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Kyran (Kim) Mish, Director Center for Computational Engineering

NEES Networking Needs The NEES MRE: Where the Infrastructure Community Meets the Cyberinfrastructure Community. Kyran (Kim) Mish, Director Center for Computational Engineering Lawrence Livermore National Laboratory. So Exactly What is NEES?.

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Kyran (Kim) Mish, Director Center for Computational Engineering

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  1. NEES Networking NeedsThe NEES MRE: Where the Infrastructure Community Meets the Cyberinfrastructure Community Kyran (Kim) Mish, Director Center for Computational Engineering Lawrence Livermore National Laboratory

  2. So Exactly What is NEES? • Network for Earthquake Engineering Simulation • NEES is a distributed array of experimental sites, grid-based data repositories, tool archives, and computational resources, all seamlessly linked (hopefully!) • NEES has four components, with three now funded: • The consortium, which will run NEES after 2004 • The consortium development (CD) builds the consortium • The experimental sites, which provide data and content • The systems integration (SI) effort, termed NEESgrid • Network drivers include telepresence, curated repositories, scalable HPC, experimental-numerical coupling, short- and long-term QoS issues

  3. Example NEES Experimental Site • Geotechnical Centrifuge at UC Davis

  4. NEES Network Stakeholders • Experimental Facilities • Shake tables, centrifuges, wave tanks, field sites • Resource providers • Computers, software, storage, networks • End users • Researchers, practicing engineers, students, … • Operational facilities • NCSA/NEESgrid  NEES Consortium in 2004

  5. Experimental Component Grid Ops Center Grid Data Repository Campus Net Component NEESgrid Component Internet Fabric and Operations Hub A Hub B Hub C Teleobservation Equipment NEESpop A NEESpop B Experimental Equipment Telepresence Equipment Passive coPI Data Cache Video I/O Active PI Audio I/O Data Cache Site A: Experimental Data Producer Site B: Remote Lead Investigator Site C: Passive Collaborator Typical NEES Cyberinfrastructure

  6. Infrastructure vs. Cyberinfrastructure • Characteristics of Infrastructure Culture • Risk averse, which leads to slow technology adoption • Code-based practice to defend against litigation • Follow community wants/needs whenever possible • Goal is highest reliability, e.g., MTBF • Characteristics of Cyberinfrastructure Culture • High-risk, “innovate or die trying” approach to technology • Best-practices approach leaves legal issues dangling • Develop technology, then look for a market • Goal is highest performance, e.g., TFLOPS

  7. Typical NEES Infrastructure • Infrastructure community builds ubiquitous networks • Robust, reliable, redundant, extensible over time • Generally, these networks degenerate gracefully with load • High-value packets are seldom lost, thankfully

  8. Consider Science and Engineering • Science is a process whose desired outcome is scientific truth • Open sharing of data in “community of science” • Metric is “evidence of a creative mind” • Engineering is a profession whose desired outcome is technology • Information may be proprietary, IP dominates • Metric is financial or market-driven (share) • NEES MRE must respect these differences

  9. Questions, Answers, and Comments “People put up with networks only because they are a necessary evil” Words of Wisdom from Bill Lennon, LLNL:

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