The National Competence Centre of Bulgaria (NCC-Bulgaria) in the area of High-Performance Computing (HPC), High-Performance Data Analytics (HPDA) and Artificial Intelligence (AI) has the goal to enhance and develop the competences of the Bulgarian computational community, making full use of EuroHPC resources and the EuroCC partnership.

The NCC-Bulgaria is built by a consortium coordinated by the Institute of Information and Communication Technologies at the Bulgarian Academy of Sciences (IICT-BAS), and two members, Sofia University “St. Kliment Ohridski” (SU), and University of National and World Economy (UNWE). The three partners carry diverse technical and scientific background in the area of HPC and ICT in general, so as to ensure achievement of the project objectives and guarantee the overall success.

The partners collaborate with Sofia Tech Park, where the Discoverer EuroHPC supercomputer is operating.

Partners involved in the success story:

The Department of Parallel Algorithms (DPA)  is one of the departments of IICT-BAS.  The main research activities of DPA are in the areas: Parallel algorithms and distributed computing; Mathematical modelling and scientific computation in Environmental Mathematics, Gas discharge plasma, Semi-conductors physics; Monte Carlo algorithms; Development of Monte Carlo approaches for solving Wigner-Boltzmann equation and Barker-Ferry equation; etc.

DPA has been, and still is, an active participant in a number of research and educational projects of the EU programs as well as in NATO Scientific Programs for cooperation between EC and Eastern Europe

Technical/scientific Challenge:

The environmental modelling and air pollution modelling in particular is one of the toughest problems of computational mathematics (together with the meteorological modelling). All relevant physical and chemical processes in the atmosphere should be taken into account, which are mathematically represented by a complex PDE system. In order to simplify it proper splitting procedure is applied. As a result, the initial system is replaced by several simpler systems (submodels), connected with the main physical and chemical processes. These systems should be calculated in a large spatial domain, because the pollutants can be moved quickly on long distances, driven by the atmosphere dynamics, especially on high altitude. One major source of difficulty is the high intensity of the atmospheric processes, which require a small time-step to be used in order to get a stable numerical solution. All this makes the treatment of large-scale air pollution models a tuff and heavy computational task. It has always been a serious challenge, even for the fastest and most powerful state-of-the-art supercomputers. Fortunately, Bulgaria is one of the leading countries in Eastern Europe with respect to the supercomputer infrastructure development in the recent years.


A large-scale environmental model – the Danish Eulerian Model (DEM) was implemented on the new petascale supercomputer DISCOVERER, installed last year by Atos Company in Sofia Tech Park, Bulgaria. The machine is part of the emerging supercomputing network under development by the European High-Performance Computing Joint Undertaking (EuroHPC JU).

DEM is mathematically represented by a system of partial differential equations for calculating the concentrations of a number of pollutants in the atmosphere above a large geographical region (including the European continent, the Mediterranean and parts of Asia, North Africa and the Atlantic ocean). The main physical and chemical processes (horizontal and vertical wind, diffusion, chemical reactions, emissions and deposition) are adequately represented in the system.

The MPI standard library is used as a main parallelization tool.  MPI parallelization is based on the space domain partitioning. The space domain is divided into sub-domains and each MPI task works on its own sub-domain. On each time-step there is no data dependency between the MPI tasks on both the chemistry and the vertical exchange stages. This is not so on the advection-diffusion stage. Spatial grid partitioning between the MPI tasks requires overlapping of the inner boundaries and exchange of certain boundary values on the neighbour subdomains for proper treatment of the boundary conditions.

The subdomains are usually too large to fit into the fastest cache memory of the corresponding CPU. In order to achieve good data locality, the smaller calculation tasks are grouped in chunks (if appropriate) for more efficient cache utilization. This is done in order to reduce the data transfer between the cache and the main (slower access) memory. The size of chunks should be tuned with respect to the cache size of the target machine.

Scientific impact:  

DEM is a powerful and flexible large scale air pollution model, capable of calculating the levels of concentration for a number of dangerous pollutants and other chemically active species interacting with them (precursors), over a long time period. Moreover, various accumulative quantities (AOT40, AOT60, etc.) can be calculated on yearly basis, which have significant impact in the area of agriculture (on the yield of crops in particular), forestry, wildlife and human health. Over the years it has been successfully applied in many scientific and practical problems in various important areas (environmental, medical, social, economic, etc.).


The unified parallel version of the Danish Eulerian Model (UNI-DEM) proved to be scalable and use efficiently the computational power of the new petascale EuroHPC supercomputer Discoverer (shown in the table below). It produces a huge amount of output results in quite reasonable time, which can be used in different long-term environmental studies and simulations in various areas:

  • Air pollution evaluation and protection measures;
  • Human healthcare;
  • Economics of agriculture (yield & losses of crops estimation);
  • Forestry and wildlife protection;
  • Global climate changes consequences simulation;
  • Simulation of industrial accidents and natural disasters.

Success story # Highlights:

  • Keywords: Environmental modelling; Air pollution; Supercomputer; Parallel computing; Scalability
  • Industry sector: Agriculture, Forestry, Healthcare
  • Technology: HPC, MPI, OpenMP

Time (T) in seconds and speed-up (Sp) (with respect to the number of MPI tasks, given in the first column) for running UNI-DEM on the DISCOVERER supercomputer:

Summer average daily ozone maxima in Europe, calculated by the fine grid version of UNI-DEM (with 10×10 km. cells):

This project has received funding from the European High-Performance Computing Joint Undertaking (JU) under grant agreement No 951732. The JU receives support from the European Union’s Horizon 2020 research and innovation programme and Germany, Bulgaria, Austria, Croatia, Cyprus, the Czech Republic, Denmark, Estonia, Finland, Greece, Hungary, Ireland, Italy, Lithuania, Latvia, Poland, Portugal, Romania, Slovenia, Spain, Sweden, the United Kingdom, France, the Netherlands, Belgium, Luxembourg, Slovakia, Norway, Switzerland, Turkey, Republic of North Macedonia, Iceland, Montenegro


Assoc. Prof. Tzvetan Ostromsky,

Prof. Ivan Dimov

Institute of Information and Communication Technologies,

Bulgarian Academy of Sciences