We mediate efficient utilisation of our leading national supercomputing infrastructure in order to increase the competitiveness and innovation of Czech science and industry. IT4Innovations primarily provides computational resources to researchers and academics from the Czech Republic within Open Access Grant Competitions. From 2013 to the end of 2022, 1,719 projects in various scientific fields, such as new materials and drug design, physics laws discovery, engineering problems, rendering, and scientific data visualisation, to projects addressing cybersecurity, advanced data analytics, and AI tasks, have received computational resources.

Computational resources allocated within Open Access Grant Competitions by scientific disciplines [%]



Computational resources allocated within the Open Access Grant Competitions by institutions [%]


 institutions using computational resources
1 700+
BILLION core hours

what do our supercomputers solve?

Podporujeme špičkový výzkum a inovace ve všech vědních oblastech.

selected projects from 29th open access grant competition 


3D reconstruction for object manipulation

Call: 29th Open Access Grant Competition; OPEN-29-7

Researcher: Varun Burde

Institution: Czech Technical University in Prague

Field: Informatics


Manipulating objects is a core capability for many robots. A pre-requisite for manipulation is object pose estimation, where the goal is to estimate the position and orientation of the object relative to the robot, as this information informs the robot on how to interact with the object (how to approach, how to grasp, etc.). The current state-of-the-art object pose estimation algorithm relies on some representation to estimate the object pose. Obtaining highly accurate CAD models can be challenging and time-consuming and may require professional hardware such as a laser scanner. Our previous result showed that state-of-the-art methods can reconstruct simple objects well, but to accommodate a wider variety of objects, the current generation of algorithms needs to be significantly improved along multiple axes, such as runtime, robustness to environmental change, and accuracy of reconstruction/representation. Our research aims to accelerate 3D reconstruction techniques and leverage modern implicit object representation, enabling real-time deployment in robotics and accommodating more complex objects. IT4Innovations computing infrastructure provides a platform to work and train with large-scale datasets. The research is part of the Student grant competition of CTU No.: SGS23/172/OHK3/3T/13.

Exploring the Intrinsically Disordered Domains in p53 Protein

Call: 29th Open Access Grant Competition; OPEN-29-55

Researcher: Amina Gaffour

Institution: Charles University, Faculty of Pharmacy in Hradec Králové

Field: Material Sciences





The p53 tumour suppressor protein is a critical cell cycle arrest and apoptosis regulator. Unfortunately, the molecular mechanisms underlying p53 function are not fully understood, particularly in intrinsically disordered regions (IDR), which have been observed to play an essential role in the protein’s folding, stability, and, most importantly, function. In this study, we will implement molecular dynamics to investigate the IDRs in p53, focusing on phosphorylation sites, ion concentration, the tetramerization process on secondary structure, and the function of the tumour suppressor protein. Preliminary findings are promising, showing a well-established effect on small trajectories from the concentration of ions and an alteration in how phosphorylated residues behave. Our findings will provide new insight into the protein's inner workings, which may provide key information for developing new therapeutic strategies for treatment.


Antimicrobial Selective Peptides To Induce Cell rupture (ASEPTIC)

Call: 29th Open Access Grant Competition; OPEN-29-23

Researcher: Timothée Emmanuel J. Rivel

Institution: CEITEC

Field: Biosciences



Antibiotic-resistant bacterial strains pose a global health threat, demanding innovative solutions. Antimicrobial peptides (AMPs) offer a promising therapeutic avenue by disrupting bacterial membranes, particularly through pore formations. In this project, we introduce a novel method to quantify the energetic cost of AMP-assisted pore formation using molecular dynamics simulations. Our primary goal is to optimize peptide sequences by reducing the energy barrier of pore formation for bacterial membranes – thus increasing AMP efficiency. Our secondary goal is to preserve a high barrier for mammalian membranes – thus reducing AMP toxicity. We achieve this by tailoring peptides to exploit the distinctive lipid content in both these membranes, and we validate our results using leakage assays on lipid vesicles with corresponding lipid contents. This project requires intensive computational resources that LUMI-C, the fastest supercomputer in Europe, can provide. Indeed, this project relies on many free energy calculations, that sums up to hundreds of simulations of the process of pore opening.

This research is supported by the project “MSCAfellow5_MUNI” (No. CZ.02.01.01/00/22_010/0003229) funded by the European Regional Development Fund.

The use of computationally expensive DFT functionals for salt-cocrystal systems investigation

Call: 29th Open Access Grant Competition; OPEN-29-25

Researcher: Simona Chalupná

Institution: University of Chemistry and Technology, Prague

Field: Material Sciences




There is currently a wide range of different solid forms of pharmaceutical substances. One of these forms are pharmaceutical salts, which are commonly used to formulate active pharmaceutical ingredients (APIs). Approximately half of the drugs found on the market today are in the form of salts. Another solid form that is increasingly used in the formulation of pharmaceuticals is a cocrystal. The difference between these two forms is due to the position of only one atom - hydrogen. The exact position of this hydrogen, and hence the type of solid form, is crucial, as pharmaceutical companies must disclose it in patent and registration documentation, as required by medical authorities. Since the difference between the salt and the cocrystal is so small, it is interesting to conduct research into new methods of identifying the position of hydrogen.

This project deals with the possibility of distinguishing between salts and cocrystals by means of a calculation based on electron density functional theory (DFT). DFT describes electrons as glue poured between atomic nuclei. A functional is a mathematical function that describes the behaviour of such glue. The functionality and accuracy of this computational solution must be tested on a large number of substances (on the order of hundreds of structures), and subsequently, it is necessary to deal with those structures where the calculation does not agree with the experimental results. Thanks to IT4Innovations' allocated computational resources, this task can be performed using state-of-the-art methods, even if they are extremely computationally expensive.

Slama – Slavonic Large Foundational Language Model for AI

Call: 29th Open Access Grant Competition; OPEN-29-48

Researcher: Aleš Horák

Institution: Masaryk University

Field: Informatics




The Slama (Slavonic Large Foundational Language Model for AI) project aims to create a new foundational language model focusing on the main Slavonic languages with Latin script (Czech, Slovak, Polish, ...). The project's primary goal is to explore the performance differences between state-of-the-art pre-trained multilingual models (where English texts represent the majority of training data) and a model tailored specifically to the Slavic language group. The research will focus on developing generative models, the training data of which is more balanced in favour of the Slavonic language group rather than English. Therefore, the new model should provide better results when using AI tools processing mainly Slavonic languages. The resulting foundational model can then be easily applied to various AI tasks.


Concrete Fracture: A meso-level approach

Call: 29th Open Access Grant Competition; OPEN-29-13

Researcher: Petr Miarka

Institution: Institute of Physics of Materials of the Czech Academy of Sciences

Field: Engineering


Schematic illustration of the heterogeneous inner structure of concrete considering various aggregates and pore sizes including 3D numerical.






The fracture of concrete is a complex mechanism influenced by its highly heterogeneous inner structure: matrix/cement paste, aggregates, and pores. Aggregates and cement paste do not represent an ideal connection, which is often considered the weakest link within the material. This often results in certain practical limitations. In concrete, which uses Portland cement as the binder, the behaviour of this material interface is relatively well investigated. Recently, material science has set its focus on the design of non-cementitious binders, which have a significantly lower carbon footprint compared to cement. However, the damage mechanisms of these modern materials can differ significantly from conventional concrete.

The computational resources at the Barbora supercomputer at IT4Innovations are used for creating complex numerical models that, in detail, consider this natural material's heterogenous inner structure. The obtained results then allow for the understanding of the onset of damage at the paste/aggregate interface and explain the role of pores during the damage evolution due to static or cyclic load. Understanding the damage evolution can contribute to faster applications of these alternative binders in structural engineering.

Structure Elucidation of Cu2O Photocatalyst Surfaces via Machine Learning

Call: 29th Open Access Grant Competition; OPEN-29-33

Researcher: Christopher Heard

Institution: Charles University in Prague

Field: Material Sciences



Cuprous oxide (Cu2O) is a material with promising applications in photo(electro)catalysis, green fuels, and solar energy production. However, its performance depends on the structure of its surface, which can change under different conditions, such as temperature, pressure and the presence of various naturally occurring adsorbate molecules. To elucidate the atomic-level morphology of Cu2O surfaces and thus understand its reactive properties, advanced simulation techniques are required, which are able to span the complexity and size of the system adequately.

This project involves the development and application of machine learning potentials (MLPs) for fast and accurate modelling of the structure and dynamic behaviour of Cu2O. It will leverage the computational power of supercomputers to generate a sufficiently large and reliable dataset of surface structures and temperature-dependent surface dynamics. The MLPs will be trained via quantum chemical calculations and validated against both high-level calculations and state-of-the-art experimental data and applied to understanding the atomistic nature of this promising catalyst.

  Publications with overview of our users' projects