|Course title||Computer System Performance Evaluation
|Course description||Computer system performance evaluation through analytical and simulation studies. Brief overview of queueing theory, computational algorithms, sequential and parallel simulation techniques. Performance evaluation in distributed resource allocation, computer interconnection architecture, multiprocessing and multithreads computation, parallel 1/O architectures, distributed database concurrency control protocols, multiple access protocols in communication network, and parallel programming models, etc. Students are expected to have knowledge in probability, stochastic processes and computer architecture.
|Semester||1 or 2|
|Grade Descriptors||A/A-: EXCELLENT – exceptionally good performance and far exceeding expectation in all or most of the course learning outcomes; demonstration of superior understanding of the subject matter, the ability to analyze problems and apply extensive knowledge, and skillful use of concepts and materials to derive proper solutions.
B+/B/B-: GOOD – good performance in all course learning outcomes and exceeding expectation in some of them; demonstration of good understanding of the subject matter and the ability to use proper concepts and materials to solve most of the problems encountered.
C+/C/C-: FAIR – adequate performance and meeting expectation in all course learning outcomes; demonstration of adequate understanding of the subject matter and the ability to solve simple problems.
D+/D: MARGINAL – performance barely meets the expectation in the essential course learning outcomes; demonstration of partial understanding of the subject matter and the ability to solve simple problems.
F: FAILURE – performance does not meet the expectation in the essential course learning outcomes; demonstration of serious deficiencies and the need to retake the course.
|Learning outcomes||At the end of the course of studies, students will have acquired the ability to:
1. understand stochastic modeling of computer/communication systems
2. understand how to apply simulation, queueing analysis and applied probability for do capacity planning for computer/communication systems
3. understand how to apply queueing network theory to model and analyze large distributed systems
4. understand how to use simulation and mathematical modeling to analyze models of computer systems so as to assess their performance implications
(for reference only)
|Essay test or exam: 60%
|Recommended Reading List||1. Queueing Systems Volume I: theory, by L. Kleinrock (Wiley Intersecience), 1975.
2. Performance Modeling of Communication Networks and Computer Architectures by P.G. Harrison and N.M. Patel (Addison Wesley), 1993
3. Probability, Stochastic Processes and Queueing Theory, by Randy Nelson (Springer-Verlag), 1995.
|CSCIN programme learning outcomes||Course mapping|
|Upon completion of their studies, students will be able to:|
|1. identify, formulate, and solve computer science problems (K/S);|
|2. design, implement, test, and evaluate a computer system, component, or algorithm to meet desired needs (K/S);
|3. receive the broad education necessary to understand the impact of computer science solutions in a global and societal context (K/V);|
|4. communicate effectively (S/V);
|5. succeed in research or industry related to computer science (K/S/V);
|6. have solid knowledge in computer science and engineering, including programming and languages, algorithms, theory, databases, etc. (K/S);|
|7. integrate well into and contribute to the local society and the global community related to computer science (K/S/V);|
|8. practise high standard of professional ethics (V);|
|9. draw on and integrate knowledge from many related areas (K/S/V);
|Remarks: K = Knowledge outcomes; S = Skills outcomes; V = Values and attitude outcomes; T = Teach; P = Practice; M = Measured|