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Lecturer:
Professor James Demmel
- email to demmel@cs

Office: 564 Soda, 643-5386; also 831 Evans

Lectures: **WF 9:30-11:00 (306 Soda) **

Office hours: W 1-2 and Th 1:30-2:30 (**note change**) in 564 Soda, or by appointment

TAs:

Please send questions about homework to all 3 instructors (professor and TAs) by using the newsgroup or by emailing cs170@inst.eecs.berkeley.edu; you are likely to get a faster answer that way. Instructions to access the newsgroup are available here.

**Enrollment:** Please send all queries to
Michael-David Sasson.

Please send questions about homework to all instructors by using the newsgroup or by emailing cs170@inst.eecs.berkeley.edu; you are likely to get a faster answer that way. Instructions to access the newsgroup are available here.

The (roughly weekly) homework sets (and solutions) will be posted here as the term progresses.

In general, problem sets will be assigned on Wednesday and will be due Friday the following week at 4pm in the boxes in 283 Soda Hall. Make sure to put your name, SID, course name (CS170), homework number, TA's name, and section number on the first page, and staple all the pages together.

For homework questions that involve designing and analyzing algorithms, we require a specific format for the answers (to both help you organize your thoughts and help the readers grade your answers), that you can find here.

You are encouraged to work on homework problems in study groups of 2 to 4 people. But you must write up your own solutions, and not read or copy the solutions of other students. You may use books or on-line resources to help solve homework problems, but you must credit all such sources in your writeup and you must not copy material verbatim. See also the discussion of grading and academic honesty below. We believe that most students can distinguish between helping other students and cheating. Explaining the meaning of a question, discussing a way of approaching a solution, or collaboratively exploring how to solve a problem within your group is an interaction that we encourage. On the other hand, you should never read another student's solution or partial solution, nor have it in your possession, either electronically or on paper. You must never share your written solutions, or a partial solutions, with another student, even with the explicit understanding that it will not be copied. You should write your homework solution strictly by yourself. You must explicitly acknowledge everyone who you have worked with or who has given you any significant ideas about the homework. Not only is this good scholarly conduct, it also protects you from accusations of theft of your colleagues' ideas.

**Warning:** Your attention is drawn to the Department's
Policy on Academic Dishonesty.
In particular, you should be aware that
copying or sharing solutions, in whole or in part, from other
students in the class *or any other source* without acknowledgment
constitutes cheating. Any student found to be cheating risks automatically
failing the class and being referred to the Office of Student Conduct.

No late homework will be accepted, since the answers will be posted on the web immediately afterwards. Instead, the lowest 3 homework scores will be dropped.

It was developed from a set of notes especially for
this course, and we will follow it fairly closely.
The previous text book was *Introduction to Algorithms*
by Cormen, Leiserson and Rivest, which is still a good
reference.

**Prerequisites:**
The prerequisites for this course are CS 61B, and either CS 70
or Math 55. In particular you should be comfortable with
mathematical induction, big-O notation, and
basic data structures. If you need to refresh any of
this material, refer to the relevant sections of the textbook.
We assume that you are familiar with a standard
imperative programming language like C, C++ or Java, so that
you can read and write the algorithms presented in the course.

Before this textbook became available, I posted very detailed lecture notes for each lecture on this web page. The availability of this textbook means the notes will mostly point to the sections of the book covered, but I will continue to post more detailed notes of material not in the book.

Tentative schedule and Lecture Notes

- (1/20) Lecture 1: Course Overview, and Computing Fibonacci Numbers (Chap 0 in text)
- (1/22) Lecture 2: Solving Recurrences, begin Divide \& Conquer (Chap 2 in text)
- (1/27) Lecture 3: Continue with Divide \& Conquer, introduce parallelism (Chap 2 in text)
- Additional lecture notes on parallelism in divide \& conquer and sorting (in pdf)
- (1/29) Lecture 4: Continue with Divide \& Conquer, parallelism, matrix multiplication
(Chap 2 in text)
- Additional lecture notes on memory hierarchies and matrix multiplication (in pdf).
- (2/3) Lecture 5: Continue with Divide \& Conquer, matrix multiplication, FFT
(Chap 2 in text)
- Matlab source code for music extraction demo
- Matlab source code for image compression demo
- (4/30) Last Lecture: Graph Partitioning (in powerpoint)

- Homeworks - 25%
- Quizzes - 5%
- 2 Midterms - 20% each
- Final - 30%

The final exam is scheduled for May 14, 8-11am. A makeup final will only be given for

- unexpected circumstances beyond your control, documented by a signed note from a physician or equivalent,
- a religious holiday, or
- conflict with another scheduled exam (ask the other professor first, and try to avoid this!!).

You are required to a bring a student photo ID and blue-covered exam book to the exams.

There will be a short quiz at the beginning of (most) sections. The quiz will consist of a few simple questions related to the material from the previous class. There will be no make-up quizzes but the two lowest quiz scores will be dropped. The motivation is to encourage you to keep up with lectures.

Regrading of homework, quizzes or exams will be done when there has been a mistake, in order to make sure all students are graded consistently. To ask for a regrade, you must return the work to your TA within one week of getting it back, along with a written note (on another piece of paper) explaining the problem. The entire assignment may be regraded in this case.