U.C. Berkeley CS267 Home Page
Applications of Parallel Computers
Spring 2012
T Th 9:30-11:00, 250 and 254 Sutardja Dai Hall
Instructor:
Teaching Assistants:
Nick Knight
Office: 593D Soda Hall (Parlab)
Office Hours: T Th 11:40-12:30 in 576 Soda Hall ("Euclid" room in ParLab)
(send email)
Brian Van Straalen
Office: Parlab, 5th floor, Soda Hall, phone?
Office Hours: T Th 3:00-4:30 in 643 Soda Hall
(send email)
Administrative Assistants:
Tammy Johnson
Office: 565 Soda Hall
Phone: (510)643-4816
(send email)
Roxana Infante
Office: 563 Soda Hall
Phone: (510)643-1455
(send email)
Link to webcasting of lectures
(Active during lectures only; archived video will be posted
here after lecture.)
To ask questions during live lectures, you have two options:
You can email them to
this address,
which the teaching assistants will be monitoring during lecture.
You can use the chat box at the bottom of the webpage of
Class Resources and Homework Assignments.
Syllabus and Motivation
CS267 was originally designed to teach students how to
program parallel computers to efficiently solve
challenging problems in science and engineering,
where very fast computers are required
either to perform complex simulations or to analyze enormous datasets.
CS267 is intended to be useful for students from many departments
and with different backgrounds, although we will assume reasonable
programming skills in a conventional (non-parallel) language,
as well as enough mathematical skills to understand the
problems and algorithmic solutions presented.
CS267 satisfies part of the course requirements for a new
Designated Emphasis ("graduate minor") in
Computational Science and Engineering.
While this general outline remains, a large change
in the computing world has started in the last few years:
not only are the fastest computers
parallel, but nearly all computers will soon be parallel,
because the physics of semiconductor manufacturing
will no longer let conventional sequential processors
get faster year after year, as they have for so long
(roughly doubling in speed every 18 months for
many years). So all programs that need to
run faster will have to become parallel programs.
(It is considered very unlikely that compilers will be
able to automatically find enough parallelism in most
sequential programs to solve this problem.)
For background on this trend toward parallelism, click
here.
This will be a huge change not just for science
and engineering but the entire computing industry,
which has depended on selling new computers by running
their users' programs faster without the users
having to reprogram them. Large research activities
to address this issue are underway at many computer
companies and universities, including
Berkeley's ParLab,
whose research agenda is outlined
here.
While the ultimate solutions to the parallel programming
problem are far from determined, students in CS267 will
get the skills to use some of the best existing parallel programming
tools, and be exposed to a number of open research questions.
Tentative Detailed Syllabus
Grading
There will be several programming assignments to acquaint students
with basic issues in memory locality and parallelism needed for
high performance. Most of the grade will be based on a final project
(in which students are encouraged to work in small interdisciplinary teams),
which could involve parallelizing an interesting application, or
developing or evaluating a novel parallel computing tool. Students
are expected to have identified a likely project by mid semester,
so that they can begin working on it. We will provide many suggestions
of possible projects as the class proceeds.
Asking Questions
Outside of lecture, you are welcome to bring your questions to office hours
(posted at the top of this page). If you cannot physically attend office hours,
you may contact the instructor team via the
instructor email.
We encourage you to post your questions to the
CS267 Piazza page
(sign up first).
If you send a question to the instructor email, we may answer your question
on Piazza if we think it might help others in the class.
During lecture, you can ask questions over the Internet
(see Google Chat link at bottom of the
resources
page). You will submit homeworks via the instructor email -
please check with assignment-specific submission instructions first.
Class Projects
You are welcome to suggest your own class project, but you may also look at
the following sites for ideas:
the ParLab webpage,
the Computational Research Division and
NERSC webpages at
LBL,
class posters from
CS267 in Spring 2010
class posters and their
brief oral presentations from
CS267 in Spring 2009.
Announcements
(Apr 21) The project poster session will be udring the regular lecture
time on Thursday of RRR week, Thursday May 3. We will start in the regular
lecture room, 250 SDH, and videorecord your short summaries of each poster,
after which we will have a regular poster session in the hallway outside.
For the short summaries of each poster, please send me one powerpoint slide
before the session (preferably by the day before, or very early in the morning),so I can put them all on my laptop. Final project reports will be due the
following Monday, May 7, by midnight.
(Mar 2) The link to Richard Gerber's guest Lecture 10 has been repaired.
(Feb 15) Details about Homework 2 have been posted
here,
due Mar 6 by midnight.
(Jan 18) Details about Homework 1 (not to be confused with Homework 0)
have been posted
here,
due Feb 14 by midnight.
Make sure you have completed the (required)
course survey,
so we can assign you your teammate.
Also, please read the "Asking Questions" section above.
(Jan 18) Please read the
NERSC Computer Use Policy Form so that you can sign
a form saying that you agree to abide by the rules state there.
(Jan 17) A corrected pointer to the archived video of the lectures has just been posted (2:36pm).
(Jan 17) Please complete the following class survey.
(Jan 17) We have been assigned 254 SDH (next to the main classroom
250 SDH) as an overflow room, so that we will be able to accomodate
all students on the wait-list.
(Jan 17) Homework Assignment 0 has been posted
here,
due Feb 2 by midnight.
(Jan 17) This course satisfies part of the course requirements
for a new Designated Emphasis ("graduate minor") in
Computational Science and Engineering.
(Jan 17) For students who want to try some on-line self-paced
courses to improve basic programming skills, click
here.
You can use this material without having to register.
In particular, courses like CS 9C (for programming in C) might
be useful.
This will include, among other things,
class handouts, homework assignments,
the class roster, information about class accounts, pointers
to documentation for machines and software tools we will use,
reports and books on supercomputing,
pointers to old CS267 class webpages (including old class projects),
and pointers to other useful websites.
Please read the
NERSC Computer Use Policy Form so that you can sign
a form saying that you agree to abide by the rules state there.
Lecture Notes and Video
Live video of the lectures may be seen
here
(only while the lecture is being given).
Archived video, posted after the lectures, may be found
here (updated 1/17, 2:36pm)
Notes from previous offerings of CS267 are posted on old
class webpages available under
Class Resources
In particular, the web page from the
1996 offering
has detailed, textbook-style notes available on-line that are still
largely up-to-date in their presentations of parallel algorithms
(the slides to be posted during this semester will contain some more
recently invented algorithms as well).
Lectures from Spr 2012 will be posted here.
Lecture 1, Jan 17, Introduction (ppt)
Lecture 2, Jan 19, Single Processor Machines: Memory Hierarchies and Processor Features (ppt) (updated Jan 24, 8:45am)
Lecture 3, Jan 24, complete Lecture 2 (updated Jan 24, 8:45am)
and then Introduction to Parallel Machines and Programming Models(ppt) (updated Jan 26, 8:55am)
Lecture 4, Jan 26, complete Lecture 3 (updated Jan 26, 8:55am)
and then Sources of Parallelism and Locality in Simulation - Part 1(ppt) (updated Jan 26, 8:55am)
Lecture 5, Jan 31, complete Lecture 4,
and then Sources of Parallelism and Locality in Simulation - Part 2(ppt)
Lecture 6, Feb 2, Shared Memory Programming: Threads and OpenMP (ppt), and
Tricks with Trees (ppt)
Lecture 7, Feb 7, complete lecture on Tricks with Trees, then
Distributed Memory Machines and Programming (ppt)
Lecture 8, Feb 9,
Partitioned Global Address Space Programming with Unified Parallel C (UPC)(ppt), guest lecture by Kathy Yelick
Lecture 9, Feb 14
Introduction to GPUs (pdf) by Bryan Catanzaro
Lecture 10, Feb 16. This will be a two part lecture:
Tools for Performance Debugging HPC Applications (pptx)
by David Skinner
Debugging and Optimization Tools (pdf)
by Richard Gerber
NERSC web site with more documentation and videos about using tools at NERSC
Lecture 11, Feb 21, Dense Linear Algebra - Part 1 (ppt)
Lecture 12, Feb 23, Dense Linear Algebra - Part 2 (ppt)
Lecture 13, Feb 28, Graph Partitioning (ppt)
Lecture 14, Mar 1, complete Lecture 13, then begin Automatic Performance Tuning and Sparse-Matrix-Vector-Multiplication (SpMV) (ppt)
Lecture 15, Mar 6, complete Lecture 14, updated version here (ppt)
Lecture 16, Mar 8,
Hierarchical Methods for the N-Body Problem (pptx)
(updated 8:40am, Mar 13)
Efficient Data Race Detection for Distributed Memory Parallel Programs (pptx) by Chang-Seo Park
Lecture 17, Mar 13,
Complete
Hierarchical Methods for the N-Body Problem (ppt),
Begin
Structured Grids (ppt), (updated 8am, Mar 22)
Lecture 18, Mar 15,
Cloud Computing with MapReduce and Hadoop (ppt),
by Matei Zaharia
Lecture 19, Mar 20,
Architecting Parallel Software with Patterns (pptx) (updated 3/20, 12:30pm),
by Kurt Keutzer
Lecture 20, Mar 22,
Complete Lecture 17 on
Structured Grids (ppt), (updated 8am, Mar 22)
Discuss Class Project Suggestions
Lecture 21, Apr 3,
Frameworks for Structured Software Development
by John Shalf
For more information about these and other frameworks, including
the software itself and tutorials, see the
DOE ACTS Collections
Lecture 22, Apr 5,
Exascale Computing by
Katherine Yelick
Lecture 23, Apr 10,
Parallel Graph Algorithms by
Aydin Buluc
Lecture 24, Apr 12,
Parallel Climate Modeling by
Michael Wehner
Lecture 25, Apr 17,
Parallel Fast Fourier Transform (FFT) (updated 4/17, 8:05pm)
Lecture 26, Apr 19,
Dynamic Load Balancing
Lecture 27, Apr 24,
Big Bang, Big Data, Big Iron: High Performance Computing and the Cosmic Microwave Background
by Julian Borrill
Lecture 28, Apr 26,
Accelerated Materials Design through High Throughput First-Principles
Calculations and Data Mining:
Part 1 (pdf) and
Part 2 (pdf),
by Kristin Persson
Sharks and Fish
"Sharks and Fish" are a collection of simplified simulation programs
that illustrate a number of common parallel programming techniques
in various programming languages (some current ones, and some
old ones no longer in use).
Basic problem description, and (partial) code from 1999 class,
written in Matlab, CMMD, CMF, Split-C, Sun Threads, and pSather,
available
here.
Code (partial) from 2004 class, written in MPI, pthreads, OpenMP,
available
here.