble. MPI versus MPI+OpenMP on the IBM SP for the NAS benchmarks. In Proceedings of 2000 International Conference for High Performance Computing, Networking, Storage and Analysis, SC'00. ACM/IEEE International Conference for High Performance Computing, Networking, Storage, and Analysis (SC), 2000
7. CAPS. CAPS the many core company, 2014. http://www.caps-entreprise.com/
8. Climate Limited-area Modelling Community. http://www.clm-community.eu/
9. Consortium for Small-Scale Modeling. http://www.cosmo-model.org/
10. Cray Inc. Cray Fortran Reference Manual, 2014. http://docs.cray.com/books/S-3901-82/S-3901-82.pdf
11. M. J. Djomehri and H. H. Jin. Hybrid MPI+OpenMP programming of an overset CFD solver and performance investigations. NASA/NAS Technical Report NAS-02-002, NASA Ames Research Center, 2002
12. G. Doms and U. Schättler. The nonhydrostatic limited-area model LM (lokal-model) of the DWD. Part I: Scientific documentation. Technical report, German Weather Service (DWD), Offenbach, Germany, 1999
13. M. Govett. F2C-ACC Users Guide, Version 4.2, 2012. http://www.esrl.noaa.gov/gsd/ab/ac/Accelerators.html
14. M. Govett, L. Hart, T. Henderson, J. Middlecoff, and D. Schaffer. The scalable modeling system: directive-based code parallelization for distributed and shared memory computers. Parallel Computing, 29(8):995-1020, 2003
15. M. Govett, J. Middlecoff, and T. Henderson. Running the NIM next-generation weather model on gpus. In Proceedings 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing (CCGrid), pages 792-796, 2010
16. T. Gysi, O. Fuhrer, C. Osuna, M. Bianco, and T. Schulthess. Stella: A domain-specific language and tool for structured grid methods. submitted
17. T. Henderson, J. Middlecoff, J. Rosinski, M. Govett, and P. Madden. Experience applying fortran GPU compilers to numerical weather prediction. In Proceedings of the 2011 Symposium on Application Accelerators in High-Performance Computing (SAAHPC 2011), pages 34-41, 2011
18. Jenkins CI. Jenkins the continuous integration tool, 2014. http://jenkins-ci.org/
19. H. Jin, H. Jin, M. Frumkin, M. Frumkin, J. Yan, and J. Yan. The OpenMP implementation of NAS parallel benchmarks and its performance. Technical report, 1999
20. W. Langhans, J. Schmidli, O. Fuhrer, S. Bieri, and C. Schär. Long-term simulations of thermally driven flows and orographic convection at convection-parameterizing and cloudresolving resolutions. Journal of Applied Meteorology and Climatology, 52:1490-1510, 2013
21. X. Lapillonne and O. Fuhrer. Using compiler directives to port large scientific applications to GPUs: An example from atmospheric science. Parallel Processing Letters, 24(1):1450003, 2014
22. J. K. Lazo, J. S. Rice, and M. L. Hagenstad. Benefits of investing in a supercomputer to support weather forecasting research: An example of benefit cost analysis. Yuejiang Academic Journal, 1:1-22, 2010
23. Mellanox. Nvidia gpudirect technology-accelerating gpu-based systems. http://www. mellanox.com/pdf/whitepapers/TB_GPU_Direct.pdf
24. M. Norman, J. Larkin, R. Archibald, V. Anantharaj, I. Carpenter, P. Micikevicius, and K. Evans. Porting the spectral element community atmosphere model (CAM-SE) to hybrid gpu platforms. In 2012 SC COMPANION: HIGH PERFORMANCE COMPUTING, NETWORKING, STORAGE AND ANALYSIS (SCC), pages 1788-1798, Salt Lake City, UT, 2012
25. NVIDIA. CUDA Parallel Computing Platform. https://developer.nvidia.com/cuda
26. L. Oliker, X. Li, P. Husbands, and R. Biswas. Effects of ordering strategies and programming paradigms on sparse matrix computations. SIAM Review, 44(3):373-393, 2002
27. OpenACC Corporation. The OpenACC Application Programing Interface, 2011. http://www.openacc.org/
28. Portland Group Inc. PGI Compiler Reference Manual, 2014. http://www.pgroup.com/doc/pgiref.pdf
29. A. Possner, E. Zubler, O. Fuhrer, U. Lohmann, and C. Schär. A case study in modeling lowlying inversions and stratocumulus cloud cover in the bay of biscay. Weather and Forecasting, 29(2):289-304, 2014/06/01 2014
30. T. Shimokawabe, T. Aoki, J. Ishida, K. Kawano, and C. Mtiroi. 145 tflops performance on 3990 gpus of tsubame 2.0 supercomputer for an operational weather prediction. In Proc. Int. Conf. Comp. Sci., volume 4 of Procedia Computer Science, pages 1535-1544, 2011
31. T. Shimokawabe, T. Aoki, C. Muroi, J. Ishida, K. Kawano, T. Endo, A. Nukada, N. Maruyama, and S. Matsuoka. An 80-fold speedup, 15.0 tflops full gpu acceleration of non-hydrostatic weather model asuca production code. In High Performance Computing, Networking, Storage and Analysis (SC), 2010 International Conference for, pages 1-11, Nov 2010
32. J. Steppeler, G. Doms, U. Schättler, H. Bitzer, A. Gassmann, U. Damrath, and G. Gregoric. Meso gamma scale forecasts using the nonhydrostatic model LM. Meteor. Atmos. Phys., 82, 2002
33. N. Stern. Review on the economics of climate change. Technical report, HM Treasury, London, UK, 2006. http://www.hm-treasury.gov.uk/stern_review_report.htm
34. The OpenMP ARB. The OpenMP API Specification for Parallel Programming, 2013. http://www.openmp.org
35. T. Weusthoff, F. Ament, M. Arpagaus, and M. W. Rotach. Assessing the benefits of convection-permitting models by neighborhood verification: Examples from map d-phase. Monthly Weather Review, 138:3418-3433, 2010