CS 498

Spring 2013 Part of Term 1

Part of Term 1
Jan 14-May 1

Special Topics

Credit: 0 TO 4 hours.

Subject offerings of new and developing areas of knowledge in computer science intended to augment the existing curriculum. See Class Schedule or departmental course information for topics and prerequisites.

May be repeated in the same or separate terms if topics vary.

My Favorites

My Schedule

Section Status updates every 10 minutes.

CS 498 class schedule data for spring 2013
CRN	Type	Section	Time	Day	Location	Instructor	Section Details
31601	Lecture	CC3	11:00AM -12:15PM	WF	1310 Digital Computer Laboratory	Campbell, R	Part of Term: 1 Date Range: 01/14/13-05/01/13 Credit: 3 hours Section Title: Cloud Computing Section Info: CS498 Cloud Computing Topic: This course serves as an introduction to Cloud Computing. The class includes Infrastructure as a Service, Software as a Service, and Platform as a service, Map Reduce and Big Data, as well as privacy and legal issues. The class will include the problems and solutions to cloud computing, including hands on laboratory experiments (Hadoop, Hive, Storm, Hbase, ?). Topics include scheduling, resource allocation, energy efficiency, security and monitoring, availability and consistency, data center networks, pricing model, applications and extensions of the cloud platform. Case studies will be drawn from Yahoo, Google, Twitter, Facebook, scientific computation, data mining and machine learning.
59276	Lecture	CC4	11:00AM -12:15PM	WF	1310 Digital Computer Laboratory	Campbell, R	Part of Term: 1 Date Range: 01/14/13-05/01/13 Credit: 4 hours Section Title: Cloud Computing Section Info: CS498 Cloud Computing Topic: This course serves as an introduction to Cloud Computing. The class includes Infrastructure as a Service, Software as a Service, and Platform as a service, Map Reduce and Big Data, as well as privacy and legal issues. The class will include the problems and solutions to cloud computing, including hands on laboratory experiments (Hadoop, Hive, Storm, Hbase, ?). Topics include scheduling, resource allocation, energy efficiency, security and monitoring, availability and consistency, data center networks, pricing model, applications and extensions of the cloud platform. Case studies will be drawn from Yahoo, Google, Twitter, Facebook, scientific computation, data mining and machine learning. Restriction(s): Restricted to Graduate - Urbana-Champaign.
56907	Lecture	DP3	10:00AM -10:50AM	MWF	1109 Siebel Center for Comp Sci	Padua, D	Part of Term: 1 Date Range: 01/14/13-05/01/13 Credit: 3 hours Section Title: Intro to Parallel Programming Section Info: Topic: Intro to Parallel Programming for Computer Scientists and Computer Engineers. Parallel programming notations for shared and distributed memory machines, memory models, atomic operations, race conditions, synchronous and asynchronous computations, performance evaluation, parallel algorithms including graph algorithms, sorting, numerical linear algebra, and FFT. This section is for undergraduate or graduate students.
56908	Lecture	DP4	10:00AM -10:50AM	MWF	1109 Siebel Center for Comp Sci	Padua, D	Part of Term: 1 Date Range: 01/14/13-05/01/13 Credit: 4 hours Section Title: Intro to Parallel Programming Section Info: Topic: Intro to Parallel Programming for Computer Scientists and Computer Engineers. Parallel programming notations for shared and distributed memory machines, memory models, atomic operations, race conditions, synchronous and asynchronous computations, performance evaluation, parallel algorithms including graph algorithms, sorting, numerical linear algebra, and FFT. This section is for graduate students only. Restriction(s): Restricted to Graduate - Urbana-Champaign.
52301	Lecture	MG3	12:30PM -1:45PM	TR	1302 Siebel Center for Comp Sci	Garzaran, M	Part of Term: 1 Date Range: 01/14/13-05/01/13 Credit: 3 hours Section Info: Topic: Performance Oriented Programming. Prerequisite: CS 225 and CS 232. The focus of this course is the study of techniques for the implementation of efficient computations in terms of time and power consumption. Specific topics include: performance monitoring tools and techniques, program analysis and transformations for performance improvement, locality enhancement, multi-core processing, programming multimedia extensions, algorithm selection, and autotuning. This section is for undergraduate or graduate students.
52302	Lecture	MG4	12:30PM -1:45PM	TR	1302 Siebel Center for Comp Sci	Garzaran, M	Part of Term: 1 Date Range: 01/14/13-05/01/13 Credit: 4 hours Section Info: Topic: Performance Oriented Programming. Prerequisite: CS 225 and CS 232. The focus of this course is the study of techniques for the implementation of efficient computations in terms of time and power consumption. Specific topics include: performance monitoring tools and techniques, program analysis and transformations for performance improvement, locality enhancement, multi-core processing, programming multimedia extensions, algorithm selection, and autotuning. This section is for graduate students only. Restriction(s): Restricted to Graduate - Urbana-Champaign.
58505	Lecture	SK3	12:30PM -1:45PM	TR	1214 Siebel Center for Comp Sci	King, S	Part of Term: 1 Date Range: 01/14/13-05/01/13 Credit: 3 hours Section Title: Art and Science of Web Progrm
58506	Lecture	SK4	12:30PM -1:45PM	TR	1214 Siebel Center for Comp Sci	King, S	Part of Term: 1 Date Range: 01/14/13-05/01/13 Credit: 4 hours Section Title: Art and Science of Web Progrm Restriction(s): Restricted to Graduate - Urbana-Champaign.
59208	Lecture-Discussion	U	3:30PM -4:50PM	TR	1214 Siebel Center for Comp Sci	Clifton, R	Part of Term: 1 Date Range: 01/14/13-05/01/13 Credit: 3 hours Section Title: Using Tech to Solve Adv Probs Section Info: Meets with ADV 490. This project-based course will allow teams of media and computer science students to use technology platforms to solve problems supplied by industry clients. Each student will bring their expertise to the problem at hand. Media students will learn capabilities and limitations of different technology platforms will learn how the end user will be impacted by technology decisions, and how they can help achieve advertising objectives with their code design. Junior or Senior standing. Computer Science students should have a knowledge of coding in various platforms. Restriction(s): Restricted to Computer Engineering or Computer Science major(s).