13S114PRS - Computer Systems Performance

Course specification
Course title Computer Systems Performance
Acronym 13S114PRS
Study programme Software Engineering
Type of study bachelor academic studies
Lecturer (for classes)
Lecturer/Associate (for practice)
Lecturer/Associate (for OTC)
ESPB 6.0 Status mandatory
Condition None
The goal Learning the basic concepts of system performance analysis with applications in computing. Training students to model and analyze systems and networks using stochastic methods and mean value analysis (MVA). Performance in software and programming. Learning about simulation methods and measurement techniques, benchmark programs, data analysis, ranking and decision-making techniques.
The outcome Students will be able to: choose an appropriate modeling technique depending on the characteristics of a computer component or system, set up an abstract model, state assumptions and approximations for a model, calculate performance indicators based on given parameters, discuss the obtained numerical indicators and analyze data with adequate interpretation of the results.
URL to the subject page
URL to lectures
Contents of lectures Techniques and applications of performance and data analysis. Processors, memory and disks performance. Queuing networks modeling. Poisson process. Birth and death formula. Closed networks. Open networks. Operational analysis of systems and networks. Fundamentals of simulation and measurement. Preparation, analysis and visualization of data and evaluation in decision making and ranking.
Contents of exercises Tasks and examples from the areas defined by the theoretical part, especially: processors, disks, memory models, central server networks, Buzen's algorithm. Interactive systems and their analysis using stochastic methods and the MVA algorithm. Examples of simulation and analytical evaluation through a single person project. Interpretation of evaluation results, biased data analysis, ratio-games.
  1. Rai Jain, "The Art of Computer Systems Performance Analysis," 2nd edition, John Wiley and Sons, April 2015.
  2. Y. C. Tay, "Analytical Performance Modeling for Computer Systems," Third Edition, Springer, 2018.
  3. Brendan Gregg, "Systems Performance," 2nd Edition, Addison-Wesley Professional Computing Series, 2020.
  4. Micha Gorelick, Ian Ozsvald, "High Performance Python: Practical Performant Programming for Humans," 2nd edition, O'Reilly Media, June 2020.
  5. Computer Systems Performance, presentations used on lectures and auditory exercises, Web site of the Department of Computer Engineering and Informatics, School of Electrical Engineering,
Number of hours per week during the semester/trimester/year
Lectures Exercises OTC Study and Research Other classes
2 2 1
Methods of teaching Lectures and auditory exercises, individual work of students on assignments and projects.
Knowledge score (maximum points 100)
Pre obligations Points Final exam Points
Activites during lectures 0 Test paper 35
Practical lessons 0 Oral examination 0
Colloquia 65