OS4PRS - Computer Systems Performance
Course specification | ||||
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Course title | Computer Systems Performance | |||
Acronym | OS4PRS | |||
Study programme | Electrical Engineering and Computing | |||
Module | Signals and Systems | |||
Type of study | bachelor academic studies | |||
Lecturer (for classes) | ||||
Lecturer/Associate (for practice) | ||||
Lecturer/Associate (for OTC) | ||||
ESPB | 6.0 | Status | elective | |
Condition | None | |||
The goal | Teaching of the basic concepts of computer performance analysis and its application areas. Explanation of simplified models of computer system components (processors, memory, disks). Providing students with the ability to model and analyze computer systems and networks using stochastic methods and the mean value analysis (MVA) applied to open and closed queuing networks. | |||
The outcome | Students will be able to: select the appropriate modeling technique, depending on the characteristics of the computer component or system, set up an abstract model, specify the assumptions and approximations for the specific model, calculate performance indicators based on a set of given parameters, critically discuss the obtained numerical performance indicators, and interpret the results. | |||
Contents | ||||
Contents of lectures | Techniques and applications of computer performance analysis. Performance of the processors, memory subsystem and disks. Modeling of computer systems based on queuing networks. Poisson process. Birth and death formula. Exponential and non-exponential models. Pollaczek–Khinchine formula. Closed networks. Open networks. Central server networks. Stochastic and MVA analysis of systems and networks. | |||
Contents of exercises | Problems and examples that follow the order of topics presented during lectures: disk modeling based on linear, discrete and continuous models, examples of the system modeling based on single server queue, cyclic model of multiprogramming, central server network, Buzen's algorithm. Interactive systems and their analysis using stochastic methods and the MVA algorithm | |||
Literature | ||||
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Number of hours per week during the semester/trimester/year | ||||
Lectures | Exercises | OTC | Study and Research | Other classes |
3 | 1 | 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 | 70 | |
Practical lessons | 0 | Oral examination | 0 | |
Projects | 30 | |||
Colloquia | 0 | |||
Seminars | 0 |