Units:

12

Description:

In designing computer systems one is usually constrained by certain performance requirements. For example, certain response times or throughput might be required of the system. On the other hand, one often has many choices: One fast disk, or two slow ones? What speed CPU will suffice? Should we invest our money in more buffer space, or a faster processor? Which migration policy will work best? Which task assignment policy will work best? How can we redesign the scheduling policy to improve the system performance? Often answers to these questions are counter-intuitive. Ideally, one would like to have answers to these questions before investing the time and money to build a system. This class will introduce students to analytic stochastic modeling with the aim of answering questions such as those above. Topics covered include Operational Laws, Markov Chain Theory, Queuing Theory, Modeling Empirical Loads, Simulations, and Management of Server Farms.

In Fall 2019 this course is broadcast to the Silicon Valley campus. ECE Silicon Valley students attend classes synchronously with students in Pittsburgh.

Last Modified: 2019-05-29 10:35AM

Semesters offered:

• Fall 2019
• Spring 2019
• Fall 2018
• Fall 2017
• Fall 2016
• Spring 2015