Cyberinfrastructure November 16, 2006

1. CyberinfrastructureNovember 16, 2006 National Science Foundation Directorate for Engineering Abhijit Deshmukh PD, Manufacturing Enterprise Systems/CMMI Office of Cyberinfrastructure ENG Cyberinfrastructure Working Group

2. Advances in components of CI-systems for S&E R&E 30+ disciplinary workshops on CI vision & impact NSB & Community Input High Performance Computing Data, Data Analysis & Visualization Virtual Organizations Learning & Workforce Development Vision Framework NSF internal working groups Complex, multi-scale, multidisciplinary S&E research challenges CI Council, Directorate/Office CI Activities, OCI, ACCI NSF Cyberinfrastructure Vision • All directorates and offices support cyberinfrastructure. • Science-driven partnerships between creation, provisioning and use of CI • Supports integrated research and education and broadened access and participation. Draft available at www.nsf.gov/oci/

3. Track 1: One solicitation funded over 4 years: $200M acquisition + additional O&M cost. Track 2: Four solicitations over 4 years: $30M/yr acquisition + additional O&M cost. First track 1 approved 8-07 Life High Performance Computing increasingly important tool for understanding Satellite tobacco mosaic virus, P. Freddolino et al. Aldehyde dehydrogenase, T. Wymore and S. Brown Matter I. Shipsey The Environment Society John Q Public S.-Y. Kim, M. Lodge, C. Taber.

4. Data, Data Analysis & Visualization • Challenges: increased scale, heterogeneity, and re-use value of digital scientific information and data. Inadequate digital preservation strategy of long-lived data. • Taking initial steps to catalyze the development of a federated, global system of science and engineering data collections that is open, extensible, evolvable, (and appropriately curated and long-lived.) • Complemented by a new generation of tools and services to facilitate data mining, integration, analysis, visualization essential to transforming data into knowledge. • NSF Leadership for OSTP/Interagency Working Group on Digital Data

5. Virtual Organizations • Distributed virtual organizations are based upon CI that provides flexible, secure, coordinated resource sharing among dynamic collections of individuals, institutions, and resources. • Resources and services include HPC, data/information management, sensor-nets/observatories, linked through global networking and middleware, and accessed by people through web portals and workflow environments. • Challenges being address include tools for more rapid building and ease of use, interoperability/middleware, high performance, end-to-end networking, and dynamic reconfiguration, social issues, assessment of impact, and economic and technical sustainability. NVO LEAD iVDgL ATLAS NEES NanoHub

6. Learning supported by CI. (cyber-enabled learning). • Workforce development to create and use CI for S&E research and education. • Broadened participation: Exploit the new opportunities that cyberinfrastructure brings for … people who, because of physical capabilities, location, or history, have been excluded from the frontiers of scientific and engineering research and education. • Explore CI support for integrated research and education. Learning & Workforce Development EPIC BIOINFORMATICS CI INSTITUTE CyberBridges MARIACHI

7. Duality of CI • CI for Big Science • Flops: Mega, Giga, Tera, Peta, … • Large data sets • Fire and forget – batch processing • Size, latency, resource discovery are NOT critical • CI for Pervasive Use • Artificial nervous system for engineered systems • Facilitates creation of adaptable/ reconfigurable/ evolvable systems • Control and coordination: computational and non-computational resources • Size, latency, bandwidth, dynamic composability, real time constraints are VERY important

8. CI and ENG • ENG believes that cyberinfrastructure will play an essential role in future engineering-related research. • ENG’s needs in this realm often dovetail with other directorates; however, ENG also has unique requirements and leadership capabilities: • Sensor networks and real-time issues • Design and control of complex systems • Multi-scale phenomena • ENG can contribute significantly to the creation of this infrastructure • Novel processors, data storage and networking • Design, management and control of CI

9. ENG Investments in CI(FY 04-06 by Category) The final ENG Totals column is truncated to preserve scale, and totals $117,317,000. Legend HPC: High-performance Computing Data: Data, Data Analysis and Visualization VO: Virtual Organizations Workforce: Learning and Workforce DCI: Development and Deployment of CI RCI: Research Enabling CI UCI: Use of CI

10. ENG CI Priorities (FY 2007 – 2012) • Engineering Research Frontiers Enabled by CI (EFRI: ARES-CI) • Engineering Gateways/ Virtual Organizations (Seed Grants) • Multi-scale, Multi-phenomena Modeling (SBES) • Research Enabling Next Generation CI Capabilities (PetaApps) • CI Education and ENG Education using CI (CIEG)

11. Autonomously Reconfigurable Engineered Systems Enabled by CI (ARES-CI) NSF 06-596 • From Complexity to Reconfigurability • Complexity arises from the need to be robust in presence of anticipated faults • Complex systems are robust to known uncertainty – yet fragile to unknown events • Reconfigurable or topologically modifiable systems enable robustness to unknown failures • Core Unanswered Questions • What are the fundamental principles underlying design and control of reconfigurable systems? • How much reconfigurability is enough? • What/when to change/reconfigure? • Continuum of adaptability, reconfigurability and evolvability ENG

12. Engineering Gateway Seed Grants Anticipated Activity • Virtual organizations (VOs): Communities of researchers and educators linked by CI resources • Can play an important role in promoting collaboration • Early NSF experience with gateways has been very positive • nanoHUB.org for nanotechnology researchers • NEES for earthquake engineering researchers • NSF Engineering is considering seed grants to assist communities form VOs ENG

13. Overarching Framework for Multiscale Modeling: atomistic  micro  meso  macro Key Issue: interfaces/exchanges between models at different length and time scales • Questions: • What information needs to be transferred from one model segment to another? • What are the correct and most effective ways to achieve such transfer of information? • What physical principles must be satisfied during the transfer of information or simulation results? Need a set of consistent logical, mathematical, and physical rules to govern information transfer across the interfaces

14. Simulation-based Engineering Science • CI will help catalyze a transformation to high-fidelity, simulation-based engineering science. • Simultaneous advances of the models, methods and algorithms that underpin the components are crucial for realizing the potential of CI. • Example: Simulation-based planning for vascular bypass surgery. From left: (1) MR image data, (2) preoperative geometric solid model, (3) operative plan, (4) computed blood flow velocity in aorta and proximal end of bypass, and (5) postoperative image data used to validate predictions. (UTA and Stanford) • WTEC study planned in FY 07

15. Accelerating Discovery in Science and Engineering Through Petascale Simulations and Analysis (PetaApps) Anticipated Activity • Anticipated program size: $15M • Expected award amounts: up to $1,000,000 • Potential proposal topics: • Enhancing algorithmic scalability exploiting multi-threaded, highly parallel, hierarchical architectures • Improving and creating data sampling, analysis and clustering algorithms for large data sets • Developing innovative modeling, simulation or optimization algorithms suitable for petascale systems • Innovative computational techniques that were previously not viable due to hardware capability OCI, ENG, MPS

16. CI Experiences for Graduate Students Dear Colleague Letter NSF 06-044 • “Boot camp” for cyberinfrastructure • Goal: Train engineering PhD students in CI tools and techniques • Pilot program in Summer 2007 • Summer residency at the San Diego Supercomputer Center • Supplements to existing MES, SEE, OR grants • Supplement request deadline: December 1, 2006 • Anticipate expanding to other facilities and other programs in the future ENG

17. Cyberinfrastructure Training, Education(CI-TEAM) Anticipated in FY 07 (past solicitation NSF 06-548) • Goals: • Develop a diverse cyberinfrastructure workforce • Foster inclusion in cyberinfrastructure activities of diverse groups • FY06 program funds ~ $10 M for two types of awards: • Demonstration Projects ≤ $250,000 • Implementation Projects ≤ $1,000,000 • Demonstration Project: Exploratory with the potential to serve as pathfinder for larger-scale implementation activities in the future • Implementation Project: Expected to deliver sustainable learning and workforce development activities that complement ongoing NSF investment in cyberinfrastructure • Multidisciplinary teams, significant impact from partnerships • Leveraged cyberinfrastructure, replicable and (potentially) scalable OCI

18. Other Opportunities

19. Strategic Technologies For CI (STCI) Standing Program • Two target dates each year: 2nd Thursday in February & August • Unsolicited proposals for the development and/or demonstration of CI services and resources or for CI education, outreach and training activities that fall outside the scope of other programs at NSF or elsewhere. OCI

20. Software Development For CI (SDCI) Program Solicitation NSF 07-503 • Full Proposal Deadline: January 22, 2007 • Program size: 10 to 20 awards, $14M total funding • Award amounts: $50,000 - $1,000,000/year, 2-3 years • Focus areas for FY07: • High Performance Computing (HPC) environments • Digital data acquisition, discovery, access, analysis, and preservation • Middleware capabilities and services to support distributed resource sharing and virtual organizations OCI

21. National Digital Data Framework Concept Anticipated Activity • Digital repositories launched with explicit goal to achieve long term sustainability • Expertise in: • Cyberinfrastructure, library and archival sciences, data science, computer and information science, social and behavioral sciences, economics, domain sciences • Combination of awards designed to test: • Sustainability models • Economies of scale • New partnerships across sectors OCI

22. ENG Community Input • ENG Ad Com Subcommittee on Cyberinfrastructure: “A Process-Oriented Approach to Engineering Cyberinfrastructure” • Assessment: CI user requirements, resource tracking, infrastructure usability metrics • Coordination: with OCI, other directorates, other agencies • Planning: ENG priorities • Building the “Innovation Loop”: ENG CI research challenges, synergies between CI research, development and deployment • ENG sponsored community-wide workshops and reports on CI strategies • ENG communities need unique engineering gateways that focus on different communities • Blue Ribbon Panel recommends a significant investment in multi-scale, multi-phenomenon modeling across the engineering disciplines • ENG should invest in creation of focused “facilities" (e.g., hazards, sensors, or environmental observatories) that will enable frontier research in different disciplines

23. Thank you