CSE 221: Graduate Operating Systems
Fall 2025
- Instructor
-
Amy Ousterhout
aousterhout@ucsd.edu
CSE 3130
- Lectures
-
Tu/Th 3:30–4:50pm
Mosaic 0204
- Teaching Assistant
- Tianyi Shan
- Office Hours
-
Amy: Wed 1:00-1:50 pm (or by appointment)
Tianyi: Mon 1:00-2:00 pm in CSE 2236 or on Zoom (https://ucsd.zoom.us/my/tshan)
- Textbook
- This course does not have a required textbook.
However, I strongly recommend using an undergraduate operating systems
textbook as a reference. Any reasonably recent OS textbook will
suffice, such as:
- Platforms
- Piazza, Gradescope, Canvas
- Prerequisites
- CSE 120 or equivalent (e.g., an OS course at your undergraduate institution)
- Enrollment
- Graduate students - complete this Google Form if you are interested in enrolling. You will be given a chance to enroll as space becomes available.
Undergraduate students - submit an EASy request. Your request will be processed in week 1 or 2 if space permits (graduate students are prioritized for enrollment in graduate courses).
Note: The format of this course is somewhat unusual. It is a highly interactive discussion-based course with significant class participation. As a result, students are expected to attend lectures and engage in person. Lectures will not be recorded. See the "Class Participation" section below for more details.
Course Objectives
The purpose of this course is to teach computer software system
structures from a design point of view. We will look at different
structuring techniques, and we will examine their usage in both
important historical systems and in modern systems.
In addition to learning about different system structures and
different operating systems, you will learn:
- How to read a research paper in an objective manner.
- How to write a critical analysis of the research described in a paper.
- How to articulate your understanding of and insights into a research paper.
- How to synthesize research themes and topics across multiple papers.
Reading List
The course does not have a textbook. Instead, the course material
will come from seminal, noteworthy, or representative papers from the
literature. Each lecture (except the first) will have two assigned
papers to read. You should read these papers before coming to
class, and be prepared to discuss them (written evaluations are not
required). Occasionally we will also list recommended papers; you are
encouraged to read those, but not required. Students often find it
useful to discuss papers together before the class period, and we
encourage the practice (see more on collaboration below).
Class Participation
The structure of this course is unusual in that there are no
slide-based presentations during the class period. Instead, we will
discuss research papers that we will have all read before each class
period.
I will lead the lecture discussions by asking questions of
students at random in class. Note that your answers to these
questions form a part of your overall grade, so it is important that
you both show up to class as well as read the papers carefully. To
give you some structure for reading through the papers, keep the
following questions in mind and ask yourself how you would answer
these questions about each paper:
- What problem does the paper address?
- How is it different from previous work, if any?
- What is the approach used to solve the problem?
- How does the paper support or otherwise justify its arguments and conclusions?
- Was the paper, in your judgement, successful in addressing the problem?
To grow accustomed to the unusual format of this class, you will
not be graded on class participation during the first two weeks of
class.
You might have to miss class for one reason or
another (e.g., travel, interview, illness).
Since you will not be in class
to participate in discussion, to help motivate you to make sure you
stay on top of the readings I ask that you write a brief evaluation
of the papers for the class that you will miss. For the evaluation,
briefly answer the above questions about the papers.
Your evaluation should be concise, with just one to a few
sentences per question. Also, below each paper on the reading list
is a question specific to the paper topic. Please conclude your
evaluation by answering this question if present. Email your
evaluations to me within two days of the missed class.
Homework
We will have a few written homeworks.
The homeworks serve as good
practice for thinking about papers and answering questions found on
the final.
Please submit your homework on time. Unless you make arrangements
with me ahead of time, we will reduce homework grades by 20% for each day
that they are late.
Project
In the course project, students will measure various aspects of system
performance on a platform of their choice.
Exam
We will have one exam at the end of the quarter. Questions on the
exam will be similar to some of the questions on the homework and in
the reading list. The exam is closed notes with a one-page (double-sided)
"cheat sheet". You can use this past exam as an example of the kinds
of questions to expect:
- Fall 2003 (Note: This exam was taken in an 80-minute exam period)
MS students: Note that the CSE 221 final exam satisfies the
MS competency exam (the passing threshold is B- or higher). You do not
need to take a separate comps exam.
Grading
The grading breakdown for the course is:
- Class participation: 15%
- Homework: 20%
- Project: 30%
- Final: 35%
Collaboration
Papers. I strongly encourage you to discuss the papers with
other students in the class — you may have insights that others
do not, and vice versa. Often students form reading groups, which I
heartily encourage. Note that group discussion, however, is not an
effective substitute for actually reading the paper.
Homework. You can also discuss the homework problems, but
you must independently complete the assignments yourself. As a rule
of thumb, you can discuss a homework problem in the lounge with
others, walk home, wash the dishes, and then write up your answer to
the problem on your own. You cannot, however, discuss homework
problems with others and then write your answers to those problems at
the same time.
Project. You can complete the course project as a team. You
can discuss project materials with others in the course, but your code
must have been authored exclusively by members of your team; you may
not copy code from another team, copy code from an AI tool, or make
your code available to others.
Exam. The exam is an individual effort.
You are expected to be aware of UCSD's academic
honesty guidelines. Any violation of the course or university
policies will be treated very seriously, and could lead to severe
repercussions. Don't cheat. It's not worth it.
Generative AI Policy
Generative AI tools such as ChatGPT, Claude, and Gemini are powerful
resources. You may use these tools in this course, but only as a way to
enhance your learning and not as a substitute for learning.
For example, you may ask these tools the kinds of questions that you
might have asked a search engine in the past, such as "what is the
difference between a lock and a sempahore?" or "how can I create a table
in latex?"
Here are some examples of ways in which you may not use generative AI tools:
- Asking an AI tool to summarize a research paper
- Asking an AI tool to answer a homework question and submitting
the answer as your own work
- Asking an AI tool to write a benchmark for the project and submitting
that code as your own work
- Asking an AI tool to generate text for your project report and
submitting that as your own work
In each of these examples, use of an AI tool prevents you from learning a
skill that this course aims to teach.
You are responsible for all work that you submit in this course and
may be asked to explain your approach to the instructor or TA.
If you are found to have violated the policy above,
you (and your teammates if applicable) will receive a zero on the portions of
the assignments that you used generative AI for. If you have any questions
about this policy, please do not hesitate to ask.
