Parallel Performance Analysis of a Regional Numerical Weather Prediction Model in a Petascale Machine

  • Roberto Pinto Souto
  • Pedro Leite da Silva Dias
  • Franck Vigilant
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 565)


This paper presents the parallel performance achieved by a regional model of numerical weather prediction (NWP), running on thousands of computing cores in a petascale supercomputing system. It was obtained good scalability, running with up to 13440 cores, distributed in 670 nodes. These results enables this application to solve large computational challenges, such as perform weather forecast at very high spatial resolution.


Parallel performance analysis Numerical weather prediction Petascale supercomputing 



This project is supported by FINEP Brazilian funding agency (process number The authors would like also to thank to ATOS/BULL for make available its computing resources in order to adapt BRAMS to run in SDumont cluster.


  1. 1.
    INPE/CPTEC Brazilian developments on the regional atmospheric modelling system (1999)Google Scholar
  2. 2.
    Freitas, S.R., Longo, K.M., Silva Dias, M.A.F., Chatfield, R., Silva Dias, P., Artaxo, P., Andreae, M.O., Grell, G., Rodrigues, L.F., Fazenda, A., Panetta, J.: Atmos. Chem. Phys. 9(8), 2843–2861 (2009)CrossRefGoogle Scholar
  3. 3.
    Pielke, R., Cotton, W., Walko, R., Tremback, C., Lyons, W., Grasso, L., Nicholls, M., Moran, M., Wesley, D., Lee, T., Copeland, J.: Meteorol. Atmos. Phys. 49(1–4), 69–91 (1992)CrossRefGoogle Scholar
  4. 4.
    Cotton, W.R., Pielke Sr., R., Walko, R., Liston, G., Tremback, C., Jiang, H., McAnelly, R., Harrington, J., Nicholls, M., Carrio, G., et al.: Meteorol. Atmos. Phys. 82(1-4), 5–29 (2003)Google Scholar
  5. 5.
    Gropp, W., Lusk, E., Doss, N., Skjellum, A.: Parallel Comput. 22(6), 789–828 (1996)CrossRefGoogle Scholar
  6. 6.
    Fazenda, A.L., Panetta, J., Navaux, P., Rodrigues, L.F., Katsurayama, D.M., Motta, L.F.: Anais do X Simpósio em Sistemas Computacionais (WSCAD-SCC), pp. 27–34 (2009)Google Scholar
  7. 7.
    Fazenda, A.L., Panetta, J., Katsurayama, D.M., Rodrigues, L.F., Motta, L.F., Navaux, P.O.: Int. J. High Perform. Syst. Architect. 3(2–3), 87–97 (2011)CrossRefGoogle Scholar
  8. 8.
    Fazenda, A.L., Rodrigues, E.R., Tomita, S.S., Panetta, J., Mendes, C.L.: 2012 13th Symposium on IEEE Computer Systems (WSCAD-SSC), pp. 126–132 (2012)Google Scholar
  9. 9.
    Petitet, A., Whaley, R.C., Dongarra, J., Cleary, A.: HPL - a portable implementation of the High-Performance linpack benchmark for Distributed-Memory computersGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Roberto Pinto Souto
    • 1
  • Pedro Leite da Silva Dias
    • 1
  • Franck Vigilant
    • 2
  1. 1.National Laboratory for Scientific Computing (LNCC)PetrópolisBrazil
  2. 2.Atos/Bull Center for Excellence in Parallel Programming (CEPP)ÉchirollesFrance

Personalised recommendations