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News
July 9, 2026
HSE Economists Use Search Queries to Forecast Birth Rates
Researchers from the HSE Faculty of Economic Sciences have shown that the accuracy of birth rate forecasts for Russia can be improved by almost 50% by incorporating the dynamics of online search queries related to pregnancy and childbirth into forecasting models. In the best-performing models, the forecasting error fell from 4.6% to 3.2%. The findings have been published in Populations and Economics.
July 8, 2026
HSE Researchers Discover Who Eats Out in Russia-And Why
Around one-third of Russians (31.3%) rarely eat out or buy ready-made meals. The core group of active consumers—those who eat out or purchase prepared food almost every day or several times a week—accounts for only about 9% of the population. These are the findings of a study conducted by the HSE Institute for Social Policy. According to the researchers eating out is no longer a marker of high social status in Russia.
July 8, 2026
HSE University and RREDA Join Forces to Support 2026 Renewable Energy of the Planet Competition
HSE University and the Russia Renewable Energy Development Association (RREDA) have signed a partnership and information cooperation agreement to support Renewable Energy of the Planet—2026, a national competition with international participation for students and early-career researchers. Applications are open on the competition's website until September 20, 2026.

 

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Algorithm for replica redistribution in an implementation of the population annealing method on a hybrid supercomputer architecture

Computer Physics Communications. 2021. Vol. 261. P. 107786.
Russkov A., Chulkevich R., Shchur L.

The population annealing method is a promising approach for large-scale simulations because it is potentially scalable on any parallel architecture. We present an implementation of the algorithm on a hybrid program architecture combining CUDA and MPI. The problem is to keep all general-purpose graphics processing unit devices as busy as possible by efficiently redistributing replicas. We provide details of testing on hardware based the Intel Skylake/Nvidia V100 running more than two million replicas of the Ising model sample in parallel. The results are quite encouraging because the acceleration grows toward the perfect line as the complexity of the simulated system increases.

Research target: Computer Science Mathematics Physics
Priority areas: IT and mathematics
Language: English
Full text
DOI
Text on another site
Keywords: метод Монте-КарлоMonte Carlo methodCUDAsupercomputingсуперкомпьютерное моделированиеmessage passing interface (MPI)population annealing algorithmОтжиг популяции
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