Application domains

Collaboration across disciplines, software stacks and system solutions has proven to be extremely effective and cross-development and interdisciplinary work, especially in combinations with ICT-related disciplines, machine learning, data processing, cross-pollination of detailed modelling, Monte-Carlo simulation and signal analysis, optimised modelling and machine learning model, with particular attention to introspective machine learning, in the stack of approaches to high energy physics, computation chemistry from quantum levels to protein folding and complex matter analysis and modelling have shown promise in this context.

There is a several domains and applications where Slovenian experts and expert researchers have developed advanced approaches or are even integrated with the developer communities. In these domains, targeted high-level support or even co-development for substantial use of the infrastructure from user communities and projects in these spaces are foreseen. These domains and applications include:

  • Machine learning, including container-based and optimised vector/GPU based application deployment for domain-specific systems as well as general frameworks (PyTorch, Theano, Caffe, Tensorflow) with optimizations for accelerator sharing, interconnect and RDMA architectural challenges and new deployments.

  • Biomolecular and materials simulations based on force-field molecular dynamics, with support for NAMD, Gromacs, Amber, and LAMMPS. Modelling of enzymatic reaction with techniques based on the empirical valence bond approach as well as quantum chemistry and materials modelling and simulations with support for Gaussian, NWchem, ORCA, and VASP and other popular packages.

  • Advanced high-level support for Quantum ESPRESSO in materials research, including support for massively parallel and GPU based executions. Efforts in integration between machine learning, ab-initio models and Monte Carlo in progressive systems in high-energy physics, quantum chemistry, materials science, and complex matter research. In soft-matter: large-scale Monte-Carlo simulations of polymers, analysis of liquid crystal defects. Medical physics: fast, possibly on-line, GPU based analysis of medical tissues using RTE solution of layered media.

  • Non-equilibrium quantum and statistical physics: dynamics and statistical properties of many-body system.

  • Fluid dynamics simulations and analysis in reactor physics and technology: the development of scalable simulations of turbulent heat transfer caused by high thermal conductivity of sodium and liquid metals and resulting high thermal loads and thermal fluctuations that can penetrate into adjacent structures with low attenuation; open-source based simulations are implemented with the use of spectral elements to solve for velocity, temperature and any other passive scalars. Support for research and simulation in particle transport theory (neutrons, protons) with Singularity and Docker environments for Monte Carlo simulations for reactor physics of power reactors, research reactor physics, nuclear fusion, nuclear data evaluation and plasma physics.

  • Astrophysics: data mining in large astrophysical collaboration datasets, modelling of radiation from astrophysical structures. Support for CORSIKA-based simulation and analysis of high energy cosmic ray particle-initiated air showers. high-level support, co-development and application porting for high-energy physics and astrophysics, specifically ATLAS at CERN, Belle2 experiment at KEK, Japan, Pierre Auger in Argentina and CTA, taping expertise gained in Slovenia where local teams collaborated at high-throughput computing and storage orchestration in these projects as well as development of distributed computing software since 2003.

  • Bioinformatics (Megamerge, Metamos). High-level support, co-development and data-flow optimizations for human genomics (currently work-flows based on GATK, Picard) with many applications in human, animal and plant-based research, but also in medicine and medical diagnostics.

  • Fire-dynamics and simulations (FDS), fluid dynamics with OpenFOAM.

  • Medical image processing and research work with medical image analysis and modelling in medical physics.

  • Satellite images and astronomic image processing, GIS processing using modern scalable machine-learning approaches. Basic parallel and message-passing programming with new architectures and interconnects, and support for basic mathematical and computational libraries, including Octave, Sage, Scilab.