Math 627 - Introduction to Parallel Computing

Matthias K. Gobbert and Madhu Nayakkankuppam

Fall 2002 - Schedule Number 7608

This page can be reached via my homepage at http://www.math.umbc.edu/~gobbert.

Final Projects

The class presentations of the final projects will be held on Monday, December 09, 2002 and Tuesday, December 10, 2002 starting at 07:00 p.m. in MP 401. Please follow the link to the Program for the titles, abstracts, and (later) links to download the project reports. Just like for seminar talks, everybody is welcome to attend!

Grading Information

Final scores and grades ordered by your assigned number: scores and grades

Basic Information

Instructors:
- Matthias K. Gobbert, Math/Psyc 416, (410) 455-2404, gobbert@math.umbc.edu,
  office hours: TTh 04:00-05:00 or by appointment
- Madhu Nayakkankuppam, Math/Psyc 427, (410) 455-3298, madhu@math.umbc.edu,
  office hours: WF 10:00-11:00 or by appointment
Lectures: MP 401, September 04 to October 28 and December 02 to December 09, MW 07:00-09:00, see the schedule for more information.
Prerequisites: Math 630, fluency in programming either C or Fortran and proficiency in using the Unix/Linux operating system, or instructor approval
Copies of all following books are on reserve in the library.
- Required textbook: Peter S. Pacheco, Parallel Programming with MPI, Morgan Kaufmann, 1997. Associated webpage: http://nexus.cs.usfca.edu/mpi
- Recommended book: William Gropp, Ewing Lusk, and Anthony Skjellum, Using MPI: Portable Parallel Programming with the Message-Passing Interface, second edition, MIT Press, 1999. Associated webpage: http://www-unix.mcs.anl.gov/mpi/usingmpi/examples/main.htm
Grading policy:

Homework Project
50% 50%

See also the general policies and procedures for more information.

Overview

In recent years, parallel computing has become an almost ubiquitous way to perform computer simulations involving large amounts of data or intensive calculations. The basic purpose of using several processors is to speed up computations of large problems by distributing the work. But large problems typically involve vast quantities of data as well; by distributing the data across several processors, problems of previously unsolvable size can now be tackled in reasonable time.

Only government agencies, national laboratories, and large corporations could afford the first parallel machines. Due to the dramatic drop in prices for personal computers (PCs) and their components, parallel computing has become much more accessible in the form of Beowulf clusters formed by connecting commodity PCs by dedicated networks.

The most common library of parallel computing instructions today for any type of parallel machine architecture is the Message Passing Interface (MPI). This course will provide interested students a basic introduction to parallel computing using MPI on a distributed-memory cluster of Linux PCs. Time permitting, we will present several application examples that show how parallel computing can be used to solve large application problems in practice.

Information for Download

Instructions: Open the file by clicking on the link; plain text should appear in your browser window. Then use the "File -> Save As" functionality of your browser to save the data to a file. Or use the right mouse button to directly save the file without opening it first. The details may vary depending on your browser software and operating system. Contact me if there is a persisting problem.

Homework 3

Homework 4

Homework 5

Other Information

General policies and procedures including grading guidelines
Guidelines on how to report on programming assignments
Schedule

The recommended literature on my homepage includes listings of books on computers programming
A brief introduction to Unix/Linux at UMBC
My introduction to Matlab at UMBC
Introduction to LaTeX gives some pointers how to get started with LaTeX and includes a sample file and a template file for project reports.
Introduction to using MPI under Linux in the Math Department

Official UMBC Honors Code

By enrolling in this course, each student assumes the responsibilities of an active participant in UMBC's scholarly community in which everyone's academic work and behavior are held to the highest standards of honesty. Cheating, fabrication, plagiarism, and helping others to commit these acts are all forms of academic dishonesty, and they are wrong. Academic misconduct could result in disciplinary action that may include, but is not limited to, suspension or dismissal.

To read the full Student Academic Conduct Policy, consult the UMBC Student Handbook, the Faculty Handbook, or the UMBC Policies section of the UMBC Directory.

Homework	Project
50%	50%