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News
October 8, 2026
HSE Experts Take Part in 23rd Annual Meeting of Valdai Discussion Club
The 23rd Annual Meeting of the Valdai Discussion Club was held from September 28 to October 1, 2026 under the theme ‘Responsibility for the Future: Limits of the Possible, or Limitless Possibilities?’ The forum brought together 120 experts from 40 countries, including representatives of China, the United States, India, Brazil, the United Kingdom, Germany, Egypt, Iran, and Japan.
October 7, 2026
‘Our Team Consists of True Leaders in Their Respective Academic Disciplines
The HSE International Centre of Decision Choice and Analysis studies a wide range of methods for analysing decision-making and possible scenarios for the development of natural, socio-economic, and political phenomena using various mathematical models. The application of advanced mathematical methods to forecasting helps to prevent negative outcomes and avoid erroneous decisions. The HSE News Service spoke to the centre’s director, Prof. Fuad Aleskerov, about its work.
October 6, 2026
International N5 Symposium ‘Neural Networks and Nonlinearity in Nizhny Novgorod Brings Together Scientists from Russia and Serbia
The International N5 Symposium ‘Neural Networks and Nonlinearity in Nizhny Novgorod’ was held at the Nizhny Novgorod House of Scientists from September 23 to 26. The event was organised by HSE University–Nizhny Novgorod and the Nizhny Novgorod House of Scientists, with the participation of Sberbank and the Institute of Physics Belgrade. The symposium was held for the second time: the first conference took place in 2025 and attracted considerable interest from the academic community.

 

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Intel OpenVINO™ Toolkit: анализ производительности выполнения генеративно-состязательных нейронных сетей

Проблемы разработки перспективных микро- и наноэлектронных систем (МЭС). 2021. № 2. С. 83–90.
Zunin V., Romanov A.

The paper provides an overview of the current state of the implementation of neural networks and their methods of execution. A detailed description of the main components of the Intel® OpenVINO ™ Toolkit for executing neural networks on various Intel hardware platforms (CPU, GPU, Neural Compute Stick 2) is considered. The works in which this toolkit is used are investigated and the conclusions made in them are presented. Before carrying out the experiment, the selection of various generative adversarial neural networks, data sets for testing them, and the process of launching neural networks on selected hardware platforms (four experimental stands with different hardware equipment) and obtaining results are described. Based on the results of the experiments, the obtained data are presented based on two metrics: performance in FPS and the cost of using the tested hardware platform to execute a neural network. Based on the data obtained, the analysis of the performance metrics of the previously selected generative adversarial neural networks is carried out without the use of tools, using the OpenVINO ™ Toolkit in the usual mode, as well as using the Multi-Device Plugin and Heterogeneous Plugin on several connected devices.

Research target: Engineering and Technology
Language: Russian
Full text
DOI
Keywords: Intelнейронные сетиneural networksGANOpenVINOIntelOpenVINOGAN
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