Scientific Computing
Dr. Guy Tel-Zur
2011B
Sunny Yellow Flower. Picture by Sharee Basinger, publicdomainpictures.net
Version: 14-10-2010 15:50
Survey
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Linux?
C/C++?
Python?
Parallel
Computing?
• CS, Biology, Chemistry,
Other Fields?
The Course Vision
“The crucial need for today's students and
readers is to move forward from the
older "formula-based" emphasis toward a
solution-based course. Solving problems
is the heart of modern engineering mathematics
and scientific computing. “ – Gilbert Strang –
Computational Science and Engineering, page
7, SIAM (2007).
What is Computational Physics?
Reference: Resource Letter CP-2: Computational Physics
Rubin H. Landau, Am. J. Phys. 76 4&5, April/May 2008
A broader view –
Computational Science
X=Physics, Biology, Chemistry, …
X
Computational
X
CS
Math
Reference: Resource Letter CP-2: Computational Physics
Rubin H. Landau, Am. J. Phys. 76 4&5, April/May 2008
3 Pillars
Theory
Computational
Science
Experiment
4 Pillars?
Theory
Computational
Science
Data Mining
Experiment
2 Computational Pillars
See next slide, from Communications of the ACM,
http://cacm.acm.org/magazines/2010/9/98038-science-has-only-two-legs/fulltext
September 2010 issue
NVIDIA CEO at the GTC2010, Sept. 2010
The 3rd Pillar of Science is HPC !!!
HPC = High – Performance Computing
Journals and Magazines…
Springer
Journal of
Scientific Computing SIAM Journal on
Scientific Computing
(SISC)
International Journal of
Modeling, Simulation,
and Scientific
Computing (IJMSSC)
Journal of Advanced Research in
Scientific Computing (JARSC)
Career Opportunities for
Computational Physicists
• A graduate degree in physics in areas such as biophysics, condensed matter
physics, particle physics, astrophysics to name a few.
• A career in High-performance and scientific computing, in the energy and
aerospace sectors, with chemical and pharmaceutical companies, with
environmental management agencies.
• Employment in firms that develop scientific software, as well as computer
games.
• A research career in an academic, industrial, or national laboratory
• A teaching career in physics
• A job in Wall Street. Even Wall Street employers are interested in people
with a background in computational physics.
Source: http://www.sru.edu/academics/colleges/ches/physics/Pages/ComputationalPhysics%28BS%29.aspx
Source: COMPUTATIONAL PHYSICS
FOR UNDERGRADUATES
THE CPUG DEGREE PROGRAM AT OREGON STATE UNIVERSITY
By Rubin H. Landau. CS&E March/April 2004
Source: COMPUTATIONAL PHYSICS
FOR UNDERGRADUATES
THE CPUG DEGREE PROGRAM AT OREGON STATE UNIVERSITY
By Rubin H. Landau. CS&E March/April 2004
Course Building Blocks
Tools
Methods
Mathematics
Case Studies
“Mini-Courses”
Physics
Practice
Rubin Landau et al, “A Survey of Computational Physics”
Parallel and distributed
computing
Rubin Landau et al, “A Survey of Computational Physics”
Scheme on previous slide refers to at least 2 quarters (20 weeks) course
Source: http://www.princeton.edu/as/LNL/presentations/spring2010/LnL031010TangFusionSimulation.pdf
What V&V Means?
The problem of quantifying uncertainty:
Validation "Solving the right equations"
Verification "Solving the equations right"
Tools
• Programming Languages
– C/C++
– Fortran
– Python
+OpenMP
+MPI
+Condor
• Numerical Tools
– CERN paw/root/Matlab/Octave/Scilab
• Visualization
– VTK
- grace
- Paraview -VisIt -Mayavi
– Vpython
- GNUplot – Workflow
– Kepler(?)
Full Scientific Research Study –
“Workflow”
Raw Data
Number
Crunching/Data
Analysis
Reduced Data
Visualization
Prototyping
(Matlab)
“Batch”
“Data Base”
Specific Format ,
e.g. NetCDF
Interactive
mode
Parallelism
Introducing Parallelism whenever possible
is going to be my own “twist” to the course
AMD Magny-Cours 12-core processor
Power7: IBM’s Next-Generation Server Processor with 8
cores.
The chip is 567 mm2 and contains 1.2 billion transistors
Recommended Reading:
http://www.computer.org/cms/Computer.org/ComputingNow
/homepage/2010/0710/W_MI_Power7.pdf
NVIDIA CEO at GTC2010
GPGPU increase presence at the Top500 Supercomputers
Serial vs. Parallel - demo
Execute: C:\FlexPDE5student\samples_student\steady_state\fluids\swirl
Low cpu utilization
Uses only one core
Some highlights of the course –
Next slides
We will have:
1. Standard “Classical” text PLUS
2. Several “Mini-Courses” – My add-ons
1. Parallel Computing – MPI, OpenMP
2. Batch/Grid Computing – Condor
3. Visualization (next slide)
4. Cluster Computing
Let’s have a demo
Go to:
C:\Users\telzur\Documents\Weizmann\ScientificComputing\SC2011B\
Lectures\01\code\HelloOMP
Open the solution file in Visual Studio
Execute in 1 and 4 threads, watch the “Task Manager” while running.
How to build a parallel computing
cluster – hands on demo
Course Web Site
http://tel-zur.net/teaching/weizmann/sc/2011B/
Course Duties
• 3 home assignments
• Final Projects
– Presentations
– Final report
• You are encouraged to bring laptops to class!
Course’s Load
The following is from: Old Dominion University Physics 420/520 Spring 2010
Keys to success Right motivation, working diligently, effectively and efficiently is the key to
success.
If you work regularly and allocate enough time each day to practice and complete
the assignments on time and keep up with the course, you will get the most out of
the course both intellectually and grade-wise.
You should invest about 4-5 hours per week outside of class to succeed in this
course. This is consistent with university guidelines (i.e. two to three hours of
outside preparation time for every credit hour). Students with little or no
programming experience (or those who love the subject and wish to do extremely
well in it) may want to put in more hours. Please, let me know as soon as possible
if you have difficulties and may need extra help.
You are recommended to start you assignments well before the last night when
your assignments are due. It is a general experience that a computer program
usually does not work correctly (if works at all) at the beginning. A search for a
problem, or a computer bug, may take more time that you expect.
Home Assignments
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3 sets of homework problems will be assigned.
The students will write computer programs based on computational algorithms discussed in
class.
These assignments constitute a very important part of the course, since the thinking involved
in scientific programming can only be developed through practical work.
The assignments must be returned by their stated due dates, unless an extension is granted
by the instructor. For late return of assignments, a 10% point deduction will be applied for
each late day.
Programs should be written in Fortran 90/95 or in C/C++ or in Python.
The programs as well as a short report discussing the results should be handed in to the
instructor by the stated due date. The solution programs should be sent as an attachment in
an e-mail to the address tel-zur@computer.org. The report (hardcopy required) should be
handed to the instructor in class before the deadline.
Every student is expected to work independently on the assignments. However, discussions
with fellow students are allowed, indeed encouraged, as long as they are kept on a general
level and do not amount to direct copying of ideas or programming solutions.
Although discussions and some degree of cooperation between students is allowed, The
material turned in must be independently written.
Inspired from: http://physics.bu.edu/~py502/syllabus.pdf
The Final Projects
• Each student will present his/her topic in front
of the class
• A list of suggested topics will be published at
the course website, however
• You are encouraged to suggest your own
topics
• Have a look at:
http://physics.usc.edu/~shaas/516/projects.html
The Final Projects
• In the presentations: Describe the project, the
computational challenge and the suggested
way to the solution (10%)
• The final project will consist of: a stand alone
document that will summarize the whole
project and any other relevant file including
the source codes and instructions how to
compile and execute the programs
The Studnts’ presentations
• Format: PPT, PPTX, Open Office, PDF, HTML…
• Language: English
• Send me the presentations no later than
midnight before class day
• Send them to: gtelzur@gmail.com
The final report
• Some of the reports will be uploaded to the
course website
• Report structure:
– Cover page: Your name, title
– Abstract, Introduction, the main part which deals with
your work, conclusions, references and appendices
– It is recommended to include graphs, charts and
tables to demonstrate the properties and results of
your work
• Format: doc(x), TeX, Open Office, PDF
• Submission by Email to tel-zur@computer.org
More tips about the Final Projects
• Consult these links:
1. http://www.odu.edu/~agodunov/teaching/p
hys420_10/organize_comp_proj.pdf
2. http://www.odu.edu/~agodunov/teaching/p
hys420_10/Sample_Project.pdf
3. http://www.odu.edu/~agodunov/teaching/n
otes/Intr02_projects.pdf
Programming Languages
• C/C++
• Fortran 90/95
• Python
• Please: No Java!
Visualization Tools
• Xmgrace – 2D, Linux only
• Python, Python Python!
– vPython – included in Python(x,y)
– Gnuplot – included in Python(x,y)
– Matplotlib, MayaVi2,
• Qtiplot – Free for Linux OS (Origin clone)
http://soft.proindependent.com/qtiplot.html
• CERN’s PAW/Root (if time will permit)
• Please no graphics using: MS - Excel
LaTeX
• Learn LaTex, here are a few links to tutorials:
– http://www.cs.cornell.edu/Info/Misc/LaTeXTutorial/LaTeX-Home.html
– http://www.pages.drexel.edu/~pyo22/students/la
texRelated/latexTutorial.html
– Getting Started With LaTex:
http://www.maths.tcd.ie/~dwilkins/LaTeXPrimer/
GSWLaTeX.pdf
LaTeX Recommended Environment
(install it on your laptops)
• MikTeX: http://www.miktex.org/
• LaTeX Editor: Led http://www.latexeditor.org/index.html
• Optional: LyX - http://www.lyx.org/
(less recommended)
• Online check your LaTeX equations with Texify:
http://www.texify.com/links.php
Linux Background
Check:
http://www.physics.udel.edu/~bnikolic/teaching/phys660/RUTE/rute/index.html
Recommended Working Environment
Other Options
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Linux (stand alone / cluster)
Dual boot Linux/Windows
Windows + Cygwin
Windows only + ports of the needed
packages, e.g MinGW
• Mac
Books - I
• Computational Science and
Engineering by Gilbert Strang
• http://math.mit.edu/cse/
• http://www-math.mit.edu/~gs/
• MIT Opencourseware:
http://ocw.mit.edu/courses/mathematics/18085-computational-science-and-engineering-ifall-2008/
Books - 2
• Python Scripting for Computational
Science, 3rd. Edition
by H. P. Langtangen
• TOC:
http://folk.uio.no/hpl/scripting/Langtangen_TCSE
3_3rd_ed_TOC.pdf
• Book web site:
http://folk.uio.no/hpl/scripting/
• Teaching slides:
http://heim.ifi.uio.no/~hpl/scripting/all-nosplit/
Books - 3
• "Computational Physics"
By Professor Morten Hjorth-Jensen from the
University of Oslo,
Lecture notes in Computational Physics (2009)
• http://www.uio.no/studier/emner/matnat/fys
/FYS3150/h09/
• An Open Source book!
• In my slides I will give references to Morten
Hjorth-Jensen by mentioning “MHJ”
Books -4
• Introduction to High-Performance
Scientific Computing
by Victor Hijkhout, 2010
• Free download:
http://www.tacc.utexas.edu/˜eijkhout/istc/istc.html
Or from Lulu.com:
http://www.lulu.com/product/filedownload/introduction-to-high-performancescientific-computing/14605650
• Rev. #311, 6-Feb.-2011
From the back cover:
The goal of this book is to teach computational scientists how
to develop tailored, flexible, and human-efficient working
environments built from small programs (scripts), written in
the easy-to-learn, high-level language Python. The focus is on
examples and applications of relevance to computational
scientists: gluing existing applications and tools, e.g. for
automating simulation, data analysis, and visualization;
steering simulations and computational experiments;
equipping old programs with graphical user interfaces; making
computational Web applications; and creating interactive
interfaces with a Maple/Matlab-like syntax to numerical
applications in C/C or Fortran. In short, scripting with Python
makes you much more productive, increases the reliability of
your scientific work and lets you have more fun - on Unix,
Windows and Macintosh. All the tools and examples in this
book are open source codes.
Books - 5
Scientific Computing: An Introductory Survey
This book presents a broad overview of numerical methods for
solving all the major problems in scientific computing, including
linear and nonlinear equations, least squares, eigenvalues,
optimization, interpolation, integration, ordinary and partial
differential equations, fast Fourier transforms, and random
number generators. The treatment is comprehensive yet
concise, software-oriented yet compatible with a variety of
software packages and programming languages. The book
features more than 160 examples, 500 review questions, 240
exercises, and 200 computer problems.
http://www.cse.illinois.edu/heath/scicomp/notes/index.html
Join: http://www.meetup.com/ComputationalScience/
Stay in Contact
• My email address: tel-zur@computer.org
• Please visit often the course web site!
• We can setup a google group, facebook,
twitter…
Let’s get started!