1 Building National Cyberinfrastructure Alan Blatecky Office of Cyberinfrastructure EPSCoR Meeting May 21,

Framing the Challenge: Science and Society Transformed by Data  Modern science  Data- and compute- intensive  Integrative, multiscale  Multi-disciplinary Collaborations for Complexity  Individuals, groups, teams, communities  Sea of Data  Age of Observation  Distributed, central repositories, sensor- driven, diverse, etc 2

Explosive Growth in Size, Complexity, and Data Rates  Enormous data sets are being generated by modern experiments and observations  Automatic extraction of new knowledge about the physical, biological and cyber world continues to accelerate  Infusion of data-intensive computation into science, engineering and education is revolutionizing research  Multi-cores, concurrent and parallel algorithms, virtualization and advanced server architectures will enable data mining and machine learning, and new approaches for innovation and discovery

Computer Architecture Trends  Continuing growth in number of cores  Increased use of hybrid accelerators  Advances in interconnect technologies will slow; more complex memory subsystems will be deployed  Power consumption becoming ever more important because of cost and performance  Application performance will be dominated by data movement  Clouds and data centers will play an increasingly larger role in data and compute infrastructure 4

Software Challenges  Simulation and model scalability is a major requirement for algorithm research and development  Parallel programming research is required to address order of magnitude changes in compute resources  New operating systems, architectures, file systems research, fault tolerance, verification and validation, complex simulation, and cybersecurity  Inadequate numbers of software workforce and expertise being produced  Focus on sustainability and usability is essential 5

Grand Challenge Communities Learning & Workforce Development Campus Bridging, Cybersecurity Advanced Computational Infrastructure Data Scientific Instruments Software Innovation, Discovery CIF21: Cyberinfrastructure Framework for 21 st Century Science and Engineering 6

Scientific Data Challenges 7 Bytes per day Genomics LHC TeraGrid, Blue Waters Square Kilometer Array Genomics LHC Climate, Environment LSST Exa Bytes Peta Bytes Tera Bytes Giga Bytes Climate, Environment Volume/Growth Useful Lifetime Distribution Data Access Many smaller datasets…

NSF Data strategy  Establish a national data infrastructure to support science, engineering and education  Ensure that this infrastructure stays at the most advanced state of sophistication and is sustainable  Support transformative interdisciplinary and collaborative research stimulated by data  Development of the next generation of compute and data intensive workforce  Development of a suite of policies for data, software, publications and other digital outputs 8

Advanced Computing Infrastructure Strategy  Foundational research to fully exploit parallelism and concurrency through innovations  Applications research and development in high end computing resources  Building, testing and deploying innovative resources in a collaborative environment  Development of comprehensive education and workforce programs  Development of grand challenge community programs 9

Scientific Software Elements: Small groups, individuals Scientific Software Integration: Research Communities Scientific Software Innovation Institutes: Large Multidisciplinary Groups Multi-year Creating Scalable Software Development Environments  Create a software ecosystem that scales from individual or small groups of software innovators to large hubs of software excellence Focus on innovation Focus on sustainability 10

Cyber-infrastructure: EarthCube Goal: to transform the conduct of research in geosciences by supporting community-based cyberinfrastructure to integrate data and information for knowledge management across the Geosciences. Community: More than 900 members subscribed to EarthCube web site. Second Charette: June GEO-OCI Partnership 11

Some observations  Science and Scholarship are team sports  Collaboration/partnerships will change significantly  Growth of dynamic coalitions and virtual organizations  International collaboration becomes ever more important  Innovation and discovery will be driven by analysis  Mining vast amounts of new and disparate data  Collaboration and sharing of information  Mobility and personal control will continue to drive innovation and research communities  Gaming, virtualization and social networking will transform the way we do science, research and education 12

EPSCoR Cyberinfrastructure Suggestions  Become a provider rather than just a user  Contribute to XSEDE as a resource  Build and coordinate data collections & resources  Issue is not scale, but capability, diversity and multi-disciplinarity  Coordinate efforts, develop collaborative projects, practice community building  Focus on Education, especially CDS&E 13

Data Infrastructure Building Blocks (DIBBs) Software Infrastructure for Sustained Innovation (SI2) EarthCube Core Techniques and Technologies for Advancing Big Data Science & Engineering (BIG DATA) Computational and Data Intensive Science and Engineering in the Mathematical and Physical Sciences (CDS&E) Campus Cyberinfrastructure - Network Infrastructure and Engineering Program (CC-NIE) Science, Engineering and Education for Sustainability NSF- Wide Investment (SEES) Integrative Graduate Education and Research Traineeship, or IGERT (CIF21 Track) 14 Solicitations that build Cyberinfrastructure

Discussion 15