The laboratory main goal is research, collection, processing, and analysis of big data, visualization of objects and studying methods for data storage and management. New big data technologies and software systems can be implemented in research and industrial areas. In particular, the laboratory activity is focused on the development of a model and analytics for the petroleum industry and environmental science.
The laboratory actively collaborates with BNL, NRC-KI, and JINR (Dubna).
The laboratory is particularly proud of its close collaboration with CERN and the ATLAS experiment. In 2016, TPU became an associate member of LHCb collaboration at CERN. The University students and young scientists have a chance to undergo research internship at CERN. Along with this, the laboratory participated in the creation of data knowledge catalog for CERN.
- Development of new approaches in analysis and processing of big data;
- Integration of smart methods and research-and-analysis tools of big data.
The core element of the project is the development of software for storing, processing, accessing, analyzing and visualizing big data for science and industry.
Areas of scientific interests of the laboratory research staff:
- Mathematics and Software of Complexes, and Computer Networks;
- Mathematical Modeling, Numerical Methods, and Program Complexes;
- Equipment and Methods of Experimental Physics;
- Nuclear and Particle Physics;
- Physics of Charged Particle Beams and Accelerator Technology.
R&D projects, implemented by the laboratory:
- MetaMiner for BigData: Development of a heterogeneous metainformation storage system for exabyte scale scientific experiments and application of machine learning methods for identifying violation in operation of distributed systems of processing and analysis of big data.
- Development of an analytical platform to unify control systems for computing tasks in a distributed heterogeneous computer environment.
- A system for analyzing of computing tasks of a heterogeneous computer environment for processing scientific experiment data.
Deadlines: 2016-2018
Funding organization: the Russian Science Foundation
Deadlines: 2016
Funding organization: The Ministry of Education and Science of the Russian Federation
Deadlines: 2017
Funding organization: The Ministry of Education and Science of the Russian Federation