CSE 8803-MGA: Massive Graph Analysis
Georgia Tech, Fall 2012
Tuesday/Thursday 12:05pm - 1:25pm, CoC Bldg. 102
Instructor:
Dr. David A. Bader
Office: KACB 1320
Office Hours: Tuesday 9:25am - 10:25am
Teaching Assistant: Abhishak Abhishak, aabhishek3@gatech.edu
TA Office Hours: Wednesday 4:00pm - 5:00pm, Klaus Room 3337
Class Mailing List:
Course Description:
Emerging real-world graph problems include detecting community
structure in large social networks, improving the resilience of the
electric power grid, and detecting and preventing disease in human
populations. Unlike traditional applications in computational science
and engineering, solving these problems at scale often raises new
challenges because of sparsity and the lack of locality in the data,
the need for additional research on scalable algorithms and
development of frameworks for solving these problems on high
performance computers, and the need for improved models that also
capture the noise and bias inherent in the torrential data streams.
In this course, students will be exposed to the opportunities and
challenges in massive data-intensive computing for applications in
computational biology, genomics, and security.
This course will introduce students to designing high-performance and
scalable algorithms for massive graph analysis. The course focuses on
algorithm design, complexity analysis, experimentation, and
optimization, for important ``big data'' graph problems. Students
will develop knowledge and skills concerning:
- the design and analysis of massive-scale graph algorithms employed
in real-world data-intensive applications, and
- performance optimization of applications using the best
practices of algorithm engineering.
Course Information:
Additional Readings:
