The heterogeneous computing platform HybriLIT is a multi-component system consisting of the “Govorun” supercomputer, a training and testing polygon, networked data storage systems, and a set of specialized services. The platform is designed for application development, high-performance computing, data processing, and data storage.
The presentation will provide an overview of the software and...
The presentation will showcase the capabilities of the ecosystem deployed on the HybriLIT platform for developing algorithms based on machine learning and deep learning methods, data annotation, service deployment, and more.
The HybriLIT platform is part of the Multifunctional Information and Computing Complex of the JINR Laboratory of Information Technologies. It includes the “Govorun” supercomputer and a training and testing cluster designed for developing and running high-performance parallel applications.
The presentation provides a step-by-step guide on how to gain access to HybriLIT resources, including...
In this computational study, we investigate the adsorption of superheavy
elements Copernicium (Cn) and Flerovium (Fl), and their lighter homologs
Mercury (Hg) and Lead (Pb), on a Selenium (100) surface. Our approach
employs periodic Density Functional Theory (DFT) in Quantum ESPRESSO
(open-source suite of codes)with spin-orbit coupling and DFT-D4
dispersion correction. Our resultsshow...
I'll give a brief overview of computational molecular physics (CMP)
techniques in my talk. They fall into two groups: Molecular Mechanics
(MM) and Quantum Mechanics (QM). MM approaches use predefined
analytical interatomic potentials, whereas QM approaches rely on an
approximate solution of the many-electron Schrödinger equation.
Likewise I'll describe few open-source CMP applications...
Computational Molecular Physics hands-on-execercises are available at: HybriLIT-workshop-2025-materials
Monte Carlo simulation in Geant4 is a highly resource-intensive process. The presentation introduces the experience of computing a complex model using the resources of the “Govorun” supercomputer and discusses aspects of running jobs through the SLURM scheduler as well as error handling.
The presentation will cover the main approaches to accelerating computations in Python. Special attention is given to the NumPy library, which provides efficient array operations and significantly improves performance. The use of the Numba JIT compiler is also discussed, enabling faster function execution by compiling them into machine code. To increase performance on multicore systems, CPU...
Quantum Approximate Optimization Algorithm (QAOA) simulations were performed on the Hybrilit quantum testbed at JINR. The testbed infrastructure is well suited for such research: significant computational resources are available, including multi-core CPUs, GPUs, and RAM; JupyterHub, as well as quantum simulators Cirq, Qiskit, qsim, and other are deployed. The problem of finding the ground...
The presentation will showcase the capabilities of the ecosystem deployed on the HybriLIT platform for developing algorithms based on machine learning and deep learning methods, data annotation, service deployment, and more.
The work was performed with the support of the Russian Science Foundation within the framework of project No. 22-71-10022
Совместный редактор кода...
This master class demonstrates the potential of the Julia programming language for exploring multiparameter models described by systems of nonlinear differential equations. A model of a point φ0 Josephson junction of the superconductor-ferromagnet-superconductor type with a direct relationship between the magnetic moment and the Josephson current is considered as an example. A methodology for...
