Curriculum Development

1
Curriculum Development 2 for CyberInfrastructure
(CI)Essential Resources Core Courses

• MSI C(I)2
• SDSC 27June06
• Dr. Kris Stewart
• San Diego State University/California State
  University System

2
Partnerships an Asset

• EOT-PACI partnership provided evaluators (Julie
  Foertsch and Baine Alexander) U. Wisconsin
  Leadership through Evaluation, Adaptation and
  Dissemination (LEAD) center Susan Millar, Dir.
• Having external evaluators helped raised
  awareness for campus Deans/Chairs of importance
  of Computational Science
• It is a costly process, so partner with an
  evaluator in proposals (as an equal).

3
Where did it begin? 1998/99 Assessment by LEAD

• Background
• Workshop in Wisconsin April 1997 to learn about
  assessment and make it real to the EOT-PACI
  (NPACI and NCSA Education Teams)
• NPACI started 01 October 1997
• EC/CSE requested assessment for 1998 project

4
Evaluation Assessment using Outside Wisdom
(Foertsch/Alexander)

• U. Wisconsin LEAD for 1998/99 Ed Center
  evaluation by Julie Foertsch Baine Alexander
  Integrating High Performance Computing into the
  Undergraduate curriculum How PACI and the ECCSE
  can Succeed
• http//homepages.cae.wisc.edu/lead/pages/product
  s/eot-paci.pdf
• Follow-on Activities (Susan Millar, LEAD)CATS
  (Classroom Assessment Techniques)FLAG
  (Field-tested Learning Assessment Guide)SALG
  (Student Assessment Learning Guide)

5
Grand Challenges for HPC Stewart Zaslavsky,
SC98, HPCHigh Performance Computing

• Faculty system of rewards does not encourage
  teaching innovations
• Lack of awareness of HPC technologies already
  used in research or teaching for different
  fields
• Faculty students unaware of benefits and
  accomplishments of HPC
• HPC technologies considered too
  complex/inaccessible for undergraduate
  instruction
• Sequential HPC-related curricula is absent
• Curricula using very large data sets not widely
  available
• Adjust to different learning styles when material
  is complex
• Variety of platforms/software leads to fragmented
  curricula
• School administration/support staff not ready for
  HPC
• Specs of computers and networks below user
  expectations
• We had been thinking about this (based on April
  97 LEAD Workshop in WI)

6
UCES ParadigmUCES Undergrad Computational
Science Engineeringthanks Tom Marchioro and
the crew, 1994
My previous exposure to assessment How well
does numerical approximationmatch the original
problem?
Along comes SDSC, NPACI and EOT-PACI
7
1998/99 Assessment by LEAD
Assessment as a Collaboration

• Background
• Workshop in Wisconsin April 1997 to learn
  about assessment and make it real
• NPACI starts 01 October 1997
• EC/CSE requested assessment for 1998 project

• Preparation SDSU Campus Visit/B.Alexander
  J.Foertsch
• Discussions at SC98- Supercomputing Fall98
  Orlando
• Email to SDSU faculty gather attitudes

8
Interviews on SDSU CampusLEAD applying info from
email surveys (Spr 99)

• Faculty skepticism
• Convincing evidence that computer-based tools
  enhance teaching process?
• Knowledge of modern computational methods and
  availability?
• Incentive from department and insufficient tech
  support?

• LEAD Interviews with V.P. Singer, Deans, Chairs
• Faculty Fellows program identified as a target
• OUTCOMES
• our local infrastructure at SDSU took us more
  seriously
• survey instruments refined
• Online tool (SWB) recog.

9
Assessment not just requirement

• Rather, found to be
• vital tool to assist in clarifying student and
  faculty needs
• improve prioritization skills
• validation of focus on human factors to integrate
  HPC (modeling visualization) into undergrad
  curriculum

10
California Education Infrastructure

• K12 Education (standards based, performance based
  now is 1st year of exit exams before diploma
  being challenged)
• Community Colleges(Freshman/Sophomore)
• Vocational (and service to local community)
• University preparation
• California State University System (24 campuses)
• University of California (9 campuses, Merced
  soon)
• Independents (Stanford U., CalTech, U. Southern
  California)

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Involving University FacultyInfrastructure for
Change

• NPACI/SDSU Faculty FellowsLocal Support from
  College Deans and Department Chairs
  (participation buy-in and faculty recognition)
• SDSU Academic Advisors (across disciplines)
• Professional Meeting (SC2001, SIAM, ACM, SIGCSE,
  your suggestions?)

12
Undergraduate Faculty A Tough Target Group

• Obstacles lack of time, tenure and review
  considerations, lack of awareness about available
  technologies
• Undergraduate faculty (SSRL phone survey 1997
  thanks Doug Coe)
• ¾ have used WWW often or sometimes (1997), but
  not in the classroom (only 18 - 1998)
• The gap between those NEVER using computers in
  the classroom, and those using them OFTEN, is the
  largest for untenured faculty, increasing towards
  tenure review
• Only 12 of surveyed faculty saw themselves as
  having a use for HPC applications in courses
  (higher for Sciences and Engineering)
• 11 of faculty have students working with
  computer models OFTEN

13
Using computers in the classroom versus number of
years as a faculty member (1997 Faculty Survey by
SSRL/Doug Coe funded by Academic Affairs)
14
Students Using Computers in the Classroom (1997
Faculty Survey)
15
Strategies for Building Faculty Community

• Reliance on most enthusiastic and technically
  advanced instructors who are already using
  computing and modeling in classes
• The Faculty Fellows program
• Stakeholders
• College Deans - Specific support through faculty
  release time
• Faculty - Compensation, and acknowledgement, of
  the value of the faculty members contribution
• Benefits
• College
• Department (Faculty Fellows as discipline-specific
  spokespersons for EC/CSE and NPACI)
• Faculty (as individuals)
• Ed Center on Computational Science and
  Engineering
• Building a special infrastructure for curriculum
  transformation human, institutional, technical
  is a requirement for successful introduction of
  advanced techniques (since they are more
  demanding on faculty time and efforts)

16
Faculty Fellows during 1998-2004

• Faculty Fellows representing departments from
  five colleges and the Library Geological
  Sciences, Geography, Linguistics, Library Info
  Access, Music, Education Technology, Biology,
  Computer Engineering, Computer Science, Business
  Information Systems
• Bi-weekly meetings at the Ed Center
• Faculty Fellows as ambassadors of computational
  science
• Partnership with LEAD for evaluation during
  1998-99

17
Faculty Fellows Fall 01 Synergyamong themselves
and with their chairs and deans
People, Time, Support, Recognition
18
Lessons Learned from ECCSE

• Institutional support required for program to be
  sustainable
• Individual reform-ready faculty is focus for
  support
• Infrastructure
• Build a Synergistic Environment (across
  disciplines) for Faculty
• Continuous monitoring through interviews,
  surveys, discussions

19
More Outside Wisdom JSBJohn Seely Brown
17Jan05 _at_ SDSU
20
Apply JSB Insights to my Curriculum

• CS596 3d Game Programming - Student Learning
  Outcomesstudent group presentations were great

• JSB highlights
• multimedia literacy

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Apply JSB Insights

• Students have grown up digital (natives) faculty
  are analog (immigrants)
• Capitalize on creativity by honoring the
  vernacular of todays students (multimedia-literat
  e)
• Communicate complexity simply (great skill)
• MITs architecture studio all work in public
  (development and critique) in context
• Learning to learn in situ is key

22
CS 575 Supercomputing

• Crucial topic Computer Security (Students may
  not appreciate the importance yet)
• ACM/IEEE SC 1995 Conference (SC'95)   p. 19HPC
  Undergraduate Curriculum Development at SDSU
  Using SDSC Resources
• Technology changing frequently and course not
  taught since Fall 2003 might be useful as
  template for you. www.stewart.cs.sdsu.edu/cs575/in
  dex.htmText High Performance Computing,
  Oreilley

• Better who is providing your class resources?
  Vendors and providers (SDSC, NCSA, PSC, OSU,
  ) have workshops. Signup and make new friends.
• Personally, I recommend Mary Thomas Grid course,
  next

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Grid Curriculum Mary Thomas

• Introduction to Grid Computing
• rohan.sdsu.edu/faculty/mthomas/courses/
• spring05/cs696/index.html (all on 1 line)

Areas of Research Grid Portal Toolkit
Grid-enabled Web Services DOE portal
development on the SciDAC Grid Grid Portals
Information Repository Middleware for Grid
Portals Grid-Enabled Portals for Advanced
Computing NSF Extensible Terascale Facility
(ETF) or TeraGrid Performance (MS Thesis)
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Mary Thomas Grid Computing

• Prerequisites This course is designed for
  Computer Science, Computational Science, and Math
  graduate students with suitable preparation.
  Students must have graduate standing, have taken
  courses such as Java (e.g. CS435, CS535) or C,
  CS580 (or equivalent). Undergraduates with highly
  advanced skills who have taken courses such as
  CS535, CS575, CS558 will be considered. 
  Priorities will be given to students interested
  in active research careers

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Mary Thomas Students must know

• Students must know
• Java (optionally Python or Smalltalk)
• HTML and other Web Technologies
• Students should be familiar with
• XML, CSS, XSLT
• computational science, parallel programming
• Web Services, SOAP, HTTP and other transport
  protocols
• basics of client-server programing
• some database experience would be useful

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COURSE OUTLINE (TENTATIVE)

• Introduction and Overview of Grid Computing
  Trends, Challenges, Technologies, and
  Applications (1 week)
• Web Services and related technologies XML,
  XML-Schemas, WSDL, WSRF, etc (2 week)
• Distributed Object Technology for Grid
  computing(1 week)
• Overview of Grid Middleware (3 weeks)
• Distributed Object Technology for Grid computing
  (OGSA, WS-RF) (1 week)
• Grid Middleware GridPort Toolkit, javaCoG,
  Globus, GSI, FTP, etc. (1 week)
• Developing Grid Services (2 weeks)
• Introduction to Grid Computing Portals (1 week)
• Overview of Grid Portal Frameworks (JetSpeed,
  OGSA) (2 weeks)
• Deploying Grid Portals (1 week)

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Readings for Week 1

• Ian Foster Paper
• What is the Grid? A Three-point Checklist
• http//www-fp.mcs.anl.gov/foster/Articles/WhatIsT
  heGrid.pdf
• Chapters 1 and 4 in text The Grid 2 by Foster
  and Kesselman
• Investigate grid related Web sites (see course
  web pages)
• Hint use the Google What is X command

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Why do We Have Grid Computing?

• The term was coined ca 1996 by Ian Foster and
  Carl Kesselman
• Used to describe software that was needed by the
  rapidly growing, highly advanced community of
  high-performance Computing (HPC)
• Resources that scale with technologies
• Supercomputers (MFlops in96, but now using
  TFlops)
• Big and not portable
• Large data sets (GB in 96, but now peta-bytes)
• Need fast networks to move data around to
  resources
• Need security
• NSF (and other gov agencies) spend money to build
  infrastructure, so it is hard to get access

29
A small grid (UTGrid)
Ext nets
Research campus
NOC
GAATN
CMS
NOC
Switch
TACC Storage
TACC PWR4
PGE
ACES
TACC Cluster
Switch
TACC Cluster
PGE Cluster
Switch
TACC Vis
ICES Cluster
PGE Cluster
ICES Cluster
PGE Cluster
Main campus
30
(No Transcript)
31
Portals typical
32
What is Grid Computing?

• Is it a new, unique idea or the next generation
  of distibuted or meta-computing?
• See Ian Foster Paper What is the Grid? A
  Three-point Checklist
• http//www-fp.mcs.anl.gov/foster/Articles/WhatIsT
  heGrid.pdf

33
Ian Fosters 3 point checklist

• A Grid is a system that is able to
• coordinate resources that are not subject to
  centralized control
• Use standard, open, general-purpose protocols
  and interfaces
• to deliver nontrivial qualities of service.
• What does this mean?
• We will try to understand this in this course.

34
Defining Grid Computing

• There are several competing definitions for The
  Grid and Grid computing
• These definitions tend to focus on
• Implementation of Distributed computing
• A common set of interfaces, tools and APIs
• Some stress the inter-institutional aspect of
  grids and Virtual Organizations
• The Virtualization of Resources abstraction of
  resources

35
What is Grid and Grid Computing?

• Grid computing promises a standard, complete
  set of distributed computing capabilities
• There is a lot of hype around grid computing
• Traditional users need to get work done now!
• Some CS researchers see it as a fad
• But there is real-world value!
• In e-science and e-business

36
What is Grid and Grid Computing?

• Grid computing must provide basic functions
• resource discovery and information collection
  publishing
• data management on and between resources
• process management on and between resources
• common security mechanism underlying the above
• process and session recording/accounting
• Current grid computing tools such as Globus
  provide most of the above at some level
• The current capabilities are incomplete
• New web service based-standard will help current
  tools become interoperable.

37
Mary Thomas - Extensive Web Site

• The previous 15 slides were taken directly from
  Mary Thomas web page, as a teaser.
• The 15 week semester is completely available for
  reading (and using) from Mary Thomas Web Site

www-rohan.sdsu.edu/faculty/mthomas/courses/spring0
5/cs696/index.html Or Google ( mary thomas
siterohan.sdsu.edu )
38
3d Game ProgrammingUpper Division Course for
Coders

• Using the Torque Game Engine from
  www.garagegames.com
• Torque is an object oriented scripting language
  with an extensive library of game capabilities
• Text Ken Finney, Thomson Pub

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3d Game Programming Spr 06

• http//www.stewart.cs.sdsu.edu/cs596.html
• The first offering of this course was Spr06 and
  the course will be reoffered Spr07. The class
  web page will be updated for the next offering
  during Fall 07. Please check back on this
  evolving curricular development.

40
More Information?

• Kris StewartProfessor, Computer Science,
  SDSUDirector, ECCSE, NPACI/CSUstewart_at_sdsu.edu
• www.edcenter.sdsu.edu

www.eotepic.orgThis work supported by NSF 520146
www.nsf.gov/awardsearch/showAward.do?AwardNumber0
520146