1. Cyberinfrastructure From Dreams to Reality Deborah L. Crawford Deputy Assistant Director of NSF for Computer & Information Science & Engineering Workshop for eInfrastructures Rome, December 9, 2003

2. 2 Daniel E. Atkins, Chair, University of Michigan Kelvin K. Droegemeier, University of Oklahoma Stuart I. Feldman, IBM Hector Garcia-Molina, Stanford University Michael L. Klein, University of Pennsylvania David G. Messerschmitt, University of California at Berkeley Paul Messina, California Institute of Technology Jeremiah P. Ostriker, Princeton University Margaret H. Wright,New York University http://www.communitytechnology.org/nsf_ci_report/

3. 3 In summary then, the opportunity is here to create cyberinfrastructure that enables more ubiquitous, comprehensive knowledge environments that become functionally complete.. in terms of people, data, information, tools, and instruments and that include unprecedented capacity for computational, storage, and communication. They can serve individuals, teams and organizations in ways that revolutionize what they do, how they do it, and who can participate. - The Atkins Report Setting the Stage

4. 4 Desired Characteristics Science- and engineering-driven Enabling discovery, learning and innovation Promising economies of scale and scope Supporting data-, instrumentation-, compute- and collaboration-intensive applications High-end to desktop Heterogeneous Interoperable-enabled by collection of reusable, common building blocks

5. 5 Hardware Integrated Cyberinfrastructure meeting the needs of a community of communities CI Services & Middleware Applications Environmental Science High Energy Physics Proteomics/Genomics Learning Science Gateways CI Commons Distributed Resources Training & Workforce Development Discovery, Learning & Innovation Science of CI

6. 6 Overarching Principles Enrich the portfolio Demonstrate transformative power of CI across S&E enterprise Empower range of CI users – current and emerging System-wide evaluation and CI-enabling research informs progress Develop intellectual capital Catalyze community development and support Enable training and professional development Broaden participation in the CI enterprise Enable integration and interoperability Develop shared vision, integrating architectures, common investments Promote collaboration, coordination and communication across fields Share promising technologies, practices and lessons learned

7. 7 S&E Gateways CI Commons Core Activities - Compute-centric - Information-intensive - Instrumentation-enabling - Interactive-intensive Integrative CI “system of systems” CI Planning - A Systems Approach CI-enabling Research Domain-specific strategic plans -Technology/human capital roadmaps -Gaps and barrier analyses (policy, funding,..) System-wide activities -Education, training -(Inter)national networks -Capacity computing -Science of CI

8. 8 Baselining NSF CI Investments Core (examples) Protein Databank Network for Earthquake Engineering Simulation International Integrated Microdata Access System Partnerships, Advanced Computational Infrastructure Circumarctic Environmental Observatory Network National Science Digital Library Pacific Rim GRID Middleware Priority Areas (examples) Geosciences Network international Virtual Data Grid Laboratory Grid Research and Applications Development.. and others too numerous to mention (~$400M in FY’04)

9. 9 CI Building Blocks Partnerships for Advanced Computational Infrastructure (PACI) –Science Gateways (Alpha projects, Expeditions) –Middleware Technologies (NPACKage, ATG, Access Grid in a Box, OSCAR ) –Computational Infrastructure NSF Middleware Initiative (NMI) –Production software releases –GridsCenter Software Suite, etc. Early Adopters –Grid Physics Network (GriPhyN), international Virtual Data Grid Laboratory (iVDGL) –National Virtual Observatory –Network for Earthquake Engineering Simulation (NEES) –Bio-Informatics Research Network (BIRN) Extensible Terascale Facility (TERAGRID) –Science Gateways (value-added of integrated system approach) –Common Teragrid Software Stack (CTSS) –Compute engines, Data, Instruments, Visualization

10. 10 Extensible Terascale Facility (TERAGRID) A CI Pathfinder Pathfinder Role – integrated with extant CI capabilities – clear value-added supporting a new class of S&E applications Deploy a balanced, distributed system – not a “distributed computer” but rather – a distributed “system” using Grid technologies computing and data management visualization and scientific application analysis remote instrumentation access Define an open and extensible infrastructure – an “enabling cyberinfrastructure” demonstration – extensible beyond original sites with additional funding NCSA, SDSC, ANL, Caltech and PSC ORNL, TACC, Indiana University, Purdue University and Atlanta hub

11. 11 Resource Providers + 4 New Sites NCSA: Compute IntensiveSDSC: Data IntensivePSC: Compute Intensive IA64 Pwr4 EV68 IA32 EV7 IA64 10 TF IA-64 128 large memory nodes 230 TB Disk Storage 3 PB Tape Storage GPFS and data mining 4 TF IA-64 DB2, Oracle Servers 500 TB Disk Storage 6 PB Tape Storage 1.1 TF Power4 6 TF EV68 71 TB Storage 0.3 TF EV7 shared-memory 150 TB Storage Server 1.25 TF IA-64 96 Viz nodes 20 TB Storage 0.4 TF IA-64 IA32 Datawulf 80 TB Storage Extensible Backplane Network LA Hub Chicago Hub IA32 Storage Server Disk Storage Cluster Shared Memory Visualization Cluster LEGEND 30 Gb/s IA64 30 Gb/s Sun ANL: VisualizationCaltech: Data collection analysis 40 Gb/s Backplane Router

12. 12 Common Teragrid Software Stack (CTSS) Linux Operating Environment Basic and Core Globus Services –GSI (Grid Security Infrastructure) –GSI-enabled SSH and GSIFTP –GRAM (Grid Resource Allocation & Management) –GridFTP –Information Service –Distributed accounting –MPICH-G2 –Science Portals Advanced and Data Services –Replica Management Tools –GRAM-2 (GRAM extensions) –CAS (Community Authorization Service) –Condor-G (as brokering “super scheduler”) –SDSC SRB (Storage Resource Broker) –APST user middleware, etc.

13. 13 TERAGRID as a Pathfinder Science Drivers - Gateways -On-demand computing -Remote visual steering -Data-intensive computing Systems Integrator/Manager -Common TERAGRID Software Stack -User training & services -TERAGRID Operations Center Resource Providers -Data resources, compute engines, viz, user services

14. 14 Focus on Policy and Social Dynamics Policy issues must be considered up front Social engineering will be at least as important as software engineering Well-defined interfaces will be critical for successful software development Application communities will need to participate from the beginning Fran Berman, SDSC

15. 15 CI Building Blocks Partnerships for Advanced Computational Infrastructure (PACI) –Science Gateways (Alpha projects, Expeditions) –Middleware Technologies (NPACKage, ATG, Access Grid in a Box, OSCAR ) –Computational Infrastructure NSF Middleware Initiative (NMI) –Production software releases –GridsCenter Software Suite, etc. Early Adopters –Grid Physics Network (GriPhyN), international Virtual Data Grid Laboratory (iVDGL) –National Virtual Observatory –Network for Earthquake Engineering Simulation (NEES) –Bio-Informatics Research Network (BIRN) Extensible Terascale Facility (TERAGRID) –Science Gateways (value-added of integrated system approach) –Common Teragrid Software Stack (CTSS) –Compute engines, Data, Instruments, Visualization

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17. 17 CI Commons Goals Commercial-grade software – stable, well-supported and well- documented User surveys and focus groups inform priority-setting Development of “Commons roadmap” Unanswered questions What role does industry play in development and support of products In what timeframe will software and services be available How will customer satisfaction be assessed and by whom What role do standards play – and does an effective standards process exist today

18. 18 CI Commons Community Development Approach End-user communities willing and able to modify code Adds features, repairs defects, improves code Customizes common building blocks for domain applications Leads to higher quality code, enhances diversity Natural way to set priorities Requires Education, training in community development methodologies Effective Commons governance plan Strong, sustained interaction between Commons developers and community code enhancers

19. 19 Challenging Context Cyberinfrastructure Ecology –Technological change more rapid than institutional change –Disruptive technology promises unforeseen opportunity Seamless Integration of New and Old –Balancing upgrades of existing and creation of new resources –Legacy instruments, models, data, methodologies Broadening Participation Community-Building Requires Effective Migration Strategy

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21. 21 Kelvin Droegemeier, Center for Analysis and Prediction of Storms (CAPS) University of Oklahoma On-Demand: Severe Weather Forecasting Several times a week, need multiple hours dedicated access to a multi-Teraflops system.

22. 22 On Demand: Brain Data Grid Duke UCLA Cal Tech Stanford U. Of MN Harvard NCRR Imaging and Computing Resources UCSD Cal-(IT) 2 SDSC Deep Web Surface Web Cyberinfrastructure Linking Tele-instrumentation, Data Intensive Computing, and Multi-scale Brain Databases. Wireless “Pad” Web Interface Objective: Form a National Scale Testbed for Federating Large Databases Using NIH High Field NMR Centers Mark Ellisman, Larry Smarr, UCSD

23. 23 membrane potential (s) bath concentration (s) – Inside / Outside bath diffusion constant channel diffusion constant time step-size number of time steps channel diameter channel length force profile ion trajectory ion type temperature ionic strength protein dielectric water dielectric protein 3-d structure coordinates technical specifications * partial charges of titratable residues pH of bath interaction potentials between titratable groups in protein temperature ionic strength protein dielectric water dielectric protein 3-d struct coord technical specifications * Related by sampling method used for calculation of diffusion constant in MD simulations Hole Profile analysis protein 3-d structure coordinates one position in channel approximate channel direction technical specifications*** protein/lipid 3-d struct coord and topology force field sets ion-water ratio ion type/initial positions simulation time step-size simulation methodology specifications ** Hole Analysis Electrostatics - I Molecular Dynamics Electrostatics - II Brownian Dynamics User Web Portal TeraGrid Resources Data Workflow Manager Workflow Manager Globus Client Globus Client Molecular Biology Simulation Eric Jakobsson, UIUC