This four-hour course address computer systems performance analysis. It introduces the main concepts and techniques needed to plan the capacity of computer systems, predict their future performance under different configurations, and design new applications that meet performance requirements. The course is mainly based on the use of analytic queuing network models of computer systems. These techniques are applied to study the performance of centralized, distributed, parallel, client/server systems, Web server and e-commerce site performance. The course provides the students with hands-on experience in performance evaluation through a project. The concept and applications of software performance engineering are also covered.

Course Topics:

• Computer System Lifecycle
• From Systems to Descriptive Models
• Quantifying Performance Models
• Performance Engineering Methodology
• Case Study I: A Database Service
• Multiclass Open Queuing Network Models
• Case Study II: A Web Server
• Multiclass Closed Queuing Network Models
• Case Study III: A Data Center
• Markov Models
• Case Study IV: An E-Business Service
• Case Study V: A Help-Desk Service
• Queuing Networks with Load Dependent Devices.
• Non-Product Form Queuing Network Models

Course resources

• Calendar
• Recommended Textbook:
  • Performance by Design: Computer Capacity Planning by Example, by Daniel A. Menasce, Virgilio A.F. Almeida, and Lawrence W. Dowdy
• Optional books:
  • Capacity Planning for Web Services: Metrics, Models, and Methods by Daniel A. Menasce and Virgilio A.F. Almeida
  • The Art of Computer Systems Performance Analysis by Raj Jain
  • Introduction to Computer System Performance Evaluation by K. Kant
  • The Art of Measurement by Ronald W. Potter
• Additional readings (papers) will be made available during the course of the semester.

People:

• Instructor: Eileen Kraemer, eileen@cs.uga.edu .

Times and Places

• Class is held T/T 2:00-3:15 in Conner 210 and W 2:30-3:20 in GSRC 306.
• Office hours are immediately after class on Tuesday and Thursday.

Course Policies

• Policy on Collaboration
• Late Policy
• Grading Policy