Spring 2021 - CMPT 305 E100
Computer Simulation and Modelling (3)
Class Number: 7884
Delivery Method: In Person
Course Times + Location:
Tu 4:30 PM – 6:20 PM
REMOTE LEARNING, Burnaby
Fr 4:30 PM – 5:20 PM
REMOTE LEARNING, Burnaby
Prerequisites:CMPT 225, (MACM 101 or (ENSC 251 and ENSC 252)) and STAT 270.
This course is an introduction to the modelling, analysis, and computer simulation of complex systems. Topics include analytic modelling, discrete event simulation, experimental design, random number generation, and statistical analysis.
This course is an introduction to the modelling and computer simulation of complex systems. The course includes both the theory and practice of model design, analysis, and simulation. The course focuses on the modelling and performance evaluation of computer systems and networks. Quizzes will cover the theory. In homework programming assignments and projects, students will model and simulate aspects of computer systems and networks.
- Basic Concepts of Simulation, Modelling, and Performance Evaluation
- Analytic Modelling: Queueing theory, fundamental laws, single/multiple server queues
- Discrete Event Simulation: Event scheduling, random number and random variate generation
- Simulation Model and Output Analysis
- Experimental Design: Factorial designs, linear regression
- Queueing Network Models
- Computer System Simulation: System components, performance metrics, simulator design
- Quizzes 30%
- Homework programming assignments 30%
- Projects (Tentative) 40%
- Quantitative System Performance: Computer System Analysis Using Queueing Network Models, Edward D. Lazowska, John Zahorjan, G. Scott Graham, Kenneth C. Sevcik, Prentice Hall, 1984, Available online at https://homes.cs.washington.edu/~lazowska/qsp/
- The Art of Computer Systems Performance Analysis: Techniques for Experimental Design, Measurement, Simulation, and Modeling, R. Jain, Wiley, 1991, 9780471503361
- Discrete-Event Simulation: A First Course, L.H. Leemis and S.K. Park, Prentice Hall, 2005, 9780131429178
- Experimental Design and Analysis, Howard J. Seltman, Online, 2018, N/A, Available online at https://www.stat.cmu.edu/~hseltman/309/Book/Book.pdf
ACADEMIC INTEGRITY: YOUR WORK, YOUR SUCCESS
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Each student is responsible for his or her conduct as it affects the University community. Academic dishonesty, in whatever form, is ultimately destructive of the values of the University. Furthermore, it is unfair and discouraging to the majority of students who pursue their studies honestly. Scholarly integrity is required of all members of the University. http://www.sfu.ca/policies/gazette/student/s10-01.html
TEACHING AT SFU IN SPRING 2021
Teaching at SFU in spring 2021 will be conducted primarily through remote methods. There will be in-person course components in a few exceptional cases where this is fundamental to the educational goals of the course. Such course components will be clearly identified at registration, as will course components that will be “live” (synchronous) vs. at your own pace (asynchronous). Enrollment acknowledges that remote study may entail different modes of learning, interaction with your instructor, and ways of getting feedback on your work than may be the case for in-person classes. To ensure you can access all course materials, we recommend you have access to a computer with a microphone and camera, and the internet. In some cases your instructor may use Zoom or other means requiring a camera and microphone to invigilate exams. If proctoring software will be used, this will be confirmed in the first week of class.Students with hidden or visible disabilities who believe they may need class or exam accommodations, including in the current context of remote learning, are encouraged to register with the SFU Centre for Accessible Learning (firstname.lastname@example.org or 778-782-3112).