Faculty of Technical Sciences

Subject: Parallel and Distributed Algorithms and Data Structures (17.RVP02)

Native organizations units: No data
General information:
 
Category Academic-general educative
Scientific or art field Applied Computer Science and Informatics
Interdisciplinary No
ECTS 6
Educational goal:

Advanced education of students in the field of parallel and distributed systems. Learning the techniques of selecting, analyzing, implementing, and applying parallel and distributed algorithms and data structures with special emphasis on the blockchain.

Educational outcome:

Students will acquire advanced knowledge about modelling problems through parallel and distributed algorithms and data structures and their implementation in contemporary parallel and distributed systems. Students will get an in-depth knowledge about public and private blockchain systems. Acquired knowledge is used in practice and subsequent subjects titled Scientific Computing and High Performance Computing for Data Science.

Course content:

Introduction to parallel and distributed systems. Models and complexity of parallel and distributed algorithms. Shared memory algorithms. Message passing algorithms. Architectures, processes, communication, coordination, consistency, and replication in distributed systems. Fault tolerance in distributed systems. Consensus algorithms. Byzantine Generals' Problem. Concepts, ideas, and techniques in blockchain systems. Public and private blockchain systems. Examples of blockchain technologies. Design patterns in parallel and distributed programming.

Teaching methods:

Lectures, practical exercises. Final exam and practical exercises form the final grade.

Literature:
Authors Title Year Publisher Language
Fokkink, W. Distributed Algorithms: An Intuitive Approach 2018 MIT Press English
McCool, M., Reinders, J., Robison, A. Structured Parallel Programming: Patterns for Efficient Computation 2012 Morgan Kaufmann English
Van Steen, M., Tanenbaum, A.S. Distributed Systems 2017 CreateSpace Independent Publishing Platform, Scotts Valley English
Donovan, A., Kernighan, B. The Go Programming Language 2015 Addison-Wesley Professional English
Antonopoulos, A. Mastering Bitcoin 2017 O’Reilly English
Knowledge evaluation:
Course activity Pre-examination Obligations Number of points
Theoretical part of the exam No Yes 30.00
Test Yes Yes 10.00
Complex exercises Yes Yes 40.00
Term paper Yes Yes 10.00
Test Yes Yes 10.00
Lecturers:

Asistent Gligorov Nenad

Assistant - Master

Computational classes
API Image

vanr. prof. dr Gajić Dušan

Associate Professor

Lectures

Asistent Horvat Nebojša

Assistant - Master

Computational classes

vanr. prof. dr Dragan Dinu

Associate Professor

Computational classes

Faculty of Technical Sciences

© 2024. Faculty of Technical Sciences.

Contact:

Address: Trg Dositeja Obradovića 6, 21102 Novi Sad

Phone:  (+381) 21 450 810
(+381) 21 6350 413

Fax : (+381) 21 458 133
Emejl: ftndean@uns.ac.rs

© 2024. Faculty of Technical Sciences.