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

Center for Computational Engineering llnl-cce 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

Lawrence Livermore National Laboratory Center for Computational Engineering llnl-cce Example NEES Experimental Site Geotechnical Centrifuge at UC Davis

Lawrence Livermore National Laboratory Center for Computational Engineering llnl-cce 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

Lawrence Livermore National Laboratory Center for Computational Engineering llnl-cce Typical NEES Cyberinfrastructure Internet Fabric and Operations NEESpop A Experimental Equipment Video I/O Audio I/O Site A: Experimental Data Producer Hub A NEESpop B Telepresence Equipment Active PI Data Cache Site B: Remote Lead Investigator Hub B Site C: Passive Collaborator Teleobservation Equipment Passive coPI Data Cache Hub C Experimental Component Campus Net Component NEESgrid Component Grid Data Repository Grid Ops Center

Lawrence Livermore National Laboratory Center for Computational Engineering llnl-cce 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

Lawrence Livermore National Laboratory Center for Computational Engineering llnl-cce 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

Lawrence Livermore National Laboratory Center for Computational Engineering llnl-cce 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

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