Distributed Computational Technologies

02.04.02In russian

Level of education Master

Type of instruction Full-time

Duration 2 years

Main academic courses
  • Algorithmic Fundamentals of Information Processing
  • Technologies and Algorithms of High-Performance and Distributed Computations
  • Algorithmic Theory of Coding and Fast Signal Processing
  • Introduction to Problems of Digital System Investigation and Design
  • Precomputation of Complex Problems
  • Methods of Statistical Information Processing
  • Applied Software for Modelling Complex Systems
  • History of Computer Engineering and Programming Development
  • Mathematical and Computer Modelling Processes in Complex Systems
  • Mathematical Description of Hard Formalisable Processes
  • Automated Systems of Data Collection and Processing
  • High-Performance and Distributed Computing Systems
  • Mathematical Methods in Programming and DB
  • Numerical Methods of Solving Complex Problems
  • Scientific Visualisation of Complex Physical Processes
Our advantages
  • Students are trained in the cutting-edge and most popular computer technologies in the world: cloud computing, big data, and Hadoop.
  • They have access to advanced computer architectures: Blue Gene, Ultra SPARC, GP GPU and others.
  • They can take part in cooperation programmes with world’s leading universities.
  • They receive a comprehensive education from a good mathematical preparation to in-depth knowledge of engineering disciplines.
  • Graduates have an opportunity to work in leading computer companies.
Future career


  • Analyst – a specialist who knows how to ‘put’ applied tasks into computing.
  • Mathematician – a specialist who knows how to bring tasks to the necessary rigour, correctness and efficiency.
  • System programmer – a specialist who knows how to bring developed models to special and intermediate software that implements all created theoretical models.
  • Our graduates are universal researchers who are ready to apply their knowledge to solve urgent and resource-intensive tasks.

Organisations where our graduates work

  • Computer companies and software producers: IBM; Oracle; EPAM Systems; T-Systems; Digital Services Association; Speech Technology Center Limited; NEOTEK MARIN JSC; group of companies ‘Digital Design’; and others
  • Computing centres and research institutions: the Resource Centre ‘The Computing Centre of St Petersburg University’; and the Laboratory of Information Technologies of the Joint Institute for Nuclear Research
  • Industry: Avrora Scientific and Production Association; JSC Concern Okeanpribor
  • Universities: St Petersburg University; the University of Amsterdam; Aalto University; and others
International relations
  • Pavol Jozef Šafárik University in Košice (Slovakia)
  • The University of Amsterdam (the Netherlands)
  • Lappeenranta-Lahti University of Technology (Finland)
  • Aalto University (Finland) and others
Main areas of research
  • High performance computing, and grid and cloud technologies
  • Distributed computing and data processing
  • Big Data
  • Distributed ledgers
  • Mathematical modelling of complex problems, development of computing environments (‘virtual testing ground’)
  • Systems of artificial intelligence and the Internet of things
  • Application of information technology methods to solve applied problems of physics, technology, medicine, and socio-economic problems
Achievements of the teaching staff of the academic programme
  • Creation of the first Beowulf-cluster in Russia (1997)
  • First distributed computing over the Internet (1998)
  • Participation in projects to create GRID infrastructure: NorduGRID, X-GRID, LCG (since 2000)
  • The system of dynamic load balancing in a heterogeneous environment (DINAMITE product) (2003)
  • Development of middleware for the European project ‘Virtual Laboratory’ (in cooperation with the University of Amsterdam) (2001-2010)
  • Development of a distributed telemedicine cardiology system (within the framework of the SKIF programme) (2004)
  • Methods for optimising data access in a heterogeneous computer environment (2008)
  • Hierarchical resource control in GRID calculations (2009)
  • Using virtualisation methods as a basis for the work of a supercomputer centre (2011)
  • Development of tools for a virtual personal supercomputer (2013)
  • Development of tools for creating a virtual elementary particle accelerator (2014)
  • Development of tools for the analysis and processing of Big Data (2015)
  • Development of tools for a virtual hydrodynamic testing ground (2018)
  • Development of a distributed ledger system and consensus algorithms (2018)
  • Development of virtualisation methods for processing distributed Big Data (2020)