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Technology for Distributed Collaboration

Technology for Distributed Collaboration. Ian Foster Computation Institute Argonne National Laboratory University of Chicago. www.ci.uchicago.edu. www.ci.anl.gov. In the Next 50 Years, We Must …. Increase energy production by 5, while reducing GHG emissions by 2 or more

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Technology for Distributed Collaboration

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  1. Technology forDistributed Collaboration Ian Foster Computation InstituteArgonne National LaboratoryUniversity of Chicago

  2. www.ci.uchicago.edu www.ci.anl.gov

  3. In the Next 50 Years, We Must … • Increase energy production by 5, while reducing GHG emissions by 2 or more • Mitigate and adapt to climate change • Address increasingly drug resistant diseases • Provide meaningful livelihoods for 9B people  Innovation

  4. We Must Get Smarter … Maxwell Smart (NBC, 1960s; Warner 2008)

  5. The Three Dimensions of Smart Biology Technology Culture

  6. Problem Solvingas “Thinking Aloud” • “What if I try A?” • “I wonder how I do B?” • “What do others know about C?” • “Hey, I’ve just learned how to do D!”  How do I reduce cycle time?

  7. Thinking Aloud:Reducing Cycle Time • “What if I try A?”  Design, modeling, fabrication tools • “I wonder how I do B?”  Wikis, design databases, conversation • “What do others know about C?”  Databases, search tools, conversation • “Hey, I’ve just learned how to do D!”  Publication, conversation, education (Distributed) collaboration is a crosscutting theme

  8. Technologies forDistributed Collaboration • Data publication • FTP, Gopher, … • Web • Blogs • Semantic Web • Federation • Collaborative bookmarking • Grid computing • Service-oriented architecture • Conversation • Post • Fedex • Telephone • Email, IRC, … • Instant messaging • Videoconference • Immersive • MUDs • Access Grid • Second Life

  9. 600 Daily 7-Day Average 500 400 GB/day 300 200 100 11/1/04 0 11/1/05 12/1/04 1/1/05 2/1/05 3/1/05 5/1/05 7/1/05 8/1/05 9/1/05 1/1/06 3/1/06 4/1/06 5/1/06 6/1/06 7/1/06 8/1/06 9/1/06 10/1/05 12/1/05 6/1/05 2/1/06 10/1/06 4/1/05 • Provides access to all IPCC data • >150 TB data downloaded • >300 scientific papers written 600 GB/day

  10. Integrating Data and Computing, on Demand Public PUMA Knowledge Base Information about proteins analyzed against ~2 million gene sequences Back OfficeAnalysis on Grid Millions of BLAST, BLOCKS, etc., onOSG and TeraGrid Natalia Maltsev et al.,http://compbio.mcs.anl.gov/puma2

  11. Social Informatics Data Grid Bennett Berthenthal et al., www.sidgrid.org

  12. NIH’sCancer Biomedical Informatics Grid caBIG: sharing of infrastructure, applications, and data.

  13. Medical Education over Access Grid Credit: Jonathan Silverstein, U.Chicago

  14. Access Grid and SARS

  15. Global Communities

  16. PRAGMA • New communities:

  17. Community WebsiteSoftware Downloads, User-contributed Content, Hardware Reference, & More

  18. Globus Downloads Last 24 Hours Last month

  19. Lessons Learned • The power of diversity & scale • Open Science Grid: 80 sites, 30K CPUs • World Community Grid: 700,000 CPUs • Access Grid: several thousand nodes • Wikipedia, Flickr, CiteULike, Connotea, … • The challenges of heterogeneity • Bandwidth, hardware, interests, trust, understanding, meaning, timezone, … • The challenges of scale • Participants, data, computing, ambition • Everything is still far too complicated!

  20. Access Grid:The Power of Context

  21. “Thinking Aloud” (for Science or Invention): 10 Year From Now • On-demand access to powerful data, design, analysis, & fabrication resources • Service-oriented science & engineering • Deep analysis of vast quantities of data • Commoditization of design & analysis • Communities of 2, 20, 200, 2K, 2M can self-identify easily within a sea of billions • To share information, converse, discover • We understand innovation & collaboration far better than today

  22. Some Key Challenges • Enable smooth scaling in many dimensions • Number of participants (K-, M-, G-persons?) • Internet capabilities (0 to Tbit/sec) • Physical resources • Amount of data (megabytes to exabytes) • Complexity of questions asked & answered • Degree of trust, shared language, etc. • Integration with the physical world • Active sensors • Automated experimental protocols • Integrate manufacturing and problem solving

  23. Current Activities • Access Grid 3.0 • Conversation, context, scale, ease of use • Dozens of sites • Collaborative tagging for scientific data • Collaborative creation of data exegesis • Resource federation in virtual organizations • Grid protocols and software • Major deployments in development economics

  24. We Can Contribute to aDemocratization of Science • Personalized manufacturing (FabLab) • Personalized reporting (blogosphere) • Personalized innovation (“Global Knowledge Environment”?) “So much ingenuity my generation has, and no place to put it” — Charlie Leduff

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