Objectif du cours
"Performance evaluation" is a label that covers many topics, from theory to practice, in computer science and computer engineering. It includes the design of mathematical models (very often with probabilistic assumptions), the analysis of such models (mathematically or using simulation), the design of experimental protocols (measuring tools and data collection), the analysis of data (statistics on real experiments or in silico experiments). It is used to design, compare or tune computer systems and communication networks. Some tools also apply to related systems like transport networks, logistics or automatic control.
- Basic knowledge in probability and in Python (or R) programming (for statistics)
- Intermediate level in Linux Operating System, including command lines and C programming (for practical case study)
Grading: 50% continuous assessment (at least one homework assignment and one time-limited written test), 50% final exam (time-limited written exam).
Performance Evaluation (from theory to practice)
- Performance Evaluation of Computer and Communication Systems, by J.-Y. Le Boudec. EPFL Press, 2011.
- The Art of Computer Systems Performance Analysis: Techniques for Experimental Design, Measurement, Simulation, and Modeling, by R. Jain. Wiley-Interscience, 1991.
- Systems Performance: Enterprise and the Cloud, by B. Gregg, Addison-Wesley, 2013.
- An Introduction to Probabilistic Modeling, by P. Brémaud. Springer-Verlag, 1994.
- Markov Chains, Gibbs Fields, Monte Carlo Simulation and Queues, by P. Brémaud. Springer-Verlag, 1999.
- Queuing Systems : Theory (vol I) & Computer Applications (vol II), by L. Kleinrock. John Wiley & Sons Inc, 1976.
- Elements of Queueing Theory: Palm Martingale Calculus and Stochastic Recurrences, by F. Baccelli & P. Brémaud. Springer-Verlag, 2000.
- The Cartoon Guide to Statistics, by L. Gonick & W. Smith. William Morrow Paperbacks, 1993.
- Python for Data Analysis, by W. McKinney. O′Reilly, 2012.