- Catalog Number: 33058
- Lectures/Discussion: 3150 DOW, MW: 12:00 PM – 1:30 PM
- Projects/Makeup: 1200 EECS, F 12:00 PM – 1:00 PM
| Member (uniqname) | Role | Office Hours |
|---|---|---|
| Mosharaf Chowdhury (mosharaf) | Faculty | 4820 BBB. By appointments only. |
| Peifeng Yu (peifeng) | GSI | BBB Learning Center, F 1:00 PM - 3:00 PM |
ALL communication regarding this course must be via Piazza. This includes questions, discussions, announcements, as well as private messages.
Presentation slides and paper summaries should be emailed to eecs598-bigdata-staff@umich.edu.
This class will introduce you to the key concepts and the state-of-the-art in big data systems and encourage you to think about either building new tools or how to apply an existing one in your own research.
Since datacenters and cloud computing form the backbone of modern big data systems, we will start with high-level overviews of the two and discuss emerging trends in both software and hardware. We will then take a deep dive into the big data systems landscape, focusing on different types of problems. A large part of the course this year will focus on the emerging AI systems that include software systems for machine learning, deep learning, and reinforcement learning. We will cover topics from top conferences in systems, networking, and databases venues.
Students are expected to have good programming skills and must have taken at least one undergraduate-level systems-related course (from operating systems/EECS482, databases/EECS484, distributed systems/EECS491, and networking/EECS489).
Undergraduates must receive explicit permission from the instructor to enroll, if space permits.
This course has no textbooks. We will read recent papers from top venues to understand trends in big data systems and their applications.
- Mandatory: Must read and review.
- Optional: Should read. No review.
- Companion: Mandatory for presenters. Optional for the rest.
The Engineering Honor Code applies to all activities related to this course.
All activities of this course will be performed in groups of 3 students for the Assignment track.
Declare your group's membership as well as preferences for track and papers by January 14, 2019. After this date, we will form groups from the remaining students.
Note that there will be an equal number of groups in each of the two tracks. Declared track preference does not guarantee a specific track assignment.
Similarly, paper preferences are also only hints.
The course will be conducted as a seminar. Only one group will present in each class. Each group will be assigned to present two papers (mandatory and companion) on the same day at least once throughout the semester. Presentations should last at most 45 minutes without interruption. However, presenters should expect questions and interruptions throughout. In the presentation, you should:
- Motivate the paper and provide background.
- Present the high level idea, approach, and/or insight (using examples, whenever appropriate).
- Discuss technical details so that one can understand the key details without carefully reading it.
- Explain the difference between this paper and related work.
- Raise questions throughout the presentation to generate discussion.
The slides for a presentation must be emailed to the instructor team at least 24 hours prior to the corresponding class. You should use this template for making your slides in powerpoint.
Read all the papers of each day carefully and write your own paper review. Being able to critically judge others’ work is crucial for your understanding. For papers that require summaries, you must address a number of questions including:
- What is the problem addressed by the paper, and why is this problem important?
- What is the hypothesis of the work?
- What is the proposed solution, and what key insight guides their solution?
- What is one (or more) drawback or limitation of the proposal, and how will you improve it?
The paper reviews of each day must be submitted electronically at least 24 hours prior to the corresponding class. Late reviews will not be counted. You can miss up to 4 paper reviews during the term without penalty. Each missing review beyond the fourth one will result in 25% decrease in grade for paper reviews. Meaning, failing to turn in 8 or more reviews on time will result in a zero for all paper reviews.
The grade for this part will be assigned as follows: at the end of the term, 2 of your reviews will be randomly selected and graded. The higher grade of the two will be used for grading.
Submit reviews via HotCRP.
You are expected to attend all lectures (you may skip up to 2 lectures due to legitimate reasons), and more importantly, participate in class discussions.
If your group is in the assignment track, you will have to complete two assignments on popular big data frameworks Apache Spark and TensorFlow. The third assignment will likely be different for each group with specific goals, and this will resemble a small research exploration project. Details of the assignments will be available over time. Tentative deadlines for the assignments are February 13, March 27, and April 22.
If your group is in the research track, you will have to complete substantive work an instructor-approved problem and have original contribution. Surveys are not permitted as projects; instead, each project must contain a survey of background and related work. You must meet the following milestones (unless otherwise specified in future announcements) to ensure a high-quality project at the end of the semester:
- Turn in a 2-page draft proposal (including references) by January 30. Remember to include the names and Michigan email addresses of the group members.
- Keep revising your initial idea and incorporate instructor feedback. However, your team and project proposal must be finalized and approved on or before February 13.
- Each group must submit a 4-page mid-semester progress report and present mid-semester progress during class hours on the week of March 27.
- Each group must present their final results during a presentation or poster session on April 22.
- Each group must turn in an 8-page final report and your code via email on or before 11:59PM EST on April 26. The report must be submitted as a PDF file, with formatting similar to that of the papers you've read in the class. The self-contained (i.e., include ALL dependencies) code must be submitted as a zip file. Each zip file containing the code must include a README file with a step-by-step guide on how to compile and run the provided code.
| Assignment Track | Research Track | |
|---|---|---|
| Paper Summary | 20% | 20% |
| Paper Presentation | 20% | 20% |
| Participation | 10% | 10% |
| Assignment 1 | 15% | - |
| Assignment 2 | 15% | - |
| Assignment 3 | 20% | - |
| Research Proposal | - | 10% |
| Mid-Semester Checkpoint | - | 15% |
| Final Report | - | 25% |