CS 6240: Large-Scale Parallel Data Processing

Covers big-data analysis techniques that scale out with increasing number of compute nodes, e.g., for cloud computing. Focuses on approaches for problem and data partitioning that distribute work effectively while keeping total cost for computation and data transfer low. Deterministic and random algorithms from a variety of domains, including graphs, data mining, linear algebra, and information retrieval, are studied and analyzed in terms of their cost, scalability, and robustness against skew. Coursework emphasizes hands-on programming experience with modern state-of-the-art big-data processing technology. Students who do not meet course prerequisites may seek permission of instructor.


News

Most aspects of the course are managed through Blackboard (northeastern.blackboard.com). However, we use Piazza for all online discussions (https://piazza.com/northeastern/fall2018/cs6240/home). Please sign up right away at piazza.com/northeastern/fall2018/cs6240. Do not email your course-related questions. Instead, post everything on Piazza. There is also an option for private posts that can only be seen by instructors and TAs.


Course Material

Please read the syllabus carefully.

Go to this page for the online modules. Please make sure you go through the material before the week it is discussed in class.

Office Hours

Mirek: Tuesday 1:45-3:30pm in 448 WVH. I am also available during the break and right after class. If you cannot make during office hours, request an appointment through Piazza private post.

Yogesh Gupta: Friday 1:30-3:30pm in 4th floor corridor of WVH (check notes on door of 472 WVH)

Rundong Li: Monday 10am-noon in 472 WVH (or right outside in the hallway)

Amul Mehta: Thursday 5-6pm, Friday 11:30am-12:30pm in 4th floor corridor of WVH (check notes on door of 472 WVH)

Xiaofang Yang: Wednesday 4:30-6:30pm in 472 WVH (or right outside in the hallway)

Important dates

Week Start date Comments
1 Sep 3  
2 Sep 10  
3 Sep 17  
4 Sep 24  
5 Oct 1  
6 Oct 8 No class Oct 8 (Columbus Day)
7 Oct 15  
8 Oct 22  
9 Oct 29  
10 Nov 5  
11 Nov 12 No class Nov 12 (Veterans Day)
12 Nov 19 Exam week (Monday, Tuesday); no class Nov 21-23 (Thanksgiving)
13 Nov 26  
14 Dec 3  
15 Dec 10 Project presentations (by default on both class meeting days)