PRUE students at JINR

News, 15 April 2022

In early April, the Meshcheryakov Laboratory of Information Technologies hosted students of the Economic Lyceum of Plekhanov Russian University of Economics (PRUE), and on 12 April, the Laboratory held a seminar “Distributed Computing and Big Data Analytics” for students of the “Data Science” interfaculty group of PRUE.

PRUE students were welcomed by MLIT Director Vladimir Korenkov, who is also the Head of the PRUE’s Scientific Laboratory “Cloud Technologies and Big Data Analytics”. MLIT Scientific Secretary Olga Derenovskaia spoke about the major directions of the Laboratory’s activities and modern IT technologies for solving scientific and applied tasks. Igor Pelevanyuk and Maxim Zuev gave a tour of the Multifunctional Information and Computing Complex of JINR, during which students got acquainted with the “Govorun” supercomputer.

Lyceum students also visited the Veksler and Baldin Laboratory of High Energy Physics and met with Dmitry Dryablov who told them with enthusiasm about the NICA accelerator complex, the principles of its operation, and ongoing research . The students dropped by the MPD experiment building, were impressed by the scale of the 70-ton superconducting solenoid and walked along the collider tunnel. Their visit to Dubna ended with an excursion to the Museum of History and Technology of JINR, whose staff not only presented the history of the Institute’s foundation, but also conducted entertaining experiments to demonstrate the laws of physics.

For students of the Data Science group there were held practical classes within the seminar. Irina Filozova showed how the Structured Query Language (SQL) is useful when working with databases, which operators are more frequently used to perform different operations. Igor Pelevanyuk introduced the students to the principles of the Monte Carlo method using the example of calculating the number π, as well as discussed possible options for accelerating computations. The practical class by Ivan Kadochnikov was devoted to MapReduce technology that focuses on parallel computing within distributed clusters.

Students gained new impressions and knowledge that would broaden their horizons and become useful in future education.