Instructor:            Dr. Jun Wang, HEC 320, 823-0449(office),


Course Objective and Description:

This course aims to introduce how to conduct performance evaluation and analysis of computer systems. The course starts with some fundamental performance analysis techniques including methods for performance measurement, performance metrics, monitoring, experimental design, and system modeling. Then, the course continues with probability theory and statistics. Other topics include: comparing two or more systems; system tuning; performance bottleneck identification; characterizing the load on the system (workload characterization); determining the number and size of components (capacity planning); predicting the performance at future loads (forecasting); queuing theory, mean value analysis, and modeling. The course also includes some real-life case studies of the learned concepts to measure the performances of computer systems like I/O systems and data centers.

Course Learning Outcomes:

At the end of the course, student must be able to

  1. use applied probability theory in measuring the performance of a computer system.
  2. Understand statistics and data presentation.
  3. Practice performance evaluation techniques and performance measures or metrics.
  4. Summarize and analyze experiments outcomes.
  5. Compare systems using sample data.
  6. Use Queuing theory to measure performances of systems.
  7. Model communication networks and I/O computer systems

Case studies

  1. Open-source Disksim simulation framework
  2. Performance, Power and Reliability (e.g. Recoverability) in Storage Systems
  3. Power and Energy Modeling and Analysis in Computer Systems and Data Centers

Prerequisite: EEL 4742C and STA 3032, or instructor approval.

Required textbooks:

1) Computer Architecture, Fourth or fifth Edition: A Quantitative Approach (The Morgan Kaufmann Series in Computer Architecture and Design) [Paperback]John L. Hennessy (Author), David A. Patterson (Author)

2) Art of Computer Systems Performance Analysis Techniques For Experimental Design

Measurements Simulation And Modeling, by Raj Jain, Wiley Computer Publishing, John Wiley & Sons, Inc. ISBN: 0471503363 Pub Date: 05/01/91

Other References: 

  • Some selective papers in leading conferences/journals will be discussed.

Course Homepage:

Course Outline (tentative):

Introduction to performance analysis and evaluation

Main performance evaluation techniques and measures

Statistics for performance analysis

Summarizing data and its variability
Comparing systems;

Introduction to Queuing theory;

Little¡¯s Law;

Utilization Law

Mid-Term Examination

Stochastic Processes;

Markov Processes;

Analysis of a Single Queue;

M/M/1 queuing analysis, M/M/c queuing analysis;

Operational law M/G/1 queue.

Grading Policies:

  • Homework assignments 20%
  • Midterm exam (Open Book) 30%
  • Course Project: 50%
    • Proposal (15%)
    • Final Presentation and Demo (20%)
    • Final Report (15%)

Note: Homework and programming assignments are due by 11:59pm of the due date (unless announced in class otherwise). Late homework (non-programming) will NOT be accepted. Late program penalty is 10% per day, according to the timestamp of your online submission. Only when verifiable extenuating circumstances can be demonstrated will extended assignment due dates be considered. Verifiable extenuating circumstances must be reasons beyond control of the students, such as illness or accidental injury. Poor performance in class is not an extenuating circumstance. Inform your instructor of the verifiable extenuating circumstances in advance or as soon as possible. In such situations, the date and nature of the extended due dates for the assignments will be decided by the instructor.

Attendance Policy:

Attendance is required. Students are responsible for any material covered in class. Lots of the materials covered in class will not be in the textbook. Announcements about homework, projects, programming assignments, etc. may be made in class or online or by emails. Students are encouraged to check the online WebCourses regularly.