Communities using TeraGrid EPSCoR National Workshop on Cyberinfrastructure

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Communities using TeraGrid EPSCoRNational
Workshop on Cyberinfrastructure

• Scott Lathrop
• TeraGrid Director of Education, Outreach and
  Training
• University of Chicago and Argonne National
  Laboratory
• Lathrop_at_mcs.anl.gov

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TeraGrid Objectives

• DEEP Science Enabling Terascale Science
• Make Science More Productive through an
  integrated set of very-high capability resources.
• WIDE Impact Empowering Communities
• Bring TeraGrid capabilities to the broad science
  community.
• OPEN Infrastructure, OPEN Partnership
• Provide a coordinated, general purpose, reliable
  set of services and resources.

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TeraGrid Facility Today
Common TeraGrid Computing Environment
Local Value-Added User Environment
Heterogeneous Resources at Autonomous Resource
Provider Sites

• A single point of contact for help
• Integrated documentation and training
• A common allocation process
• A common baseline user environment
• Services to assist users in harnessing the right
  TeraGrid platforms for each part of their work,
• Enhancements driven by users.
• Science Gateways to engage broader communities

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TeraGrid Allocation by Field of Science
Additional fields 2
Advanced Scientific Computing 3
Atmospheric Sciences
Molecular Biosciences
7
20
Chemical,
Thermal Systems
8
Physics
Materials Research
18
10
Astronomical Sciences 15
Chemistry
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Data for 1000 projects as of April 2006 provided
by David Hart (dhart_at_sdsc.edu)
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Science GatewaysA new initiative for the TeraGrid

• Increasing investment by communities in their own
  cyberinfrastructure, but heterogeneous
• Resources
• Users from expert to K-12
• Software stacks, policies
• Science Gateways
• Provide TeraGrid Inside capabilities
• Leverage community investment
• Three common forms
• Web-based Portals
• Application programs running on users' machines
  but accessing services in TeraGrid
• Coordinated access points enabling users to move
  seamlessly between TeraGrid and other grids.

Source Dennis Gannon (gannon_at_cs.indiana.edu)
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TeraGrid Science Gateways InitiativeHuman
Interface to Grids
TeraGrid
Grid-X
Grid-Y

• Common Web Portal or application interfaces
  (database access, computation, workflow, etc).
• Back-End use of TeraGrid computation,
  information management, visualization, or other
  services.
• Standard approaches so that science gateways may
  readily access resources in any cooperating Grid
  without technical modification.

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Science Gateways

• Independent infrastructure using TeraGrid
  resources in back-end fashion
• Local gateway user management, authentication,
  authorization
• Service Oriented Architecture using TeraGrid via
  web services such as job submission, file
  movement, authorization, job tracking and audit,
  etc.
• Current Status
• 15 prototypes at various stages of local
  production (some new gateways, most are
  operational with local services, early versions
  of TeraGrid-enabled services)
• Developing scalable model to allow for many
  independent gateways, using standard TeraGrid
  services interfaces, with gateway-managed
  TeraGrid computational and storage allocations.

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Science Gateway Examples
As well as additional gateway projects that have
joined us or are planning to join, including
University of Buffalo, BIRN ,NEES, GEON, Several
NCAR projects, Cornell (large data collections),
LSU (coastal modeling), IU Hydra Portal
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Science Gateways and Education NanoHub
Nanohub is used to complete coursework by
undergraduate and graduate students in dozens of
courses at 10 universities. Currently serves
over 1000 users.
Sebastien Goasguen (sebgoa_at_purdue.edu)
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Data Collections
Instruments Sensors
Science/Education Portal
Colleagues
Data Collections
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On Demand Predicting Severe Weather Droegemeier
(OU) and LEAD
Large Data Virtualized Resources Earthquake
Simulation Olsen (SDSU), Okaya (USC), Southern
California Earthquake Center
Sources Kelvin Droegemeier (OU), Dennis Gannon
(IU), Tom Jordan (USC). Images by PSC and SDSC.
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Virtualized Resources, EnsemblesFOAM Climate
Model Liu (UWisc)
Coupled Simulation Full Body Arterial Tree
Simulation Karniadakis (Brown)
Sources Ian Foster (UC/ANL), Mike Papka
(UC/ANL), George Karniadakis (Brown). Images by
UC/ANL.
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Modeling Information Processing and Public
Opinion
How do people assess political candidates? How do
campaign events and new information change their
views? Sung-youn Kim, University of Iowa, and
Milton Lodge and Charles Taber, Stony Brook
University, New York, saw gaps between existing
models and empirical findings integrated both
cognitive and affective information-processing
theories into a computational model that
simulates how voters political opinions
fluctuate during a campaign. Using data from the
2000 National Annenberg Election Survey (NAES),
they constructed virtual voters, each with a
unique mindset. Campaign messages were gleaned
from news accounts and reduced to simple
sentences (e.g. "Bush said Gore is dishonest" or
Gore said Bush is anti-abortion). The
computational model parses each sentence,
retrieves relevant concepts from the long-term
memory of each agent, and updates each agent's
knowledge and attitudes accordingly. Using 100
agents, this simulation was repeated 100 times,
returning results that accord well with the
actual 2000 polling data. Because of this
complexity and the sheer computational intensity
of the simulation, the researchers relied on the
computational power of the TeraGrid, employing
systems at SDSC and NCSA.
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Social and Behavioral Science Gateway
Understanding neural, cognitive, and social
behaviors can depend on the ability to uncover
coherent patterns among disparate data collected
at different times and places. Researchers
correlate subjects videotaped reactions with eye
movements, heart rates, electroencephalogram
results, and answers to written surveys. Its
complicated, says Chicago psychologist Bennett
Bertenthal, and technological infrastructure has
not kept pace with research needs.Bertenthal
and his team are working to develop a set of
cybertools to help collect and analyze behavioral
data, collaborating with the TeraGrid Science
Gateways Program.
With NSF support, the Social Informatics Data
(SID) Grid is a vast and sophisticated warehouse
of readings and measurements meant to foster
collaboration and to spur the development of
standards for gathering and coding datawhich,
Bertenthal says, right now is not part of the
landscape. In two years, when the SID Grid is
complete, psychologists, sociologists,
anthropologists, economists, and neuroscientists
can share notes across the globe and use software
interfaces like the ones shown above to
synthesize numerous forms of streaming data at
once.
Adapted from University of Chicago Magazine
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Source Jay Boisseau (TACC), Eric Roberts (TACC)
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Education and Training Opportunities

• Professional development opportunities
• Development and dissemination of resources
  including software, curricular materials, and
  lesson plans
• Materials added to the National Science Digital
  Library
• Hands-on training on topics from introductory to
  advanced applications of grid computing.
• Training venues include live workshops, Access
  Grid sessions, and on-line tutorials
• CI-Channel web accessible recordings of seminars,
  workshops, and presentations http//cichannel.org

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SC07-09 Education Programs

• Focus on two and four year colleges and
  universities - working with faculty and students
• Year-long program of engagement and support
• Participation in annual SC conference in November
• Summer workshops around the country
• Visits to campuses to work with administrators,
  faculty and students
• Training on cyberinfrastructure
• Assist with curriculum development
• Looking for institutions willing to commit to
  work with the Education Program team for three
  years
• Minority Serving Institutions
• EPSCoR Institutions
• Community Colleges

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Spectrum of Workforce Preparation
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Community Engagement

• Development Allocations Committee (DAC) accepts
  requests for developing applications,
  experimenting with platforms, and for classroom
  instruction.
• Collaborating on Science Gateway community
  portals
• Involving 2- and 4-year colleges and universities
  including MSIs and EPSCoR schools
• Expanding disciplinary impact - e.g. HASTAC
• Connecting new resources and sites
• We need your involvement to drive the evolution
  of TeraGrid

TeraGrid 06 Conference June 12-15 in
Indianapolis, Indiana Invited speakers Arden
Bement, Dan Atkins, Kelvin Droegemeier, Donna Cox
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Community Advice is Essential

• User requirements workshops led by external
  evaluator - U Michigan
• Cyberinfrastructure User Advisory Committee

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Process for Joining TeraGrid

• Primer outlining TeraGrid architecture with
  respect to integrating new computational systems
• www.teragrid.org/basics/
• Four-Stage process
• Definition, Evaluation and Negotiation
• Resource to be integrated, support commitments,
  etc.
• Planning
• Integration
• Production
• Working with several interested sites
• Developing a program of campus partnerships

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TeraGrid More Information
www.TeraGrid.org
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NSF TeraGrid In Context
TeraGrid
Operation Enhancement
Construction
Petascale
NSF Centers Program
PACI
TeraGrid

1/00
1/05
1/10
1/95
1/90
1/85
TeraGrid builds upon a twenty-year program at the
National Science Foundation to provide
high-performance computational resources and
services to the national science and education
community. As of April 2006 all resources from
the PACI program are accessible as part of the
TeraGrid facility.
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TeraGrid Integrating NSF Cyberinfrastructure
PSC
PU
UC/ANL
IU
NCSA
ORNL
TACC
SDSC
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TeraGrid Resources
Updated by Kelly Gaither (gaither_at_tacc.utexas.edu)
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TeraGrid Usage
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Enhancements Driven by User Input
Overall Score (depth of need)
Partners in Need (breadth of need)
Remote File Read/Write
High-Performance File Transfer
Coupled Applications, Co-scheduling
Grid Portal Toolkits
Grid Workflow Tools
Batch Metascheduling
Global File System
Client-Side Computing Tools
Batch Scheduled Parameter Sweep Tools
Advanced Reservations
Data
Results of in-depth interviews with over 30 users
from 16 TeraGrid user teams.
Capability Type
Grid Computing
Science Gateways