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

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/ 2

Setting the Stage

In summary then, the opportunity is here to create cyberinfrastructure that enables more ubiquitous, comprehensive knowledge environments become functionally complete ..

that in terms of people, data, information, tools, and instruments and that include unprecedented capacity for computational, storage, and communication.

They can serve individuals, teams organizations in ways that revolutionize and what they do, how they do it, and who can participate .

- The Atkins Report 3

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 4

Integrated Cyberinfrastructure

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

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 6

CI Planning - A Systems Approach

S&E Gateways Domain-specific strategic plans -Technology/human capital roadmaps -Gaps and barrier analyses (policy, funding, ..)

CI-enabling Research

Integrative CI “system of systems” Core Activities System-wide activities -Education, training -(Inter)national networks -Capacity computing -Science of CI CI Commons - Compute-centric - Information-intensive - Instrumentation-enabling

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) 8

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.

Extensible Terascale Facility (TERAGRID) – Science Gateways (value-added of integrated system approach) – Common Teragrid Software Stack (CTSS) – Compute engines, Data, Instruments, Visualization 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) 9

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 10

Resource Providers + 4 New Sites

Caltech

: Data collection analysis

0.4 TF IA-64 IA32 Datawulf 80 TB Storage IA64 IA32 30 Gb/s 30 Gb/s 4 TF IA-64 DB2, Oracle Servers 500 TB Disk Storage 6 PB Tape Storage 1.1 TF Power4 IA64 Pwr4 LA Hub SDSC

: Data Intensive

Sun LEGEND Cluster Storage Server Visualization Cluster Shared Memory Disk Storage Backplane Router Extensible Backplane Network 40 Gb/s Chicago Hub ANL

: Visualization

IA32 IA64 IA32 1.25 TF IA-64 96 Viz nodes 20 TB Storage 30 Gb/s IA64 10 TF IA-64 128 large memory nodes 230 TB Disk Storage 3 PB Tape Storage GPFS and data mining NCSA

: Compute Intensive

30 Gb/s 30 Gb/s EV7 6 TF EV68 71 TB Storage 0.3 TF EV7 shared-memory 150 TB Storage Server EV68 Sun PSC

: Compute Intensive 11

• • 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 Common Teragrid Software Stack (CTSS) • 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.

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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

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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 14

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.

Extensible Terascale Facility (TERAGRID) – Science Gateways (value-added of integrated system approach) – Common Teragrid Software Stack (CTSS) – Compute engines, Data, Instruments, Visualization 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) 15

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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 17

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 community code enhancers developers and 18

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 19

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On-Demand: Severe Weather Forecasting

Several times a week, need multiple hours dedicated access to a multi-Teraflops system.

Kelvin Droegemeier, Center for Analysis and Prediction of Storms (CAPS) University of Oklahoma 21

Cal Tech Stanford

On Demand: Brain Data Grid

Objective: Form a National Scale Testbed for Federating Large Databases Using NIH High Field NMR Centers

U. Of MN SDSC NCRR Imaging and Computing Resources UCSD Cal-(IT) 2 Harvard

Surface Web Deep Web

UCLA Duke

Cyberinfrastructure Linking Tele-instrumentation, Data Intensive Computing, and Multi-scale Brain Databases.

Mark Ellisman, Larry Smarr, UCSD Wireless “Pad” Web Interface 22

Molecular Biology Simulation

User Web Portal

• 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 Related by sampling method used for calculation of diffusion constant in MD simulations • ion trajectory • ion type •temperature • ionic strength • protein dielectric • water dielectric • protein 3-d structure coordinates • technical specifications * • partial charges of titratable residues

Molecular Dynamics

• 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 Profile analysis

Hole Analysis

• protein 3-d structure coordinates • one position in channel • approximate channel direction • technical specifications ***

Electrostatics - I

• pH of bath • interaction potentials between titratable groups in protein • temperature • ionic strength • protein dielectric • water dielectric • protein 3-d struct coord • technical specifications *

Data Workflow Manager Globus Client TeraGrid Resources

23 Eric Jakobsson, UIUC