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Data- and Compute-Driven Transformation of Modern Science

Data- and Compute-Driven Transformation of Modern Science Update on the NSF Cyberinfrastructure Vision People, Sustainability, Innovation, Integration. Edward Seidel Acting Assistant Director, Mathematical and Physical Sciences, NSF (Director, Office of Cyberinfrastructure ).

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Data- and Compute-Driven Transformation of Modern Science

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  1. Data- and Compute-Driven Transformation of Modern Science Update on the NSF Cyberinfrastructure Vision People, Sustainability, Innovation, Integration Edward Seidel Acting Assistant Director, Mathematical and Physical Sciences, NSF (Director, Office of Cyberinfrastructure)

  2. Profound Transformation of ScienceGravitational Physics • Galileo, Newton usher in birth of modern science: c. 1600 • Problem: single “particle” (apple) in gravitational field (General 2 body-problem already too hard) • Methods • Data: notebooks (Kbytes) • Theory: driven by data • Computation: calculus by hand (1 Flop/s) • Collaboration • 1 brilliant scientist, 1-2 student 2

  3. Profound Transformation of ScienceCollision of Two Black Holes • Science Result • The “Pair of Pants” • Year: 1972 • Team size • 1 person (S. Hawking) • Computation • Flop/s • Data produced • ~ Kbytes (text, hand-drawn sketch) • 400 years later…same! • 3D Collision • Science Result • Year: 1998 • Team size • ~ 15 • Data produced • ~ 50Gbytes • Science Result • The “Pair of Pants” • Year: 1994 • Team size • ~ 10 • Data produced • ~ 50Mbytes • Impact of HPC taking root 3

  4. Now: Complexity of UniverseLHC, Gamma-ray bursts! • Gamma-ray bursts! • GR now soluble: complex problems in relativistic astro can now be attacked • All energy emitted in lifetime of sun bursts out in a few seconds: what are they?! Colliding BH-NS? SN? • GR, hydrodynamics, nuclear physics, radiation transport, neutrinos, magnetic fields: globally distributed collab! • Scalable algorithms, complex AMR codes, viz, PFlops*week, PB output! • LHC: What is the nature of mass? Higgs particle? • ~10K scientists, 33+ countries, 25PB data, distributed! • Planetary lab for scientific discovery! Remote Instrument Remote Instrument 4

  5. Grand Challenge Communities Combine it All...Where is it going to go? Same CI useful for black holes, hurricanes 5

  6. Grand Challenge Communities New social networking technologies will be needed for collaborations at this scale. Allen, Schnetter, et al • Complex problems require many disciplines, all scales of collaborations, advanced CI • Individuals, groups, teams, communities • Multiscale Collaborations: Beyond teams • Grand Challenge Communities assemble dynamically • Emergency forecasting: flu, hurricane, tornado... • Gamma-ray bursts, supernovae, • They can only work by sharing data • Place requirements on • CI: software, networks, collaborative environments, data, sharing, computing, etc • Scientific culture, reproducibility, access, university structures 6

  7. Campus DataNet Learning & Work Force Needs & Opportunities DataNet Campus Track 2 Campus Campus Nets Campus Campus Campus Campus Virtual Organizations for Distributed Communities Track 2 Track 2 DataNet DataNet DataNet High Performance Computing Data & Visualization/Interaction NSF Vision and National CI Blueprint Education Crisis: I need all of this to start to solve my problem! Software Track 1

  8. What is Needed? NSF-wide CI Framework for 21st Century Science & Engineering

  9. CF21: Cyberinfrastructure Framework for 21st Century Science & Engineering Comprehensive, balanced, integrated, national high performance CI; Dear Colleague Letter released December, 2009 by all units • High-end computation, data, visualization for transformative science; sustainability, extensibility • Facilities/centers as hubs of innovation • MREFCs and collaborations including large-scale NSF collaborative facilities, international partners • Software, tools, science applications, and VOscritical to science, integrally connected to hardware • Campuses fundamentally linked; grids, clouds, loosely coupled campus services, policy to support • People. Comprehensive approach workforce development for 21st century science and engineering

  10. Software: David Keyes, Columbia/KAUST (MPS) Grand Challenge Communities/VOs: Tinsley Oden, Austin (ENG) Data & Viz: Shenda Baker, Harvey Mudd (MPS); Tony Hey, (CISE) Campus Bridging: Craig Stewart, IU (BIO) Education & Workforce: Alex Ramirez, CEOSE Computing: Thomas Zacharia, ORNL/UTK (DOE) ACCI Task Forces • Timelines: 12-18 months • Advising NSF • Workshop(s) • Recommendations • Input to NSF informs CF21 programs, 2012 CI Vision Plan 10

  11. Preliminary Task Force (TF) Results • Computing TF Workshop Interim Report • Rec: Address sustainability, people, innovation • Developing CF21-oriented HPC program • Software TF Interim Report • Rec: Address sustainability, create long term, multi-directorate, multi-level software program • Developing CF21-oriented integrated program • GCC/VO TF Interim Report • Rec: Address sustainability, OCI to nurture computational science across NSF units • Concept paper coming to NSF • PITAC: “inadequate structures within the Federal government and the academy today do not effectively support computational science”

  12. Track 2 Track 2 Track 2 DataNet DataNet Roadmap and Timelines • National Petascale Facility • CF21Computing program; hubs of innovation • CF21 Software • People, VOs • Better campus integration • Major facilities CI planning Updating for 2013 & Beyond • NSF CF21 Strategic Plan 2012-2017 • Integration • Stronger interagency interaction • New science activities enabled DataNet DataNet DataNet Task Force Reports and Workshops 2013 2010 2011 2012

  13. OCI Special Role in CF21 • Driver for integrative CI activity via CF21 • Working with all units, community • Develop vision and implementation plan • OCI budget ¼ NSF CI; other units critical! • Catalyst for coordinated, linked investments • CI in all forms: campus, centers, MREFC • Leadership in R&D for prototypes, pilots, best practices • Looking for coherence, re-use of CI • Science applications enabled by CI • People: supporting next generation of CI researchers • Steward for NSF-wide computational science • Working with all NSF units to provide sustainable home

  14. 2009 PetaApps, CDI, CI-Reuse 70% OCI ARRA: Innovations in software, apps, people • PetaApps: OCI led, NSF-wide • Partners: MPS, CISE, ENG, GEO and SBE • 2009: $16M from OCI, matched for total of $35M! • 2007-9 Total: 42 awards, ~200 proposals, $60M • Equivalent to entire Track-2 award (including O&M) • CDI: CISE led, NSF-wide • OCI a “Big 4” contributor in FY09! (CISE, ENG, OCI, MPS…), $63M total • OCI contributed to 22 awards, more than $10M • CI Re-Use: Internal OCI-led NSF program • OCI venture fund of $4M to catalyze • CISE, GEO, OPP, BIO and MPS • 13 awards, > $20M investments catalyzed by OCI

  15. MREFC Projects:NEON, and Cyber-GIS

  16. National Ecological Observatory NetworkNew horizons for large-scale biology James Collins, Assistant Director Biological Sciences Directorate, NSF Office of Management and Budget Briefing October 5, 2009

  17. What is NEON? In theory all life is interconnected…. NEON is an integrated sensing system to detect, understand, and forecast the consequences of climate and landuse change and the effects of invasive species on the biosphere of the U.S. at the regional and continental scales. Enables research to address …. • How does the effect of climate change on biosphere processes vary along regional and continental gradients? • What is the effect of the biosphere on regional climate? • How will land use change affect the dispersion of invasive species through a region and across the continent? • How do large scale physical processes produce regional to continental ecological responses?

  18. Cyberinfrastructure Research Education Decision Support Distributed Distributed Centralized Operational and Support Systems (OSS) In situ Sensors Data Management Satellite Remote Sensing Data Acquisition Data Process Management Portals Airborne Remote Sensing Biological Monitoring and Measurements Data Services Future Sources Data Products Archive Raw

  19. Landuse Analysis Package Goal to “… collate existing data … on past and current land use practices as well as economic and social data that are useful for prediction of future land use processes” • On land use, land cover and land management -- drivers of change • Across multiple spatial scales (local to the continental) for the entire NEON realm • Across multiple temporal scales (days to decades to centuries) to help understand legacy effects of prior land use on ecosystem function and performance • For use by ecological modelers and forecasters to extend models to a continental scale The NEON Land Use Analysis Package (LUAP) provides information: (ISEP, NOD)

  20. Landuse Analysis Package • NEON must scale from site to region to continent • Remote sensing, aircraft borne, satellite. • Spectral and LiDAR data converted into 3D biogeochemical fingerprints of earth surface including vegetation and human structures. • GIS critical to convert sensor data to spatial data • USGS will provide satellite data from MODIS, Landsat, etc. • NEON will ingest other spatial data from and convert them into spatial data using GIS

  21. New Approaches with CF21

  22. Emerging CF21 Concepts • CF21 HPC program • Sustainability, hubs of innovation + experimental • Looking to develop new program in FY10 • CF21 Software Institutes and Innovators • Transform innovation into sustainable software • Significant multiscale, long-term program • Connected institutes, teams, investigators • Integrated into CF21 framework w/Directorates Hierarchical structures that link innovation and sustainability, integrate with national and campus activities

  23. Concept for NSF-wide Fellowships for Transformative Computational Science • Goal: People! Build innovative researchers in computational science by supporting outstanding postdocs • Emphasize central role of cyberscience in all sciences (physical, biological, geological, mathematical, social, behavioral, economic, computer, information and data) • Support cyberscience research and education: CI-based, cross disciplinary boundaries • Use CI to make revolutionary advances in their disciplines • Research and develop CI that enables innovative computational practices

  24. Summary • Science is being revolutionized through CI • Compute, data, networking advance suddenly 9-12 orders of magnitude after 4 centuries • All forms of CI—including GIS—needed for science • NSF responsive: developing much more comprehensive, integrated CF21 initiative • All units involved; OCI, CISE play important roles • Community deeply engaged in planning • Activities ramp up in FY11-12 and beyond • People, sustainability, innovation, integration • Longer term programs, better linked, hubs of innovation • Support computational scientists who develop and/or use advanced CI

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