Performance and scalability experiments with a large-scale air pollution model on the EuroHPC petascale supercomputer DISCOVERER

• Autorzy: Ostromsky Tzvetan

Identyfikatory

DOI

10.15439/2022F224

• Konferencja: 17th Conference on Computer Science and Intelligence Systems
• Języki publikacji: EN

Abstrakty

EN

The basic parallel versions of the Danish Eulerian Model (UNI-DEM) has been implemented on the new petascale supercomputer DISCOVERER, installed last year in Sofia, Bulgaria by the company Atos. DISCOVERER is part of the European High Performance Computing Joint Undertaking (EuroHPC), which is building a network of 8 powerful supercomputers across the European Union (3 pre-exascale and 5 petascale).The results of some scalability experiments with the basic MPI and a hybrid MPI-OpenMP parallel implementations of UNI-DEM on the new Bulgarian petascale supercomputer DISCOVERER (in EuroHPC network) are presented here. They are compared with similar earlier experiments performed on the Mare Nostrum III supercomputer (petascale too) at Barcelona Supercomputing Centre - the most powerful supercomputer in Spain by that time, upgraded currently to the pre-exascale Mare Nostrum V, also part of the EuroHPC JU infrastructure.

Słowa kluczowe

EN

air pollution; numerical model; supercomputer; parallel computing; algorithm; scalability; MPI; OpenMP

• Wydawca: Polskie Towarzystwo Informatyczne
• Czasopismo: Annals of Computer Science and Information Systems
• Rocznik: 2022
• Tom: Vol. 32
• Strony: 81--84
• Opis fizyczny: Bibliogr. 9 poz., tab.

Twórcy

autor

Ostromsky Tzvetan

• Institute of Information and Communication Technologies (IICT), Bulgarian Academy of Sciences (BAS), Sofia, Bulgaria

Bibliografia

• 1. V. Alexandrov, A. Sameh, Y. Siddique and Z. Zlatev, Numerical integration of chemical ODE problems arising in air pollution models, Env. Modeling and Assessment, 2 (1997) 365-377.
• 2. I. Dimov, R. Georgieva, S. Ivanovska, Tz. Ostromsky, Z. Zlatev, Studying the sensitivity of pollutants’ concentrations caused by variations of chemical rates, J. Comput. Appl. Math., Vol. 235 (2010), pp. 391-402.
• 3. Ø. Hov, Z. Zlatev, R. Berkowicz, A. Eliassen and L. P. Prahm, Comparison of numerical techniques for use in air pollution models with non-linear chemical reactions, Atmospheric Environment, Vol. 23 (1988), pp. 967-983.
• 4. Tz. Ostromsky, I. Dimov, R. Georgieva, Z. Zlatev, Air pollution modelling, sensitivity analysis and parallel implementation, Int. Journal of Environment and Pollution, Vol. 46 (1-2), (2011), pp. 83-96.
• 5. Tz. Ostromsky, Z. Zlatev, Parallel Implementation of a Large-scale 3-D Air Pollution Model, in: Large Scale Scientific Computing (S. Margenov, J. Wasniewski, P. Yalamov, Eds.), LNCS-2179, Springer, 2001, pp. 309-316.
• 6. Tz. Ostromsky, Z. Zlatev, Flexible Two-level Parallel Implementations of a Large Air Pollution Model, in: Numerical Methods and Applications (I.Dimov, I.Lirkov, S. Margenov, Z. Zlatev - eds.), LNCS-2542, Springer (2002), pp. 545-554.
• 7. WEB-site of the Danish Eulerian Model, available at: http://www.dmu.dk/AtmosphericEnvironment/DEM
• 8. Z. Zlatev, Computer treatment of large air pollution models, Kluwer (1995).
• 9. Z. Zlatev, I. Dimov, Computational and Numerical Challenges in Environmental Modelling, Elsevier, Amsterdam (2006).

Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).