CS 689-002 Spring 2007
CS 689 University Handbook Description
Advanced topics in numerical analysis, scientific computation, and complexity of continuous problems. Specific topics may include, but are not limited to: iterative methods, advanced parallel algorithms in numerical linear algebra, multivariate function approximation and integration.
Prerequisites: CS-537 or an equivalent or the instructor's consent.
Specific Course Description for this Term
Dynamic Data-Driven Application Systems (DDDAS) is a paradigm whereby applications (or simulations) and measurements become a symbiotic feedback control system. DDDAS entails the ability to dynamically incorporate additional data into an executing application, and in reverse, the ability of an application to dynamically steer the measurement process. Such capabilities promise more accurate analysis and prediction, more precise controls, and more reliable outcomes. The ability of an application to control and guide the measurement process and determine when, where, and how it is best to gather additional data has itself the potential of enabling more effective measurement methodologies.
In this course, we will study several successful DDDAS applications that are extensively documented through the DDDAS community web site, http://www.dddas.org. DDDAS is already in use in Lexington: the entire traffic light system is run using a single computer cluster, a dynamic data-driven commodity transportation application, and a large number of sensors under many strategic streets.
No prior knowledge of DDDAS is assumed nor knowledge of high level mathematics or computational sciences. This will be a self contained class. We will construct at least one DDDAS during the course in part based on the background of the students.
Requirements, Goals, and Friendly Advice
You need to understand the concept of a rate of change (i.e., a derivative in math terms). If you understand this simple concept, you can get through the course. The textbook is self contained and assumes that the material is completely new to the reader. There is good motivational material in the book, useful references, and examples to make concepts more obvious.
The goal at the end of this course is that you will know why using dynamic data and models is more useful than the traditional take some random data and run a computer into the ground until it gives one, and only one, prediction for some phenomena. Then keep repeating with another random data set until the computer eventually fails or is replaced with a faster one (then the data sets can get bigger). Repeat all until you retire or change jobs.
The friendly advice is as follows:
- Always come to class unless you are sick (in which case, do not come to class).
- Raise your hand and participate in class discussions often.
- Interrupt lectures if you do not understand or agree with something.
- Do your work on time (i.e., do not tell me your flowering pine tree ate your homework).
Textbook(s) and Suggested Reading
There is one traditional textbook that you are expected to read cover to cover:
- Angela B. Shiflet and George W. Shiflet, Introduction to Computational Science: Modeling and Simulation for theSciences, Princeton University Press, 2006, ISBN 0691125651.
Web page: http://www.wofford-ecs.org/IntroComputationalScience/index.htm
Office Hours and Contact Information
My office hours will be on Tuesdays 11:00-12:00 and Wednesdays 10:00-11:00 (and subject to cancellation occasionally).
My office is 514H RMB (the building formerly known as the Robotics building). My office telephone number is 257-2438 and the eFAX is +1-203-547-6273. Feel free to telephone my office as late as 6:00pm. In a pinch, I can be reached at home on Friday evenings and weekends only at +1-203-625-9449 (this is in Connecticut, not Kentucky). Please do not call me at home before 9:00 am or after 9:00 pm. I respond to e-mail (Craig.Douglas@uky.edu) fairly quickly (always include a phone number where I can call you back and CS689 in the subject). If you are stuck on something, please do not hesitate to contact me. Please be utterly brazen.
Your grade will be based entirely on the homework.
It is quite easy to either cheat or plagiarize in any course, even by accident. Do not exchange code, homework, or projects unless you have been explicitly told it is alright to do so. Do not swap printed or electronic versions either. Do not look over a shoulder and take notes. Do not try to be a lawyer and find a clever way of doing something similar to these examples. Getting caught cheating or plagiarizing will result in a grade of E and possibly much worse, including expulsion from the university and legal proceedings against you. I have zero tolerance for cheaters. There are enough interesting things to do in life without experiencing being tossed out of school.