Multiscale Modeling and Supercomputer Architectures

2024/2025

Academic Year

ENG

Instruction in English

6

ECTS credits

Delivered at:

School of Applied Mathematics

Course type:

Elective course

When:

2 year, 1, 2 module

Instructors

Kondratyuk, Nikolay

Tararushkin, Evgeny

Course Syllabus

Abstract

The course «Computer multiscale modelling and simulation» is aimed at the teaching students with a wide spectrum of methods, technologies and problems in the field of multiscale modelling and simulation and material properties. Different levels of theoretical description at various space and time scales are considered as well as the connections between them and computational technologies oriented on the hardware of the pre-exaflops era supercomputers

Learning Objectives

• The objectives of this course are at the suding of a wide spectrum of methods, technologies and problems in the field of multiscale modelling and simulation and material properties

Expected Learning Outcomes

• be capable of: Application in the given subject area statistical methods of processing experimental data, numerical methods, methods of mathematical and computational modeling of complex systems; Understanding meaning of the tasks appearing in the course of professional activity and employment the related physico-mathematical apparatus for description and solving the above tasks; Using the knowledge of physical and mathematical subjects for further learning according to the training profile;
• get experience in: Formulation of computational tasks in studies of complex systems; Preparing and running computer simulations of various systems; Correct processing of modeling results and their comparison with available experimental and literature data; Theoretical analysis of real problems related to atomic-scale studies
• know: the principles of the theoretical and computational description of matter at various scales. the basic algorithms for application of software for numerical solution of problems at each scale. the principles of bridging the gaps between the scale for solving particular problems and to have the corresponding experience
• be capable of: Estimation the computational complexity of the multiscale problems and the amount of computational resources for their solution; Analyzing scient ific problems and physical processes, realizing in practice fundamental knowledge obtained in the course of training; Adaptation new problematics, knowledge, scientific terminology and methodology, to possess the skills of independent learning;

Course Contents

• Computational aspects of multiscale modelling and simulation
• Principles of bridging the gaps between the scales
• Examples of the development and deployment of multiscale models in different fields
• Multiscale levels of theoretical description of matter

Assessment Elements

• Домашнее задание 1
• Контрольная работа 1
• Домашнее задание 2
• Контрольная работа 2
• Экзамен

Interim Assessment

• 2024/2025 2nd module
  0.2 * Домашнее задание 1 + 0.2 * Домашнее задание 2 + 0.2 * Контрольная работа 1 + 0.2 * Контрольная работа 2 + 0.2 * Экзамен

Bibliography

Recommended Core Bibliography

• Frenkel D., Smit B. Understanding Molecular Simulation: From Algorithms to Applications. –Elsevier, 2002.
• Rapaport, D. C. The art of molecular dynamics simulation. –Cambridge university press, 2004.

Recommended Additional Bibliography

• Precision Physics of Simple Atomic Systems, S.G. KarshenboimV.B. Smirnov (Eds.), Springer, 2003.
• Schweitzer F., Browning Agents and Active Particles Collective Dynamics in the Natural and Social Sciences, Springer, 2003

Authors

• TARARUSHKIN EVGENIY VIKTOROVICH
• KONDRATYUK NIKOLAY DMITRIEVICH
• SMIRNOV GRIGORIY SERGEEVICH