
COSC 594  201420 Scientific Computing for Engineers: Spring 2014 – 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 Prof.
Jack Dongarra
with help from Profs. George Bosilca, Jakub Kurzak, Piotr Luszczek, Heike McCraw,
Gabriel Marin, Stan Tomov Email: dongarra@eecs.utk.edu Phone: 8659748295 Office
hours: Wednesday 11:00  1:00, or by appointment TA: Reazul Hoque <rhoque@utk.edu> TAÕs
Office : Claxton
309 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. Class
Roster If
your name is not on the list or some information is incorrect, please send
mail to the TA:
Book
for the Class: The
Sourcebook of Parallel Computing, Edited by Jack
Dongarra, Ian Foster, Geoffrey Fox, William Gropp, Ken Kennedy, Linda Torczon,
Andy White, October 2002, 760 pages, ISBN 1558608710, Morgan Kaufmann
Publishers. Lecture
Notes: (Tentative outline of the class)
Introduction
to High Performance Computing Read Chapter
1, 2, and 9 Homework
1 (due January 22, 2014)
Homework 2 (due January 29, 2014) 3. January
22rd (Dr. Tomov) Projection and its importance in
scientific computing Homework 3 (due February 5, 2014)
Discretization of PDEs and Tools for the Parallel
Solution of the Resulting SystMesh generation and load balancing Homework 4 (due February 12, 2014)
Sparse Matrices and Optimized Parallel
Implementations NVIDIA's Compute Unified Device Architecture
(CUDA) Homework 5
(due February 19, 2014)
Iterative Methods in Linear Algebra (Part 1) Iterative Methods in Linear Algebra (Part 2) Video of CUDA  "Better Performance at
Lower Occupancy", V. Volkov Video of OpenCL  "What
is OpenCL" Homework 6
(due February 26, 2014) High
Performance Linear Algebra with Intel Xeon Phi Coprocessors
Homework
7 (due March 5, 2014)
Performance Analysis and Tools Homework 8 (due March 19, 2014)
Parallel programming paradigms and their
performances Homework 9 (due March 26th, 2014) March 19th – Spring Break
Homework
10 (due April 9^{th}, 2014)
Homework
11 (due April 23rd, 2014)
Continue with the slides from last week
Schedule Class
Final Reports 1:30 Cole Gentry 1:50 Anthony Gianfraesco 2:10 Jason Jiahui Guo 2:30 Reazul Hoque 2:50 Artem Maksov 3:10 Marshall Mcdonnell 3:30 Christopher Ostrouchov 3:50 Thananon Patinyasakdikul 4:10 Chunyan Tang 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, 1015 pages, and in class you will have 20 minutes to make a presentation. Here
are some ideas for projects: o
Projects
and additional
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: http://www.cpuworld.com/CPUs/index.html http://www.cpuworld.com/sspec/index.html http://processorfinder.intel.com 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://wwwunix.mcs.anl.gov/dbpp/ Alice Koniges, ed., Industrial Strength Parallel Computing,
ISBN1558605401, Morgan Kaufmann Publishers, San Francisco, 2000. Ananth
Gramma et al., Introduction to Parallel
Computing, 2^{nd} edition, Pearson Education Limited, 2003. Michael
Quinn, Parallel Programming: Theory and
Practice, McGrawHill, 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, McGrawHill, 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
ElGhazawi, 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
``MPI
 The Complete Reference, Volume 1, The MPI1 Core, Second Edition'', ``MPI: The Complete Reference  2nd
Edition: Volume 2  The MPI2 Extensions'', MPI2.2 Standard, September 2009 PDF format: http://www.mpiforum.org/docs/mpi2.2/mpi22report.pdf
Hardcover: https://fs.hlrs.de/projects/par/mpi//mpi22/
Online Documentation
and Information about Machines Highperformance computing systems: á
High
Performance Computing Systems: Status and outlook, Aad J.
van der Steen and Jack J. Dongarra, 2012.
á
Green
500 List of Energy –Efficient Supercomputers Other Scientific
Computing Information Sites á
Netlib
Repository at UTK/ORNL á
LAPACK
á
GAMS
 Guide to Available Math Software á
Fortran
Standards Working Group á
Message
Passing Interface (MPI) Forum á
OpenMP á
DOD
High Performance Computing Modernization Program á
DOE
Accelerated Strategic Computing Initiative (ASC) á
NSF
XSEDE (Extreme Science and Engineering Discovery Environment á
AIST
Parallel and High Performance Application Software Exchange
(in Japan)
(includes information on parallel computing conferences and journals) á
HPCwire Related Online 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 MessagePassing 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 deadtree version of this book is
available by AddisonWesley. á
Introduction to HighPerformance
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 á
PAPI á
TAU á
Vampir á
Scalasca á
mpiP á
ompP á
IPM á
Eclipse
Parallel Tools Platform 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 University of Florida Sparse Matrix Collection á Templates for the solution of linear systems, a collection of iterative methods, with advice on which ones to use. The web site includes online versions of the book (in html and pdf) 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 Updated survey of sparse direct linear equation solvers, by Xiaoye Li 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 PETSc: Portable, Extensible, Toolkit for Scientific Computation á Issues related to Computer Arithmetic and Error Analysis á Efficient software for very high precision floating point arithmetic á Notes on IEEE Floating Point Arithmetic, by Prof. W. Kahan á Other notes on arithmetic, error analysis, etc. by Prof. W. Kahan á Report on arithmetic error that cause the Ariane 5 Rocket Crash Video of the explosion á The IEEE floating point standard is currently being updated. To find out what issues the standard committee is considering, look here. 4/26/2014



