## CSC/ECE 579 — Introduction to Computer Performance Modeling

### University Community Standards and Personal Safety Requirements Rule related to COVID-19.

### Lecture slides, assignments, and solutions are available from the course Moodle space

### Lecture videos are available from the EOL site

### Zoom session — only available during scheduled class times

## Fall 2020 Schedule of Lectures

Date | Lecture # | Topic | Assignment | Due |
---|---|---|---|---|

Aug 10 | 1 | Overview, goals, logistics | ||

Aug 12 | 2 | Introduction | HW 1 | |

Aug 17 | 3 |
Review of probability theory Text: Appendix II.1-II.3 |
||

Aug 19 | 4 | Review of probability theory (cont'd) | ||

Aug 24 | 5 |
Review of Laplace and z transforms Text: Appendix I |
Project 1 | |

Aug 26 | 6 | Introduction to simulation | HW 2 | HW 1 due |

Aug 31 | — | Classes cancelled/postponed by the University | ||

Sep 2 | 7 |
Introduction to simulation (cont'd) Random number generation |
||

Sep 7 | 8 | Random number generation (cont'd) | ||

Sep 9 | 9 |
Discussion of Project 1 Simulation design |
HW 2 due | |

Sep 14 | 10 | Estimation techniques | ||

Sep 16 | 11 | Estimation techniques (cont'd) | ||

Sep 21 | 12 |
Poisson process Text: pp. 60-71 |
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Sep 23 | 13 |
Markov processes Text: 2.4 |
Project 2 | Project 1 due |

Sep 28 | 14 |
Birth-death processes, Birth-death queueing systems Text: 2.5 Discussion of sample exam problems |
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Sep 30 | — | Midterm Exam | HW 3 | |

Oct 5 | 15 |
Discussion of midterm exam Discussion of Project 2 |
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Oct 7 | 16 |
Little's law M/M/1 queueing system Text: 2.1, 3.1, 3.2 |
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Oct 12 | 17 |
M/M/1 queueing system (cont'd) |
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Oct 14 | 18 |
Simple Markovian queueing systems Text: 3.3-3.6 |
Project 3 | Project 2 due |

Oct 19 | 19 |
Simple Markovian queueing systems (cont'd) Discussion of Project 3 |
HW 4 | HW 3 due |

Oct 21 | 20 |
The method of stages M/Er/1 queueing system Text: 4.2, 4.3 |
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Oct 26 | 21 |
Bulk arrivals, Coxian distributions Text: 4.5, 4.7 |
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Oct 28 | 22 |
M/G/1 queuing system Mean queue length Text: 5.1, 5.3, 5.5 |
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Nov 2 | 23 |
Mean queue length (cont'd) ARQ protocol analysis M/G/1 queue with vacations |
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Nov 4 | 24 |
M/G/1 queue with vacations (cont'd) Pollaczek-Kinchin Transform Equations Text: 5.6, 5.7 |
HW 4 due | |

Nov 9 | 25 | Priority queueing | Project 3 due | |

Nov 11 | 26 | M/G/1 conservation laws | ||

Nov 18 8:30-11am |
— | 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 312 or ECE 218 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

Xian Yang (xyang45@ncsu.edu) is the TA for this course.

You may contact him 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 2306 of the EB II 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.