COSC 594-005 (22314)
Scientific Computing for Engineers: Spring 2013 – 3 Credits
This class is part of the Interdisciplinary Graduate Minor in Computational Science. See IGMCS for details.
Wednesdays from 1:30 – 4:15, Room 233 Claxton
Office hours: Wednesday 11:00 - 1:00, or by appointment
TA: Blake Haugen <firstname.lastname@example.org>
TAÕs Office : Claxton 353
TAÕs Office Hours: WednesdayÕs 10:00 – 12:00 or by appointment
There will be four major aspects of the course:
The grade would be based on homework, a midterm project, a final project, and a final project presentation. Topics for the final project would be flexible according to the student's major area of research.
Book for the Class:
Edited by Jack Dongarra, Ian Foster, Geoffrey Fox, William Gropp, Ken Kennedy, Linda Torczon, Andy White, October 2002, 760 pages, ISBN 1-55860-871-0, Morgan Kaufmann Publishers.
Lecture Notes: (Tentative outline of the class)
Read Chapter 1, 2, and 9
Homework 1 (due January 23, 2013)
Homework 2 (due January 30, 2013)
Read Chapter 3
Read Chapter 20
Homework 3 (due February 6, 2013)
Read Chapter 21
Homework 4 (due February 13, 2013)
Read Chapter 11
Homework 5 (due February 20, 2013)
Homework 6 (due March 6th, 2013)
Samuel Williams, Andrew Waterman, and David Patterson. 2009.
Roofline: an insightful visual performance model of multicore architectures
Commun. ACM 52, 4(April 2009), 65-76
Homework 8 (due March 20, 2013)
10. March 13th (Dr. Tomov)
Homework 9 (due April 10, 2013)
March 27th – Spring Break
Homework 10 (due April 17, 2013)
Homework 11 (due April 21, 2013)
Read Chapter 20 and 21
15. April 24th No Class
Prepare for final Project report
Read Chapter 20
BaileyÕs paper on Ò12 ways to fool ÉÓ
Class Final reports
¥ 1:30 Jacob Fosso Tande
– Implementation of Fox's Algorithm
¥ 1:50 Austin Harris
– Computational astrophysics and linear algebra GPU
¥ 2:10 Sang-Hyeb Lee
– Distributed iterative medical image reconstruction for Inveon SPECT modality using with MPI and GPU
¥ 2:30 BREAK
¥ 2:40 John Martin
– Large scale text mining and analysis using LSI/LSA
¥ 3:00 Bryan Sundahl
– Orbital localization algorithm
¥ 3:20 Ziliang Zhao
– Compare apps and optimizing configurations
The project is to describe and demonstrate what you have learned in class.
The idea is to take an application and implement it on a parallel computer.
Describe what the application is and why this is of importance.
You should describe the parallel implementation, look at the performance,
perhaps compare it to another implementation if possible.
You should write this up in a report, 10-15 pages, and in class you will have
20 minutes to make a presentation.
Here are some ideas for projects:
Additional Reading Materials
Message Passing Systems
Several implementations of the MPI standard are available today. The most widely used open source MPI implementations are Open MPI and MPICH.
Here is the link to the MPI Forum.
Other useful reference material
á Here are pointers to specs on various processors:
á Introduction to message passing systems and parallel computing
``Message Passing Interfaces'', Special issue of Parallel Computing, vol 20(4), April 1994.
Ian Foster, Designing and Building Parallel Programs, see http://www-unix.mcs.anl.gov/dbpp/
Alice Koniges, ed., Industrial Strength Parallel Computing, ISBN1-55860-540-1, Morgan Kaufmann Publishers, San Francisco, 2000.
Ananth Gramma et al., Introduction to Parallel Computing, 2nd edition, Pearson Education Limited, 2003.
Michael Quinn, Parallel Programming: Theory and Practice, McGraw-Hill, 1993
David E. Culler & Jaswinder Pal Singh, Parallel Computer Architecture, Morgan Kaufmann, 1998, see http://www.cs.berkeley.edu/%7Eculler/book.alpha/index.html
George Almasi and Allan Gottlieb, Highly Parallel Computing, Addison Wesley, 1993
Matthew Sottile, Timothy Mattson, and Craig Rasmussen, Introduction to Concurrency in Programming Languages, Chapman & Hall, 2010
á Other relevant books
Stephen Chapman, Fortran 95/2003 for Scientists and Engineers, McGraw-Hill, 2007
Stephen Chapman, MATLAB Programming for Engineers, Thompson, 2007
Barbara Chapman, Gabriele Jost, Ruud van der Pas, and David J. Kuck, Using OpenMP: Portable Shared Memory Paralllel Programming, MIT Press, 2007
Tarek El-Ghazawi, William Carlson, Thomas Sterling, Katherine Yelick, UPC: Distributed Shared Memory Programming, John Wiley & Sons, 2005
David Bailey, Robert Lucas, Samuel Williams, eds., Performance Tuning of Scientific Applications, Chapman & Hall, 2010
Message Passing Standards
- The Complete Reference, Volume 1, The MPI-1 Core, Second Edition'',
``MPI: The Complete Reference - 2nd
Edition: Volume 2 - The MPI-2 Extensions'',
MPI-2.1 Standard, September 2008
PDF format: http://www.mpi-forum.org/docs/mpi21-report.pdf
MPI-2.2 Standard, September 2009
On-line Documentation and Information about Machines
High-performance computing systems:
á High Performance Computing Systems: Status and outlook, Aad J. van der Steen and Jack J. Dongarra, 2012.
Other Scientific Computing Information Sites
(includes information on parallel computing conferences and journals)
Related On-line Books/Textbooks
á Templates for the Solution of Linear Systems: Building Blocks for Iterative Methods, SIAM Publication, Philadelphia, 1994.
á LAPACK Users' Guide (Second Edition), SIAM Publications, Philadelphia, 1995.
á Using MPI: Portable Parallel Programming with the Message-Passing Interface by W. Gropp, E. Lusk, and A. Skjellum
á Parallel Computing Works, by G. Fox, R. Williams, and P. Messina (Morgan Kaufmann Publishers)
á Designing and Building Parallel Programs. A dead-tree version of this book is available by Addison-Wesley.
á Introduction to High-Performance Scientific Computing, by Victor Eijkhout with Edmond Chow, Robert Van De Geijn, February 2010
á Introduction to Parallel Computing, by Blaise Barney
Performance Analysis Tools Websites
Other Online Software and Documentation
á Matlab documentation is available from several sources, most notably by typing ``help'' into the Matlab command window. See this url
á SuperLU is a fast implementations of sparse Gaussian elimination for sequential and parallel computers, respectively.
á Sources of test matrices for sparse matrix algorithms
á Templates for the solution of linear systems, a collection of iterative methods, with advice on which ones to use. The web site includes on-line versions of the book (in html and postscript) as well as software.
á Templates for the Solution of Algebraic Eigenvalue Problems is a survey of algorithms and software for solving eigenvalue problems. The web site points to an html version of the book, as well as software.
á MGNet is a repository for information and software for Multigrid and Domain Decomposition methods, which are widely used methods for solving linear systems arising from PDEs.
á Resources for Parallel and High Performance Computing
á ACTS (Advanced CompuTational Software) is a set of software tools that make it easier for programmers to write high performance scientific applications for parallel computers.
á Issues related to Computer Arithmetic and Error Analysis
á Efficient software for very high precision floating point arithmetic
á The IEEE floating point standard is currently being updated. To find out what issues the standard committee is considering, look here.