NREN 3.0

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STEPHEN WOLFF, Internet2, on national research education networks

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NREN 3.0

  1. 1. NREN 3.0STEPHEN WOLFFInternet2JUNE 2013
  2. 2. •  Mobile Internet•  Automation of knowledge work•  Internet of things•  Cloud technology•  Advanced robotics•  Autonomous/near-autonomousvehicles•  Next-generation genomics•  Energy storage•  3-D printing•  Advanced materials•  Advanced oil/gas exploration,recovery•  Renewable energy[ 2 ]Twelve disruptive technologiesJune 11, 2013 © 2013 Internet2“Disruptive Technologies: Advances that will transform life, business, and the global economy”McKinsey Global Institute, 2013These technologies are forecast to account for $33 trillion of the global economy in 2025
  3. 3. [ 3 ]Big Data is the primary driverJune 11, 2013 © 2013 Internet2Familiar numbers:•  Major genome sequencingcenters @ 2 PB/year•  LSST @ 10 PB/year•  LHC @ 30 PB/year•  SKA @ 1 EB/day•  …
  4. 4. •  Continued rise of “team” science“To a very considerable extent statistics and applied mathematics and parts ofpure mathematics have become ‘group’ science requiring bodies of graduatestudents, postdocs and computing resources…”http://www.nsf.gov/attachments/124926/public/DMS_Name_Change_Committee_Report_Final_4-1-12.pdf•  One Culture. Computationally Intensive Research in the Humanities andSocial Sciences, Christa Williford & Charles Henry, CLIR, June 2012•  Internet2/Microsoft workshop on CI for social science February 2013•  IEEE Workshop on Big Humanities October 2013[ 4 ]Then there’s the long tailJune 11, 2013 © 2013 Internet2
  5. 5. Globalization of scientific research, e.g.:•  LHC involved scientists from 36 countries•  Annual funding for India-US collaborative research exceeds$2B, and there are more than 360 projects funded at$250,000 or more•  Annual funding for China-US collaborative research exceeds$1B, and there are more than 450 projects funded at$100,000 or more[ 5 ]…and ‘teams’ are not all localJune 11, 2013 © 2013 Internet2
  6. 6. Globalization and democratization of higher education –•  Remote campuses•  Classical distance education•  MOOCs[ 6 ]Nor is higher education…June 11, 2013 © 2013 Internet2
  7. 7. [ 7 ]US NREN speed vs. Moore’s LawJune 11, 2013 © 2013 Internet21985 1990 1995 2000 2005 2010YEAR10 kb/s1001 mb/s101001 Gb/s10100 Gb/s
  8. 8. [ 8 ]OAM multiplexingJune 11, 2013 © 2013 Internet2
  9. 9. [ 9 ]OAM multiplexingJune 11, 2013 © 2013 Internet2•  Willner et al USC•  Nearly 100 b/s/HzBUT•  You can’t beatShannon
  10. 10. Moving “Big Data” has led to fundamental advances in theunderstanding and design of networks•  Van Jacobson and Berkeley UNIX source (1988)•  Matt Mathis and Web100 (2003)•  Science DMZ (ESnet, 2009)[ 10 ]Big DataJune 11, 2013 © 2013 Internet2
  11. 11. Using “Big Data” has led to fundamental advances inscience and in analytics•  “Traditional” science, with Big Data (e.g., LHC)•  The Fourth Paradigm – learning algorithms, coping withvelocity, unstructured data, visualization,…[ 11 ]Big DataJune 11, 2013 © 2013 Internet2
  12. 12. •  Globalization ⇒ No NREN is an island•  Team science ⇒ (possibly virtual) team networks forvirtual communities•  Big Data ⇒ More than just bigger pipes[ 12 ]Implications/consequences
  13. 13. •  Globalization ⇒ It’s time to engineer global R&Econnectivity: from NRENs to a GREN•  Team science ⇒ A one-size-fits-all IP network is notenough. SDN (e.g., OpenFlow, OSCARS) will help usersand applications configure the network•  Big Data ⇒ Re-architecting (Science DMZ), tuning(Web10G), measuring (perfSONAR)[ 13 ]Further implications
  14. 14. •  Data = “content”•  Future NREN node?•  CDN/NDN–  via SDN?[ 14 ]…and a speculationSource: D. Comer
  15. 15. •  Growing number of instances where the data are toonumerous to move•  Instead, move the computation to the data•  Computation in place–  AWS, Microsoft Azure, cloud computing generally…•  Map-reduce and Hadoop–  Widely applicable and successful programming model–  Not well adapted to typical HPC architectures[ 15 ]The Black Swan
  16. 16. •  All the data are not – and cannot – be in one place–  10 EB of spinning disk ≈ 2.4 Gwattsnot counting backups or redundancy measures"•  “Computation in place” => GREN as backplane[ 16 ]Distributed data
  17. 17. •  Computers, datastores, and networks are all programmable•  Computational models / multicomputer architectures, networkarchitectures, and storage architectures are convergingdisciplinestherefore•  NREN engineers and operators must acquire added skills.•  The need is for support staff who are versed in computational_______, and able to program everything (see above)[ 17 ]Convergence
  18. 18. •  “Big data” and the growth of team science are bringing in to ourcommunity researchers with little background in computingbeyond their laptops.•  We are faced with a group of scientists who are “…analyzing datathey did not collect, using software they did not write, oncomputers they do not own.” – Myron Livny•  Not only are Renaissance thinkers needed for support staff, wemust begin to hold scientific software to the same standards aspublications. cf. Joppa et al, “Troubling Trends in ScientificSoftware Use”, Science, v 340, pp 814-815, 2013/05/17[ 18 ]BootnoteBootnote
  19. 19. NREN 3.0STEPHEN WOLFF[ 19 ]swolff@internet2.eduJune 11, 2013 © 2013 Internet2Thank  you!  

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