CSC/ECE 579 — Introduction to Computer Performance Modeling
Lecture slides, assignments, and solutions are available from the course Moodle space
Lecture videos are available from the EOL site
Fall 2024 Schedule of Lectures
| Date | Lecture # | Topic | Assignment | Due |
|---|---|---|---|---|
| Aug 20 | 1 | Overview, goals, logistics | ||
| Aug 22 | 2 | Introduction | ||
| Aug 27 | 3 | HW 1 | ||
| Aug 29 | 4 | |||
| Sep 3 | 5 | |||
| Sep 5 | 6 | Project 1 | ||
| Sep 10 | 7 | |||
| Sep 12 | 8 | HW2 | HW1 | |
| Sep 17 | — | No class (Wellness Day) | ||
| Sep 19 | 9 | |||
| Sep 24 | 10 | |||
| Sep 26 | 11 | HW2 | ||
| Oct 1 | 12 | |||
| Oct 3 | 13 | Project 1 | ||
| Oct 8 | 14 | |||
| Oct 10 | 15 | |||
| Oct 15 | — | No class (Fall Break) | ||
| Oct 17 | 16 | HW3 | ||
| Oct 22 | 17 | |||
| Oct 24 | 18 | |||
| Oct 29 | 19 | |||
| Oct 31 | 20 | HW4, Project 3 | Project 2 | |
| Nov 5 | 21 | HW3 | ||
| Nov 7 | 22 | |||
| Nov 12 | 23 | |||
| Nov 14 | 24 | |||
| Nov 19 | 25 | HW 4 | ||
| Nov 21 | 26 | |||
| Nov 26 | 27 | Project 3 | ||
| Nov 27 | — | No class (Thanksgiving Holiday) | ||
| Dec 3 | 28 | |||
| Dec 5 3:30-6 | — | Final exam | ||
Syllabus
Prerequisites
Students who wish to take this course must have completed a course on Probability Theory (MA 421 or equivalent) and a course on Computer Organization (CSC 236 or ECE 109 or equivalent).
Students must also have good working knowledge of a high-level programming language such as C, C++, or JAVA. The programming projects can be challenging, hence good programming experience is required.
Objectives
The purpose of this course is to present simulation techniques and queueing theory as tools for modeling and studying the performance of communication networks and computer systems.
At the conclusion of the course you should be able to:
- apply simulation techniques to develop models of computer and communication systems;
- appy queueing-based models to characterize computer and communication systems;
- use appropriate analytic tools to compute performance measure of interest (e.g., response time and throughput) for a given queueing system;
- select the system characteristics (e.g., storage capacity) to achieve a given level of performance;
- evaluate the relative merits of alternative system design solutions; and
- engage in research in the field of performance analysis and evaluation.
I encourage and expect you to participate actively in the learning process. In particular, I welcome your comments and questions as we cover material in class. One-way lectures quickly become boring, both for you and for me. By asking lots of questions your understanding of the material will be deepened significantly, and the course will be much more fun!
Outline
The course is logically divided in three parts.
Part I: Refresher.
At the beginning of the semester we will review important concepts from probability theory and Laplace and z transforms.
Part II: Simulation Techniques.
This part addresses the development of simulation models, including:
- generation of random numbers and stochastic variates
- simulation designs
- estimation techniques for analyzing endogenously created data
- validation
Part III: Queueing Theory.
This part introduces a number of fundamental concepts and techniques, including:
- stochastic processes and Markov processes
- Poisson process
- birth-death processes
- the M/M/1 queue and variants
- Erlang and Coxian distributions as models of service time
- the M/G/1 queue
- priority queueing and conservation laws
Textbook
Students are required to purchase the following textbook:
- L. Kleinrock, Queueing Systems, vol. 1: Theory, Wiley. ISBN: 0-471-49110-1
I also suggest the following two books as reference:
- L. Kleinrock, Queueing Systems, vol. 2: Computer Applications, Wiley
- W. Drake, Fundamentals of Applied Probability Theory, McGraw-Hiil (or any other book on probability theory and transforms)
I will also make available an extensive set of lecture slides.
Grading
Students are required to complete all assignments and show all work in order to receive full credit. The final grade will be determined using the following weights:
- 45% — Three programming projects (15% each)
- 15% — Homework assignments (of equal weight)
- 20% — Midterm exam (open book)
- 20% — Final exam (comprehensive, open book)
Policies
Attendance: Attendance is not mandatory but strongly encouraged. Students are responsible for making up any course material they miss.
Assignments: No hard copies of assignments or solutions will be handed out. New assignments and solutions will be announced in class and/or the course mailing list, and will be available on the course web page.
Submission: Students must submit their assignments as PDF or Word files using the submit facility. The deadline for submission is midnight (Eastern time) on the day due. Any deadline extensions are up to the discretion of the instructor, and will be announced to the whole class. Extensions may be provided to individual students only in advance of the submission deadline and only under extenuating circumstances.
Late Submission: No late assignments will be accepted and no partial credit will be given for late assignments without a valid excuse.
Cheating: Homework and projects are individual assignments and students are required to submit their own solutions. All students are bound by the University’s academic integrity policies (refer to the relevant section below).
Teaching Assistant
TBD (tbd@ncsu.edu) is the TA for this course.
You may contact her to arrange for an online chat or video call at a mutually convenient time.
Feel free to contact the TA for any questions about the course.
Office Hours
My office is in Room 2409 of the EB III building.
Please email me to arrange for a mutually convenient time to have a discussion over the phone or online chat.
Academic Integrity
Students are required to respect the NC State academic integrity policies.