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Cyberinfrastructure for Data Intensive Science (DIS). Follow-on panel to DIS session at Internet2/ESCC Joint Techs Conference Baton Rouge – January 24, 2012 . Joint Techs Winter 2012 Focus. Data intensive science focus session Input from many groups in the community

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cyberinfrastructure for data intensive science dis

Cyberinfrastructure for Data Intensive Science (DIS)

Follow-on panel to DIS session at

Internet2/ESCC Joint Techs Conference

Baton Rouge – January 24, 2012

joint techs winter 2012 focus
Joint Techs Winter 2012 Focus
  • Data intensive science focus session
    • Input from many groups in the community
      • Multiple science disciplines
      • Multiple infrastructure areas (networks, supercomputers, laboratory environments, mission agencies)
    • Success stories illustrated effective DIS support
  • The intent was to integrate the needs, context, and commonalities in a white paper
dis focus area presenters
DIS Focus Area Presenters
  • Bill St. Arnaud, Green IT
  • Matthew Trunnell, Broad Institute
  • Don Middleton, NCAR
  • Rich Carlson, DOE Office of Science
  • Kevin Thompson, NSF OCI
  • Mike Ackerman, NIH NLM
  • Gary Jung, LBNL
  • Gwen Jacobs, Montana State/Hawai’i
  • Ruth Marinshaw, UNC-Chapel Hill
  • Eli Dart, ESnet
  • Brent Draney, NERSC
  • Ron Hutchins, Georgia Tech
  • Joe Breen, Utah
  • Tad Reynales, Calit2-UCSD
  • Jim Bottum, Clemson

DIS Steering Committee: Scott Brim, Eric Boyd, Steve Corbató, Eli Dart,

Susan Evett, Kate Mace, Jim Pepin, Dan Schmiedt, Steve Wolff

joint techs 2012 what we heard
Joint Techs 2012 – What We Heard
  • Need for effective cyberinfrastructure voiced by multiple communities and disciplines
    • Genomics
    • Climate
    • Supercomputer centers
  • Success stories outlined the path forward
    • Science DMZ model
    • Effective communication between cyberinfrastructure providers, science disciplines, funding agencies
rapidly evolving context
Rapidly Evolving Context
  • Things are moving quickly now
    • NSF CC-NIE call focused on improving campus networks
    • Federal Big Data initiative
  • This stuff is for real – it’s not just talk
    • Infrastructure funding
    • Grant funding
  • The direction is not in doubt – the only thing to decide is the actions to take
    • Institutions that are aggressive in this space are likely to acquire first-mover advantage
    • The wide area infrastructure is available now
  • The need for a white paper has passed
solutions required for research institutions
Solutions Required for Research Institutions
  • Means by which campuses can connect to science services outside their borders
    • Collaboration
    • Computation
    • Data sources and services
  • Support data-intensive collaboration
    • Foster environment for grants, projects
    • Attract new faculty, new programs
  • Refresh science infrastructure
science infrastructure refresh
Science Infrastructure Refresh
  • NSF call  reinvestment in foundations of data intensive science
  • Architecture that has been shown to work: Science DMZ
  • In addition to technology, people and processes must be included in the refresh
    • Science programs, infrastructure providers and security officers must all be on board
    • Communication and a common vision are very important
    • Staff need the skills to manage high-performance science flows and the infrastructure to support them
the science dmz refresher
The Science DMZ – Refresher
  • The Science DMZ is two things
    • An element of network architecture
    • A model for supporting data-intensive science at a research institution
  • Architecture
    • Portion of the network, at or near the site perimeter
    • Devoted exclusively for science support
    • Built with capable hardware
    • Dedicated resources for data transfer, network measurement
    • Appropriate security applied, application set restricted so that security controls, risk, and science mission are all aligned
    • http://fasterdata.es.net/science-dmz/science-dmz-architecture/
the science dmz model
The Science DMZ Model
  • In general, the Science DMZ model is a framework for cyberinfrastructure
    • Explicitly accommodates science mission
    • Builds in flexibility to adopt tools and technologies for science support
    • Establishes appropriate security infrastructure to both enable and protect science
  • Must balance security, usability, and performance
  • The science mission is given what it needs to succeed
integration of campus with wider infrastructure
Integration of Campus with wider infrastructure
  • Science DMZ enables a campus to connect local scientists and resources in a frictionless manner to other sites and services
    • Science networks
    • Advanced services
      • Virtual circuit services, network overlays
      • Internet2 Innovation Platform
      • http://fasterdata.es.net/science-dmz/advanced-services/
    • Science DMZ resources at other campuses
      • This is a critical point – remember Metcalfe’s Law
      • Value of a Science DMZ increases as others deploy them
  • The data-intensive era is upon us – the infrastructure must evolve to keep pace
conclusions
Conclusions
  • The time to act is now
  • Lots of movement in this space – dynamic, evolving
  • Create a coalition of the willing
    • Set of Universities and National Labs of sufficient critical mass to create transformative environment to support DIS
    • Must create environment to encourage innovation while encouraging coherence to support scientific disciplines scattered across the globe
  • Infrastructure pieces are well-understood
    • Hence the NSF call for campus activities
    • Get these deployed now
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