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  • Collaboration
    of leading
  • Lomonosov Moscow State University
    as part of units
    Faculty of Mechanics and Mathematics
    Faculty of Computational Mathematics and Cybernetics
    Research computing center
    Keldysh Institute of Applied Mathematics of the RAS
    Marchuk Institute of Computational Mathematics of the RAS
  • Research Areas
    Development and application
    of supercomputer technologies
    Scientific teams of MSU, IAM RAS and INM RAS
    have unique expertise and world-class competencies
    in high-performance computing technology
    MSU Supercomputer Complex
    Supercomputer simulation
    of helicopter rotor rotation
    (IAM for Kamov Design Bureau)
    New computational methods,
    models and algorithms
    The efficiency of modern computing systems
    is directly related to the used algorithms.
    In particular, within the framework of the Center’s work,
    it is planned to obtain new methods for solving gas dynamics equations,
    develop software packages for modeling
    and visualization of complex processes, and their application
    to solving complex fundamental and industrial problems.
    The development of mathematical models
    and high-performance computing technologies
    for calculating the spatial structure and dynamics
    of a whole Earth system (IAM RAS, RCC MSU)
    A complete and continuous reproduction system
    of highly qualified world-class specialists
    in the field of fundamental and applied mathematics

Moscow Center for Fundamental and Applied Mathematics


On August 29, 2019, the winners of the competition held within the framework of the national project “Science” for the creation of world-class mathematical centers in Russia were announced. Among the winners are the Moscow Center for Fundamental and Applied Mathematics in a consortium of Lomonosov Moscow State University (based on Faculty of Mechanics and Mathematics, Faculty of Computational Mathematics and Cybernetics and Research computing center), the Keldysh Institute of Applied Mathematics of the Russian Academy of Sciences, and the Marchuk Institute of Computational Mathematics of the Russian Academy of Sciences.

The formation of international mathematical centers will make a significant contribution to the accelerated development of the research and development sector.

Among the main tasks of the Center:

  • conducting research in most relevant areas both in solving fundamental mathematical problems and in applied problems involving leading scientists and promising young researchers from Russia and other countries;
  • creating an environment for communication, cooperation and joint research by teams of participants of the center and leading experts from other scientific, educational and industrial centers in the field of mathematical sciences;
  • training highly qualified specialists in the field of mathematical sciences in most relevant areas of research.



The mathematical school of Moscow University gained worldwide fame over a hundred years ago. The school of Egorov, Luzin and their students received fundamental results on the widest range of problems faced by mathematicians in the first half of the 20th century. The names of Kolmogorov, Alexandrov, Gelfand, Arnold are known throughout the mathematical world. Since the 30-40s of the last century, the Faculty of Mechanics and Mathematics of Moscow State University has been one of the largest mathematical centers in the world, research is being conducted here in almost all relevant areas. It is enough to note that his graduates 6 times became winners of the Fields Medal.

The Faculty of Mechanics and Mathematics has always been one of the main centers of the Moscow School of Mathematics. Experts in all major mathematical areas work at its departments. One of the main traditions of the faculty is the presence of a number of large mathematical schools headed by outstanding scientists and conducting research in the rapidly developing areas of modern mathematics. The Faculty of Mechanics and Mathematics maintains constant strong ties with other mathematical centers; in particular, the director of the MI RAS, his deputy and many employees of this institute (including department heads), the director of the IAM RAS, employees of the Moscow Institute of Physics and Technology, the Higher School of Economics, etc. work at the faculty.

Faculty of Computational Mathematics and Cybernetics, Moscow State University Lomonosov, founded in 1970 on the initiative and thanks to the efforts of one of the largest Russian scientists of the 20th century, academician Tikhonov, is today the leading educational center in Russia for training personnel in the field of basic research in applied mathematics, computer technology and computer science. The faculty conducts research on the widest range of fundamental and applied problems of modern mathematics.

Moscow University is a source of highly qualified mathematical personnel for the mathematical centers of Russia and the world; in particular, the vast majority of employees of Moscow mathematical centers are graduates of Moscow State University.

The institutes of IAM RAS and INM RAS, founded by outstanding scientists, mathematicians, who made a huge contribution to the solution of many applied problems (in particular, in space exploration, the development of atomic energy, etc.) and who served as president of the USSR Academy of Sciences, academicians Keldysh and Marchuk, conduct research on how in the field of fundamental principles of computational mathematics and mathematical modeling, so in a wide range of areas related to solving important applied problems.

The solution of a large number of modern problems of mathematical modeling is possible only with the help of powerful computer technology, supercomputers. Moreover, the very task of transferring computations to this technique is a fundamental, non-trivial mathematical problem. Specialists of the Scientific and Research Center of Moscow State University in collaboration with colleagues from Moscow State University, IPM, IVM and other mathematical centers are engaged in solving this problem both at a fundamental, theoretical level and in the practical implementation of the developed methods.

Employees of the Research computing center of Moscow State University possess world-class competencies in the development and practical use of mathematical models and methods for building scalable computing systems and ultra-high performance environments, in creating scalable parallel algorithms and methods for solving applied problems in the natural sciences and humanities. It is this potential that is laid in the foundation of the MSU supercomputer complex, combining the resources of the Lomonosov supercomputers and the Lomonosov-2 supercomputer - the most powerful in Russia at present. The Center for the collective use of ultra-high-performance computing resources of Moscow University was created on the basis of the Research computing center of Moscow State University, which makes it possible to efficiently use powerful supercomputer resources to carry out more than 700 projects from various fields of science, based on the potential of mathematical modeling and computational technologies.

In many applied fields of science based on supercomputers and computational technologies, such as climate research, computational chemistry, cryptography, unique methods of processing big data and data compression, bioinformatics and bioengineering, astrophysics, and in many other MSU scientists hold strong authoritative positions in the world. A significant area of ​​research and development at Moscow University is the development of models, methods and technologies for creating highly efficient parallel applications. The results of work in this area are being actively implemented in the Russian supercomputer community, and are constantly used by thousands of users of high-performance computing systems.


It is planned to increase the number of young researchers participating in scientific programs and projects implemented by the center.

An increase in the number of papers published in journals indexed in international databases (Web of Science Core Collection / Scopus) is expected.

Upcoming events

17:15Research computing center, Lomonosov Moscow State University

Shaposhnikov D.S., Moscow Institute of Physics and Technology, Space Research Institute RAS

Rodin A.V., Moscow Institute of Physics and Technology, Space Research Institute RAS

Medvedev A.S., Max Planck Institute for Solar System Research, Gottingen, Germany

Numerical modeling of the Hydrological Cycle of Mars

The hydrological cycle plays a significant role in the Martian climate. Water vapor can be a very sensitive indicator of transport processes, which is especially important for three-dimensional climate models.

This study presents a new hydrological block of the general circulation model of the Martian atmosphere, developed at the Moscow Institute of Physics and Technology in collaboration with the Max Planck Institute of Solar System Research (MPI-MGCM). The model has a spectral dynamic core and successfully predicts wind speeds and temperatures due to the use of physical parameterizations characterized for both terrestrial and Martian models. The hydrological scheme includes two-moment microphysics, advection, diffusion, sedimentation of passive impurities depending on the average particle radius, a scheme of interaction with the surface, and photodissociation of water vapor.

The model successfully reproduces both the seasonal distribution of water vapor and ice, as well as the spatial distribution by latitudes and longitudes, which is confirmed by comparison with experimental data from SPICAM (IR spectrometer Mars Express), TES (Mars Global Surveyor) and CRISM (Mars Reconnaissance Orbiter). In addition, for individual orbits, the vertical profiles of the concentration of water vapor, ice particles and effective radii of water ice particles are well reproduced.

The simulations using an extended (up to 160 km) version of the model allow us to successfully demonstrate the process of water vapor transfer from the lower atmosphere to the upper one and to claim the leading role of dust distribution in this transport.

17:30Faculty of Computational Mathematics and Cybernetics, Lomonosov Moscow State University

R.A. Ibraev, Marchuk Institute of Numerical Mathematics of RAS, Shirshov Institute of Oceanology RAS

K.V. Ushakov, Shirshov Institute of Oceanology RAS

M.N. Kaurkin, Shirshov Institute of Oceanology RAS


The report presents the results of studies on the creation of a computer System for Operational Oceanology (SOO) of the global ocean. SOO consists of a joint ocean dynamics model INMIO and sea ice model CICE, a parallel ensemble optimal interpolation algorithm (DAS-EnOI). The whole system is running a compact computing platform for CMF modeling. The features and main characteristics of the components of the INMIO system - CICE, DAS-EnOI, CMF are considered. An example of the work of the World Ocean 1/10 x 1/10 x 49 INMIO model and its verification is given.

Using DAS-EnOI, the results of an ocean prediction study with assimilation of temperature and salinity profiles (ARGO) and ocean level anomaly (AVISO) in the North Atlantic model, which is part of the 1/10 x 1/10 x 49 World Ocean model, are considered.

Preliminary results of a global SOO model with a spatial resolution of 0.25 degrees created on the basis of the Marine Hydrophysical Institute of the Russian Academy of Sciences (Sevastopol) are presented. A multivariate data vector, consisting of ARGO profiles for temperature and salinity, satellite observations of ocean level and sea ice cohesion, is assimilated in the SOO layout. As part of this system, a fundamentally new technology for strong coupled data assimilation has been developed in two models - IWMIO (ocean) and CICE (sea ice), operating in parallel under the control of CMF3.0.

More details about working at

The work was funded by the Russian Science Foundation, grant No. 17-77-30001.

16:30Faculty of Computational Mathematics and Cybernetics, Lomonosov Moscow State University

The seminar was organized on the basis of the Scientific and Educational Center «Supercomputer Technologies». The reports cover all aspects of the use of supercomputers, parallel computing systems and distributed data processing methods for solving large computational problems. The seminar has a pronounced interdisciplinary nature, however, the various nuances of using supercomputer technologies are of interest to researchers from various fields.


1. 16:30 - 17:15

Krasnopolsky B.I., candidate of physical and mathematical sciences, senior researcher

Медведев А.В., Leading Programmer, Institute of Mechanics, Lomonosov Moscow State University

On the role of non-blocking communications in the implementation of linear algebra algorithms on supercomputers

The effective use of asynchronous data exchange mechanisms is a prerequisite for the development of scalable linear algebra algorithms with sparse matrices. New features of the MPI-3 standard, in particular, the emergence of non-blocking collective operations, were the impetus for the development of modified mathematical algorithms aimed at blocking the time of global communications and computations. However, non-blocking operations are not always asynchronous in practice.

The report describes the developed methodology for testing the degree of asynchrony of non-blocking local and global communications. The importance of a correct understanding of the operation of non-blocking communications on the used computing equipment is demonstrated and examples of erroneous conclusions published in the literature about the properties of algorithms using asynchronous non-blocking global communications are discussed.

Links on the topic of work:

1) B. Krasnopolsky, Revisiting performance of BiCGStab methods for solving systems with multiple right-hand sides // Computers & Mathematics with Applications, 2019,

2) A. Medvedev. Towards benchmarking the asynchronous progress of non-blocking MPI point-to-point and collective operations // Proceedings of ParCo conference, 2020 (in press).

3) B. Krasnopolsky. Predicting Performance of Classical and Modified BiCGStab Iterative Methods // Proceedings of ParCo conference, 2020 (in press).

4) A. Medvedev. IMB-ASYNC benchmark.


2. 17:15 - 18:00

Dokukin S.A., graduate student, Faculty of Physics, Lomonosov Moscow State University

Investigation of the self-organization and physical properties of a platinum-copper surface alloy

Investigation of the self-organization and physical properties of a platinum-copper surface alloy
The work is devoted to computer modeling of the formation and physical properties of surface alloys of Pt-Cu. In the framework of this work, the interatomic interaction potentials of Pt-Cu and Pt-Pt were selected, and a numerical method for modeling the formation of surface Pt-Cu alloys was developed. The atomic mechanisms, dynamics, and growth conditions of finger-like outgrowths and fractal clusters in the surface Pt / Cu (111) alloy were studied. In the Pt / Cu (001) surface alloy, the order – disorder phase transition was studied with a change in the platinum concentration, the dynamics of the dissolution of platinum clusters in copper, and the effect of platinum atoms on the electromigration rate of vacancy islands. All results were obtained on Lomonosov and Lomonosov 2 supercomputers.

Links on the topic of work:

1) Dokukin, S. A.; Kolesnikov, S. V.; Saletsky, A. M. et al. Growth of the Pt/Cu(111) surface alloy: Self-learning kinetic Monte Carlo simulations. JOURNAL OF ALLOYS AND COMPOUNDS. 2018. V. 763. P. 719-727.

2) Dokukin, S. A.; Kolesnikov, S. V.; Saletsky, A. M. Efficient energy basin finding method for atomistic kinetic Monte Carlo models. COMPUTATIONAL MATERIALS SCIENCE. 2018. V. 155. P. 209-215.

3) Dokukin, S. A.; Kolesnikov, S., V; Saletsky, A. M. Dendritic growth of the Pt-Cu islands on Cu(111) surface: Self-learning kinetic Monte Carlo simulations. SURFACE SCIENCE. 2019. V. 689, UNSP 121464.

4) Dokukin, S. A.; Kolesnikov, S. V.; Saletsky, A. M. Diffusion-mediated processes in Pt/Cu(001) surface alloy. SURFACE SCIENCE. 2020. V. 692, 121515.