Project goals
- Developing computer assembly in the data processing center (DPC) that allows the teams of the research center to conduct intensive calculations and solve complex problems, including:
- Performing computational tasks of quantum mechanics, neutron interactions;
- Innovative developments in the field of reverse engineering, visualization, nanosystems industry.
- Support for the mechanism of interaction between participants in the research process, experimental and technological monitoring.
Project deadlines
December 2015 – August 2017
Project summary
In the project, Borlas Group introduced computer assembly at St. Petersburg Institute of Nuclear Physics named after B. P. Konstantinov (part of National Research Center Kurchatov Institute), consisting of the following components:
- Systems of computing modules, node management, parallel data storage based on Niagara equipment;
- High-speed data transmission equipment based on Mellanox switches;
- Systems for transmission of control and service data, routing of external networks.
The computer assembly combines several computing modules with a total peak performance of 364 Tflops and storage subsystems with 3.5 PB of usable capacity (5.4 PB of raw capacity of the memory array). The network infrastructure powered by Extreme Networks switches, which provide high performance and bandwidth to handle large amounts of data even at maximum loads.
Borlas Group ensured the delivery of equipment, installation and commissioning of all components of the new computer assembly of St. Petersburg Institute of Nuclear Physics.
The computer assembly of St. Petersburg Institute of Nuclear Physics has been selected as a member of the prestigious rating of supercomputers of Russia and CIS of Top50.
Borlas won the contract to deliver equipment in open auction, where the company's offer was recognized as the best.
Project results
- Developing a reliable and high-performance infrastructure for innovative developments of St. Petersburg Institute of Nuclear Physics, providing additional opportunities to increase the functionality of the Institute's GRID network;
- Improving efficiency, speeding up the tasks of modeling, engineering calculations, analysis and visualization of data obtained in fundamental and applied research;
- Ample opportunities for training engineering personnel who have a strong supercomputer competence to develop science-intensive products.