VEGA

There are several domains and applications where Slovenian experts and expert researchers have developed advanced approaches or are part of the development. 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.
  • Quantum chemistry and materials modelling and simulations with support for Gaussian, NWchem, ORCA, and VASP and other popular packages.
  • Materials research with Large-scale Monte Carlo simulations of polymers, analysis of liquid crystal defects with Quantum ESPRESSO. 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.
  • 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, 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 (Pierre Auger in Argentina and CTA), modelling of radiation from astrophysical structures. CORSIKA‑based simulation and analysis of high energy cosmic ray particle-initiated air showers.
  • High-energy physics, extreme scale data processing, detector simulation, data reconstruction and distributed analysis, ATLAS at CERN, Belle2 experiment at KEK, Japan.
  • Bioinformatics (Megamerge, Metamos), co-development and data-flow optimizations for human genomics (GATK, Picard) with many applications in human, animal and plant-based research, 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, support for basic mathematical and computational libraries, including Octave, Sage, Scilab.

Collaboration across disciplines, software stacks, and system solutions has proven to be extremely effective 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.