High Performance Computing Laboratory

HPC Lab offers unique solutions of complex problems like uncovering hidden characteristics, exploring unknown correlations in natural phenomena as well as predicting market trends and even estimating customer preferences using techniques like HPC (high-performance computing), AI (Artificial Intelligence) and Big Data analytics.

HPC Lab offers reliable and sustainable (24/7) computational resources, meeting the needs of the research and academic community as well as those of the small and medium enterprise sector on a national and regional level.

HPC Lab is included in the international network https://www.labsexplorer.com/, which disseminates information about the services that users receive from laboratories with verified international presence.



HPC Lab’s team is connected to research with pan-european interest, conducted jointly with colleagues from the Supercomputing centre in Barcelona, Spain.


HPC Lab utilizes industry-leading technologies that provide the best money-per-watt ratio for computational resources on the market.


HPC Lab uses highly-scalable methods for modeling and simulations, allowing for improved parallelism and data storage.


HPC Lab has partnered with universities to conduct educational graduate-level courses in the field of computational science and high-performance computing systems. These courses are accredited by the National Evaluation and Accreditation Agency. HPC Lab’s team regularly conducts intense training tailored-on-demand for the users.


HPC Lab opens doors for group visits of students to get acquainted with modern computer technology.

The lab’s team participates in information days for business, public administration and the general public. We have been regular participants in the European Researcher’s Night since 2017.

Current research projects
  1. HPC Lab (via RDIC) is an Associated partner in the project BG05M2OP001-1.001-0004 (2018-2023): UNITe, financed by the Operational Programme Science and Education for Smart Growth

In this project scientific research is distributed in several subjects, in which HPC Lab’s resources have crucial role:

Infrastructure for Big Data as a service, Software services for Big Data; innovative mathematical methods and models in the digital workspace; Systems for analysis and virtualisation for Big Data in real time; Visualisation; digitalisation and prototyping; Intelligent cyber-physical systems; Intelligent and sustainable cities, Factories of the future, Big Data in natural sciences.

  1. HPC Lab is included in the international network for Open Science, CoNOSC (2019-2030) coordinated by the Ministry of Education and Science, under the contract between Sofia Tech Park and Sofia University.
  2. HPC Lab is included in the National Roadmap for Research Infrastructure (via RDIC) (2017-2023)
  3. HPC Lab’s team members work on projects by the National Research Program ICT in Science, Education and Security (2019-2023)
  4. Contract High Performance Computing in Complex Systems
Current business projects
  1. Contract for creation of a system for descriptive and forecast analysis (Aug 2019 – Jan 2021) – financed by OPIC
  2. Contract for application of computational models for regional atmospheric forecast (July, 2020-July, 2021) – financed by the public administration
  3. Contract for creation of interactive 3D models (July 2018-Jan 2021) – financed by OPIC
Completed research projects
  1. High Performance Computing in Complex Systems and Processes in Them (2018-2019)
  2. Task-based Parallel Applications in Containers Platform, (2019-2020)
  3. GATE – Big Data for Smart Society funded by the European Commission Framework program HORIZON2020, the Topic: WIDESPREAD‐04‐2017; Grant Agreement No. 76356
  4. InRoad (2018-2019) funded by the European Union’s Horizon 2020 Research and Innovation programme under grant agreement No 730928
Completed business projects
  1. Contract for application of computational models for regional atmospheric forecast (2017-2018) – financed by the public administration
  2. Contract for application of computational models for regional atmospheric forecast (2018-2019) – financed by the public administration
  3. Contract for application of computational models for regional atmospheric forecast (2019-July, 2020) – financed by the public administration
  4. Contract for optimisation of a transport problem (Jun 2018 – Jul 2019) – financed by OPIC
  5. Contract for creation of interactive 3D models (July 2018-June 2020) – financed by OPIC
  1. Tuning the photocatalytic activity of carbohydrate-derived humins via ball milling: Insights by experimental and chemometrics approach, Tzvetkov, G., Nedyalkova, M., Zaharieva, J., Spassov, T., Tsyntsarski, B. 2019 Powder Technology
  2. Calculating the Partition Coefficients of Organic Solvents in Octanol/Water and Octanol/Air Nedyalkova, M.A., Madurga, S., Tobiszewski, M., Simeonov, V. 2019 Journal of Chemical Information and Modeling
  3. Simulation Paths of Anticancer Drugs on a Graphene Oxide Surface, Nedyalkova, M., Romanova, J., Stoycheva, J., Madurga, S. 2019 Carbon Nanostructures
  4. Chemomertic Risk Assessment of Soil Pollution, Nedyalkova, M., Simeonov, V. 2019 Open Chemistry
  5. Chemometric assessment of soil pollution and pollution source apportionment for an industrially impacted region around a non-ferrous metal smelter in Bulgaria, Dimitrov, D.S., Nedyalkova, M.A., Donkova, B.V., Simeonov, V.D. 2019 Molecules
  6. How to analyze compromised data from biological experiments? Simeonova, V. 2019 Comptes Rendus de L’Academie Bulgare des Sciences
  7. A manganese hydride molecular sieve for practical hydrogen storage under ambient conditions Morris, L., Hales, J.J., Trudeau, M.L., Georgiev, P.A., Kaltsoyannis, N., Antonelli, D.M. Energy Environ. Sci., 2019, 12, 1580
  8. Desolvation process in the flexible metal-organic framework [Cu(Me-4py-trz-ia)], adsorption of dihydrogen and related structure responses, Erhart, O., Georgiev, P.A., Krautscheid, H. 2019 CrystEngComm
  9. What one can learn from the cloud condensation nuclei (CCN) size distributions as monitored by the BEO Moussala? Kleshtanova, V., Angelov, Ch., Kalapov, I., (…), Guerova, G., Tonchev, V. 2019 AIP Conference Proceedings
  10. Scaling and Dynamic Stability of Model Vicinal Surfaces, Krzyzewski, F., Załuska-Kotur, M., Krasteva, A., Popova, H., Tonchev, V. 2019 Crystal Growth and Design
  11. Modeling the impact of urbanization on local meteorological conditions in Sofia, Dimitrova, R., Danchovski, V., Egova, E., (…), Gueorguiev, O., Ivanov, D. 2019 Atmosphere
  12. Comparison of urban mixing layer height from ceilometer, radiosonde and WRF model, Danchovski, V., Dimitrova, R., Vladimirov, E., Egova, E., Ivanov, D. 2019 AIP Conference Proceedings
  13. Peering into microscale details of mountain winds, Fernando, H.J.S., Mann, J., PaLMa, J.M.L.M., Dimitrova, R., Wildmann, N., Wang, Y. 2019 Bulletin of the American Meteorological Society
  14. I. Iliev, S. Pisov, A. Proykova, HIGH PERFORMANCE COMPUTING FOR NANOSCIENCE AND NANOTECHNOLOGY (technical report), Nanoscience & Nanotechnology (ISSN:1313-8995), 18, № 2, pp.39-41, eds. E. Balabanova, E. Mileva, Sofia, 2018
  15. Nikola Drenchev, Mali H. Rosnes, Pascal D. C. Dietzel, Alberto Albinati, Konstantin Hadjiivanov, and Peter A. Georgiev, Open Metal Sites in the Metal–Organic Framework CPO-27-Cu: Detection of Regular and Defect Copper Species by CO and NO Probe Molecules
  16. Phys. Chem. C, Article ASAP, DOI: 10.1021/acs.jpcc.8b04045, Publication Date (Web): July 2, 2018
  17. Olzat Toktarbaiuly, Victor Usov, Cormac Ó Coileáin, Katarzyna Siewierska, Sergey Krasnikov, Emma Norton, Sergey I. Bozhko, Valery N. Semenov, Alexander N. Chaika, Barry E. Murphy, Olaf Lübben, Filip Krzyzewski, Magdalena A. Załuska-Kotur, Anna Krasteva, Hristina Popova, Vesselin Tonchev, and Igor V. Shvets, Step bunching with both directions of the current: Vicinal W(110) surfaces versus atomistic-scale model, PHYSICAL REVIEW B 97, 035436 (2018), DOI:10.1103/PhysRevB.97.035436
  18. Filip Krzyżewski, Magdalena Załuska-Kotur, Anna Krasteva, Hristina Popova, and Vesselin Tonchev, Scaling and Dynamic Stability of Model Vicinal Surfaces, Cryst. Growth Des., DOI: 10.1021/acs.cgd.8b01379
  19. Desislava Dimova, Stoyan Pisov, Ana Proykova,Magnetism Of Bilayer Graphene With Vacancies, Volume 2, Issue 12, Page 779-782, Year 2017 | DOI: 10.5185/amp.2017/914
  20. D. Dimova, S. Pisov, N. Panchev, A. Proykova, The role of canonical ensemble in predicting the toluene film structure under external electric field, Nanoscience & Nanotechnology: Nanostructured material, application and innovation transfer, v17. No.1, pp.14-18 (2017) ISSN:1313-8995
  21. Desislava Dimova, Stoyan Pisov, Nikolay Panchev, Miroslava Nedyalkova, Sergio Madurga, and Ana Proykova, Insight into electric field-induced rupture mechanism of water-in-toluene emulsion films from a model system, The Journal of Chemical Physics 146, 194703 (2017); doi: 10.1063/1.4983163
  22. High-Performance Scientific Computing: First JARA-HPC Symposium , JHPCS 2016, Aachen, Germany, October 4–5, 2016, Revised Selected Papers, Volume 10164 of Lecture Notes in Computer Science, Theoretical Computer Science and General Issues, eds. Edoardo Di Napoli, Marc-André Hermanns, Hristo Iliev , Andreas Lintermann, Alexander Peyser, Springer International Publishing, 2017, ISBN 3319538616
Published abstracts of conference reports
  4. Ana Proykova, Bond type and bond length in nano-sized systems (In Memory of my friend and colleague Prof. Iovka Dragieva), 21st International conference on Nanoscience and Nanotechnology, Sofia 21-22.11.2019, Book of Abstracts.
  5. Nano fundamentals for dreamer-engineers, M. Alаdjov, V.Videkov, A.Proykova, 21st International conference on Nanoscience and Nanotechnology, Sofia 21-22.11.2019, Book of Abstracts.
  6. F. Krzyżewski, M. Załuska-Kotur, A. Krasteva, H. Popova3 and V. Tonchev, Unstable dynamics of model vicinal surfaces: Initial and intermediate stages, https://arxiv.org/abs/1806.10819
  • Computational and numerical model tests.
  • Computational resources for academic groups and business users.
  • Containers (Docker, Singularity).

Information of available software: http://hpc-lab.sofiatech.bg/available-software/

Note: New software can be installed per user requests


The Nestum Cluster, which the laboratory has at its disposal, is the second most efficient supercomputer in Bulgaria:

– The HPC cluster Nestum has 24 compute nodes, Fujitsu Primergy RX2530 M1 servers, equipped with 2 Intel Xeon E5-2698v3@2.3 GHz processors. Each processor consists of 16 cores, and the file system is maintained via a high-speed Infiniband subsystem.

More information about the hardware: http://hpc-lab.sofiatech.bg/infrastructure/

Prof. Dr. Ana Proykova

Scientific fields: Theoretical and computational physics; Optimization algorithms; High Performance Computing; Nuclear physics; Big Data Analytics


Prof. Dr. Ana I. Proykova, Doctor Habil, is a Full Professor at the University of Sofia, the Head of the High Performance Computing Laboratory at the Sofia Tech Park and the Chair of the European Strategy Working Group on Data, Computing and Digital Infrastructures. In her professional career she has worked at universities around the world, including Belgium, Germany, Israel, Italy, the USA, Japan, Singapore, Taiwan and in the 1980s – the USSR.  A member of four European advisory groups (AG) for Horizon2020 Work programme, namely on the Future and Emerging Technologies, on Science With and For Society, on Gender, on International Cooperation.
She is a member of the Horizon2020 Program Committee on the Nanotechnologies, Advanced Materials, Advanced Manufacturing and Processing, and Biotechnology  and a member of the Scientific Committee on Health, Environmental and Emerging Risks (SCHEER).

Sofia, bul. Tsarigradsko Shousse 111,
Laboratory Complex, Floor 2

e-mail: hpc-lab@sofiatech.bg

e-mail: labs@sofiatech.bg

Phone: + 359 889 900 614




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