Parallel Computing for Partial Differential Equations
Universität Kassel  Sommersemester 2012
Matthias K. Gobbert  University of Maryland, Baltimore County
This page can be reached via the Teaching area of my homepage at
http://www.math.umbc.edu/~gobbert.
Basic Information
 Instructor: Matthias K. Gobbert, University of Maryland, Baltimore County,
on sabbatical leave at the Universität Kassel
from November 2011 to June 2012.
Office AVZ Room 2431,
office hour Tuesdays 1415,
email gobbert@umbc.edu.
 The lectures and associated computer labs are listed as
Vst.nr. FB1017.2421s and FB1017.2422s, respectively,
in the
Vorlesungsverzeichnis of Sommersemester 2012.
The course is taught as 4+2 SWS
during the first seven weeks of the Sommersemester 2012
and counts as 2+1 SWS; see the
Vorlesungsverzeichnis for more information.
Additionally, there is a time slot for open programming exercise
offered by Stefan Kopecz.
lectures and labs:
Lectures Tuesdays 1517 and Wednesdays 1315 in AVZ Room 1403;
Labs Wednesdays 1517 in AVZ Room 2421 (computer lab).
Open programming exercise Mondays 1517 in AVZ Room 2421 (computer lab).
See the outline of the contents of the course
and the updated detailed schedule
of the lectures and computer labs,
with attached postings of class summaries, PDF transcripts, and postings.
The latter area is restricted to participants in the course.
To access the area, just follow the link and then enter the
username and password that will be supplied to you.
 Prerequisites: Introduction to Parallel Computing, Numerik I,
fluency in programming C, C++, or Fortran and
proficiency in using the Unix/Linux operating system,
or consent of instructor
 Books on parallel computing, the programming language C,
and numerical methods for partial differential equations:

Required textbook on parallel computing:
Peter S. Pacheco,
Parallel Programming with MPI,
Morgan Kaufmann, 1997.
Associated webpage:
http://www.cs.usfca.edu/~peter/ppmpi.
We may have explicit reading assignments for
several chapters from this book.

Recommended book on the programming language C:
Brian W. Kernighan and Dennis M. Ritchie,
The C Programming Language,
second edition, PrenticeHall, 1988.
Associated webpage:
http://cm.belllabs.com/cm/cs/cbook/.
This is the classic book on C written by its creators.
You can use other books or internet resources instead.
I will strive to explain all necessary C in class,
but some additional resources may be convenient to have.

Recommended book on numerical methods for partial differential equations:
Arieh Iserles,
A First Course in the Numerical Analysis of Differential
Equations, Cambridge Texts in Applied Mathematics,
second edition, Cambridge University Press, 2008.
Associated webpage:
Click on "Textbook" in the left column from the webpage
http://www.amtp.cam.ac.uk/user/na/people/Arieh
 Grading policy:
Homework and Quizzes
 Participation

90%
 10%


The homework includes
the computer assignments that are vital to understanding
the course material.
A late assignment accrues a deduction of
up to 10% of the possible score
for each day late until my receiving it;
I reserve the right to exclude any problem from scoring
on late homework, for instance, if we discuss it in class.
The quizzes will generally be unannounced and brief and
will include the use of learning groups formed by the instructor.
For instance, they may be designed to initiate class discussion
or to give me feedback on your learning.
They may be technical or nontechnical in nature.

The graded participation component rewards
your professional behavior and active involvement
in all aspects of the course.
Examples of expected professional behavior include
attending class regularly,
reading assigned material when requested,
cooperating with formal issues such as
submitting requested material on time, and
participating constructively in class, specifically in group work.
In this course, professional behavior also includes
adhering to good user behaviors on the shared
computing facilities that you will work on.
Additional details or changes will be announced as necessary.
 Homework submission:
Each homework is to be submitted as one single PDF file attached to an email
to gobbert@umbc.edu, with the attachment name to include
both the number of the homework and your unique name.
For example, if your name were Peter Smith,
the submission of Homework 2 would use the filename "HW2_Smith.pdf".
Please include your name also in the Subject field of the email,
such as "HW 2 from Peter Smith".
If there are several student with same last name in class,
include first name after the last name such as "HW2_SmithPeter.pdf".
If your last name is very long, consider abbreviating it.
If in doubt, contact me about these issues;
the goal is to have clear and unique filenames.
Please also make sure that the From field of your email shows your
full name clearly, not just your username or some other internet handle;
to guard against confusion about the sender of the mail,
I require the name in the Subject field above.
The contents of email for homework submission should be essentially
empty, since I have no way to integrate this with your PDF file;
make sure that all contents for grading is in the PDF attachment!
But a sensible, short message, signed by your full name is
of course useful to guard against misunderstandings.
Please submit each homework only once; if you send several copies,
I cannot guarantee which one I end up grading.
Course Description
This course is preceded by the course
Introduction to Parallel Computing
in Wintersemester 2011/2012
and accompanied by the seminar
Applications of Parallel Computing
in Sommersemester 2012.
The latter seminar would be appropriate for students who want to explore
other problems in parallel computing in general
or more sophisticated numerical methods for partial differential equations.
An important application of parallel computing is in the area
of numerical methods for partial differential equations.
This course will introduce methods for the elliptic Poisson equation
and the parabolic reactiondiffusion equation as examples.
The presentation will use relatively simple numerical methods
and focus on their parallelization,
so that no formal background in the subject of
numerical methods for partial differential equations is required.
Learning Goals
By the end of this course, you should:

understand and remember the key ideas, concepts, definitions,
and theorems of the subject.
Examples include understanding the purpose of parallel computing
and why it can work, being aware of potential limitations,
and knowing the major types of hardware available.
This information will be communicated in class and in the
textbook, but also in additional reading.
> This information will be discussed in the lecture as well as
in the textbook and other assigned reading.

have experience writing code for a Linux cluster using MPI in C, C++,
and/or Fortran that correctly solves problems in scientific computing.
The sample problems are taken from mathematics and your code has to
compile without error or warning, run without error,
and give mathematically correct results first of all.
In addition, it needs to run on a Linux cluster without error
and you need to be able to explain its scalability, i.e.,
why or why not it executes faster on several processors than in serial.
We will have problems stated in different ways and from various
sources to provide you with exposure to as many issues as possible.
> This is the main purpose of the homework and most
learning will take place here.

have gained proficiency in delivering code written by you to others
for compilation and use.
This includes the concept of providing a README file that gives
instructions how to compile and run the code as well as
of providing a sample output file to allow the user to check the results.
We will work together in class to discuss best practices to transfer code
for homework problems of increasing complexity.
> You will submit your homework code by email to the instructor
and it needs to compile and run in parallel for credit; this is
complemented by a report that shows and explains your results.

have some experience how to learn information from a research paper
and to discuss it with peers.
Group work requiring communication for effective collaboration
with peers and supervisors is a vital professional skill,
and the development of professional skills is a declared learning goal
of this course.
> I will supply some research papers carefully
selected for their readability and relevance to the course.
Learning from research papers is a crucial skill to develop.
Other Information
Copyright © 20012012 by Matthias K. Gobbert. All Rights Reserved.
This page version 2.1, April 2012.
Updated links to summary area 05/22/14 MGo.