CS252A Policies

Description
Communication
Course Components
Student Support
1. Office Hours
2. Accommodations and Extensions
Grading
Collaboration and Ethics
Use of LLMs
Inclusion
Acknowledgements

Description

This course provides a graduate survey of contemporary computer organizations covering: early systems, CPU design, instruction sets, control, processors, busses, ALU, memory, I/O interfaces, connection networks, virtual memory, pipelined computers, multiprocessors, and case studies. Term paper or project is required.

Communication

The course schedule and all resources (e.g. lecture slides, discussion worksheets) will be posted on the course website.

All course announcements and content/logistics questions will happen on Ed (the course discussion forum). We will be automatically enrolling everyone.

If you need to contact the course staff privately, please make a private question on Ed.

Course Components

Lectures

Identical to the CS 152 lecture and time conflict policies.

Discussions

TAs will hold weekly 2-hour live discussions throughout the week. Discussion sections start on the second week of classes and will be taught by 2 TAs. Discussion attendance is optional, but highly encouraged.

Paper Readings and reading discussion section

Every week, CS 252A will meet for a special 1.5 hour paper reading discussion. The discussion time is TBD and will be decided during the first week of class based on peoples’ availability. During each session, we will either: discuss 2 papers or discuss/present on a milestone related to the final semester project.

For each assigned reading, students are expected to submit a summary demonstrating their understanding of the paper contents. Paper summaries should be submitted to HotCRP. Each summary should include one paragraph summarizing the main content of the paper including good/bad points, plus 1-3 questions to contribute to the in-person paper discussion.

Each paper will be presented by one student (assigned ahead of time). This student will give a short presentation of the paper (12-15 min), conference-style, and moderate subsequent discussion.

Exams

Identical to the CS 152 exam policies.

Class Project

The course will feature a substantial research project done by pairs of students, with a 10-page conference-style paper and class presentation.

Student Support

Office Hours

Office hours will be in-person. See the course calendar on the website for the office hours schedule. Office hours start on the second week of classes. For help with assigned readings and the final project, please attend office hours for TAs with the “GSI” tag on the staff page. TAs without the “252a” tag have not taken 252a and will therefore not be familiar with 252a-specific content.

Accommodations and Extensions

As instructors, our goal is to teach you the material in our course. The more accessible we can make it, the better. If you encounter any extenuating circumstances, please let us know as soon as possible so we can best help you succeed in the class.

If you ever need an extension during the semester, please make a private Ed post.

The Disabled Students’ Program (DSP) supports disabled students at UC Berkeley. They offer a wide range of services and accommodations. If you are facing barriers in school due to a disability, apply to DSP! Students registered with DSP can expect to receive an onboarding email within a week of sending us your formal letter of accommodation through the AIM portal.

Grading

Overall grades will be determined from:

Paper Readings (20%)
Exams (30%)
- Midterms: 12% each
- Quiz: 6%
Class Project (50%)

Staff may adjust grades upward based on class participation or extenuating circumstances. The grade of A+ will be awarded at staff discretion based on exceptional performance.

If you are taking the class P/NP, you will need to attain a letter grade of C- or higher AND take the final to pass. If you are a graduate student taking the class SUS, you will need to attain a letter grade of B- or higher AND take the final to pass.

Class grades will be compliant with the Departmental Grading Guidelines for Graduate Courses

Collaboration and Ethics

Please note that obtaining, sharing, and posting solutions to any assignment is a violation of academic integrity. This includes uploading project code, official solutions, your own solutions, etc. to any site that is accessible by other people, such as a public GitHub repository.

Problem Set submissions should acknowledge all collaborators and sources consulted.

All code and written responses should be original. We trust you all to submit your own work, but to protect the integrity of the course from anyone who doesn’t want to play by the rules, we will actively be checking for code plagiarism (both from current classmates and previous semesters), as well as written homework submissions that look eerily similar.

You may use a small, generic code snippet from a website such as Stack Overflow—for example, code that capitalizes a string—but you must cite the source in an adjacent code comment.

Use of LLMs

We believe that the most effective way to learn the course material is to engage with it yourself. If you are stuck on an assignment or concept, we strongly encourage you to ask course staff on Ed or attend office hours. Large language models (LLMs) can produce convincing but incorrect explanations and can easily bypass the work that an assignment is designed to teach.

LLM use is therefore permitted only with caution and for restricted cases. Unless explicitly stated, the following policy applies to all course-related use of chatbots, code assistants, IDE integrations, and similar generative AI tools.

Appropriate Uses

You may use an LLM to clarify general concepts or terminology without sharing course materials or work from your submission. Examples include:

“Why are pointers useful in C?”
“What is a PRF?”
“What is the difference between cache coherence and memory consistency?”
“What does this compiler error mean?” when the prompt does not include substantial assignment text or solution code.
“Show a short C example that reads one character from a file.”
“Show how an array can be declared in Chisel.”

Cautionable Uses

You may ask for more substantial examples that are not tailored to a course assignment, but you must exercise caution. For example:

“Show a generic Chisel implementation of a parameterized arbiter.”
“Show a short C++ snippet that updates a two-bit saturating counter based on a Boolean outcome.”

If AI-generated code, prose, a diagram, or a substantive idea influences anything you submit, you must clearly cite it where it is used. For code, include an adjacent comment naming the tool and identifying the generated or adapted portion. Retain the relevant prompt and output because course staff may ask to review them. You remain responsible for understanding and verifying everything in your submission. Citation does not make an otherwise prohibited use acceptable.

Prohibited Uses

You may not use an LLM to avoid the intellectual work required by an assignment. In particular, you may not:

Ask an LLM to design or solve an assignment task or to generate an answer, implementation, report, paper summary, or lab analysis.
Give your solution code or written response to an LLM for debugging, review, completion, rewriting, or refactoring.
Submit generated material
Use an LLM during a quiz or exam.

These restrictions include tools such as automatic code completion, built-in IDE assistants, and agents that inspect or modify your assignment files. Any submissions containing generated content or signs of prohibited use will receive a 0.

If an LLM gives you an explanation that seems questionable, please ask course staff about it on Ed or in office hours. You will not be penalized for bringing us an AI-generated claim to check; course staff and official course materials remain the authoritative sources for this class.

Exams are expected to demonstrate your work, and your work alone. We have a zero-tolerance policy for any form of collaboration on exams. We are not lenient about cheating. Caught students will be reported to the Center for Student Conduct and will be assigned an “F” in the class. Please, just don’t cheat. It’s not cool, and penalties for graduate students tend to be stricter than those for undergrads.

We sympathize with Kris Pister’s policy.

Inclusion

We believe in the crucial importance of creating a learning environment that is welcoming and respectful to students of all backgrounds. The following are specific steps that will help us in achieving this goal:

If you feel your academic performance has been impacted negatively due to a lack of inclusion, or due to experiences outside of class such as current events or family matters, please reach out to the instructors and staff. Our job is not only to teach but to support you in every way we can.
If something happens in the course that runs counter to the goal of making every student feel safe, respected, and welcome, please contact the head TA or the instructors; if you don’t feel comfortable contacting course staff, you can fill out this form to anonymously let the department know.
You may also consult a departmental Faculty Equity Advisor, or fill out the anonymous feedback form for the College of Engineering for equity and inclusion related feedback.
If you have a preferred name or set of pronouns that differ from your legal name, you may designate a preferred name for the classroom by following these steps.
As a member of the CS 252a community, realize that you have an important duty to help other students feel respected in helping create an inclusive learning environment.

Acknowledgements

This website and syllabus was inspired by CS188 and CS161, which generously provided its support and source code. Parts of the syllabus are adapted from CS61C.