CENIC:CENIC: DrivingDriving InnovationInnovation throughthrough NetworkingNetworking

JimJim DolgonasDolgonas PresidentPresident andand ChiefChief OperatingOperating OfficerOfficer

CENICCENIC

AprilApril 4,4, 20062006 CENICCENIC MissionMission andand GoalsGoals zz Mission:Mission: “…to“…to develop,develop, deploydeploy anandd operateoperate leadingleading edgeedge network-basednetwork-based servicesservices andand toto facilitatefacilitate andand coordinatecoordinate theirtheir useuse forfor thethe researchresearch andand educationeducation communitycommunity toto advanceadvance learninglearning andand innovation”innovation” zz Goals:Goals: „„ ProvideProvide competitivecompetitive advantageadvantage inin globalglobal marketplacemarketplace toto educationeducation andand researchresearch communitiescommunities

„„ ProvideProvide opportunitiesopportunities forfor innovationinnovation inin teaching,teaching, learninglearning andand researchresearch throughthrough useuse ofof thethe network.network.

2 CENIC’s Place in National R&E Networking

zz 1969-90--1969-90--ARPANETARPANET (Mil(Milnetnet splitsplit offoff iinn ‘83)‘83) zz 1981-96--1981-96--BITNET/CRENBITNET/CREN zz 1981-91ish--1981-91ish--CSNETCSNET (CSnet(CSnet mergedmerged withwith BITNBITNETET intointo CREN)CREN) zz 1986-95ish—1986-95ish—NSFNeNSFNett zz MidMid 90’s90’s-Co-Commmermerccialial InternetInternet zz 1995-2001ish--1995-2001ish--vBNSvBNS zz 1996-97---1996-97---InInternternet2/Abilenet2/Abilenee zz 1997-1997-CENIC/CalRENCENIC/CalREN 22 (California)(California)-Phase-Phase II ooff CENICCENIC evoevolulutiontion zz 2000-20022000-2002-CENIC/-CENIC/CCalRalREENN addsadds K-12-K-12-PhasePhase IIII ofof evolutionevolution zz 2003-042003-04-C-CENICENIC deploydeployss statewidestatewide fibefiberr backbonebackbone andand beginsbegins toto ssupportupport CCCCC’sC’s andand CSUCSU’’s-Phases-Phase IIIIII ofof CENICCENIC evolutionevolution zz 20032003-NLR-NLR (www.nlr.net)(www.nlr.net) createcreatedd toto deploydeploy nationalnational fifiberber backbonebackbone forfor researchresearch zz 2004-05-2004-05-CCEENICNIC expands-Phaseexpands-Phase IVIV ofof evolutionevolution zz CurrentCurrent toto futurefuture

3 CalRENCalREN zz FiberFiber networknetwork supportssupports needsneeds ofof highhigh endend research-itresearch-it isis aa criticalcritical componentcomponent ofof UniversityUniversity researchresearch zz HighHigh speedspeed networknetwork facilitatesfacilitates collaboration-collaboration- facultyfaculty andand researchersresearchers dodo notnot workwork alone.alone. TheThe networknetwork enablesenables thethe barriersbarriers ofof geographygeography toto bebe removedremoved zz ProvidesProvides forfor longlong termterm costcost effectiveeffective networknetwork servicesservices

4 A Tiered Network . . . The Pyramid

5 NationalNational andand RegionalRegional ParticipationParticipation

zz ConnectConnect toto commodity/commercialcommodity/commercial internet-multipleinternet-multiple carriers/connectionscarriers/connections zz ConnectConnect toto InternetInternet 2/Abilene2/Abilene zz ConnectConnect toto NationalNational LambdaRailLambdaRail (NLR)(NLR) zz ConnectConnect toto westernwestern U.S.U.S. state/regionalstate/regional networksnetworks -- ee.g.,.g., Nevada,Nevada, UtahUtah

6 LayerLayer 33 NetworksNetworks inin thethe USUS zz ThereThere areare severalseveral LayerLayer 33 networksnetworks inin thethe USUS includingincluding twotwo nationalnational footprintfootprint HigherHigher EducationEducation Networks:Networks: „„ AbileneAbilene (Internet2)(Internet2) „„ NLRNLR layerlayer 33 PacketPacket NetworkNetwork zz ManyMany AgencyAgency specificspecific networksnetworks likelike ESNetESNet zz ManyMany projectproject orientedoriented networksnetworks likelike TeragridTeragrid zz AndAnd multiplemultiple regionalregional networksnetworks likelike CalRENCalREN

John Silvester, USC

7 CENIC-AsCENIC-As FoundingFounding MemberMember ofof NLRNLR

zz ToTo addressaddress allall 33 layerslayers ofof pyramidpyramid zz ToTo achieveachieve advantagesadvantages ofof fiber-basedfiber-based networknetwork insteadinstead ofof managedmanaged serviceservice

8 NationalNational LambdaRailLambdaRail MissionMission zz ToTo advanceadvance thethe research,research, clinicalclinical andand educationaleducational goalsgoals ofof membersmembers andand otherother institutionsinstitutions byby establishingestablishing andand maintainingmaintaining aa nationwidenationwide advancedadvanced networknetwork infrastructure.infrastructure.

9 10 ChangesChanges inin R&ER&E ImpactingImpacting NetworkingNetworking NeedsNeeds zz GrowingGrowing urgencyurgency forfor newnew networknetwork technologiestechnologies zz IncreasedIncreased collaborationcollaboration worldwideworldwide on“Big”on“Big” ScienceScience projectsprojects zz ExponentialExponential growthgrowth inin sizesize ofof datadata setssets beingbeing accessedaccessed zz NeedNeed forfor multiplemultiple dedicated/privatededicated/private researchresearch networksnetworks zz iGRIDiGRID demonstrateddemonstrated manymany examplesexamples ofof high-endhigh-end andand lightpathlightpath networknetwork applicationsapplications

11 FromFrom “Supercomputer-Centric”“Supercomputer-Centric” toto “Supernetwork-Centric”“Supernetwork-Centric” CyberinfrastructureCyberinfrastructure Terabit/s 1.E+06

32x10Gb “Lambdas” Computing Speed(GFLOPS)

1.E+05 Bandwidth of NYSERNet Research Network Backbones 1.E+04 bps) M ( Gigabit/s h t 1.E+03 d i 60 TFLOP Altix ndw 1.E+02 a

B 1 GFLOP Cray2 Optical WAN Research Bandwidth 1.E+01 Has Grown Much Faster Than Supercomputer Speed! 1.E+00 Megabit/s 1985 T1 1990 1995 2000 2005

Network Data Source: Timothy Lance, President, NYSERNet 12 NASANASA BroadensBroadens SupercomputingSupercomputing

Mark Foster, NASA 13 NASANASA SimulationsSimulations

Mark Foster, NASA 14 CAMERACAMERA BuildsBuilds onon CyberinfrastructureCyberinfrastructure Grid,Grid, Workflow,Workflow, andand PortalPortal ProjectsProjects inin aa ServiceService OrientedOriented ArchitectureArchitecture

National Biomedical Computation Resource an NIH supported resource center Cyberinfrastructure: Raw Resources, Middleware & Execution Environment Virtual Organizations Workflow Management Web Services

NBCR Rocks Clusters

Vision

Telescience Portal

15 Larry Smarr, Calit2 KEPLER TheThe OptIPuterOptIPuter –– CreatingCreating HighHigh ResolutionResolution PortalsPortals OverOver DedicatedDedicated OpticalOptical ChannelsChannels toto GlobalGlobal ScienceScience DataData

Source: Mark Ellisman, David Lee, Jason Green: Purkinje Cells Leigh Red: Glial Cells Light Blue: Nuclear DNA Calit2 (UCSD, UCI) and UIC Lead Campuses—Larry Smarr PI 16 Larry Smarr, Calit2 Partners: SDSC, USC, SDSU, NW, TA&M, UvA, SARA, KISTI, AIST iGrid2005iGrid2005 DataData FlowsFlows MultipliedMultiplied NormalNormal FlowsFlows byby FiveFive Fold!Fold!

Data Flows Through the Seattle PacificWave International Switch

17 Larry Smarr, Calit2 iGridiGrid LLambdaambda HighHigh PerformancePerformance ComputingComputing Services:Services: DistributingDistributing AMRAMR CosmologyCosmology SimulationsSimulations zz UsUseses ENZOENZO ComputationalComputational CosCosmmologyology CodeCode „„ Grid-BasedGrid-Based AdaptiveAdaptive MeshMesh RefinementRefinement SimulationSimulation CodeCode „„ DevelopedDeveloped byby MikeMike Norman,Norman, UCSDUCSD zz CanCan OneOne DisDisttributeribute thethe Computing?Computing? „„ iGrid2005iGrid2005 toto ChicagoChicago toto AmsterdamAmsterdam zz DistributingDistributing CodeCode UsUsinging LayerLayer 33 RoutersRouters FailsFails zz InsteadInstead UsingUsing LayerLayer 2,2, EssentiallyEssentially SameSame PerformancePerformance asas RunningRunning onon SingleSingle SupercomputerSupercomputer „„ UsUsinging DyDynamicnamic LightpathLightpath ProvisioningProvisioning

Source: Joe Mambretti, Northwestern U 18 iGridiGrid LambdaLambda ControlControl Services:Services: TransformTransform BatchBatch toto Real-TimeReal-Time GGloballobal e-Verye-Very LongLong BaselineBaseline InterferometryInterferometry

zz Goal:Goal: Real-TimeReal-Time VLBIVLBI RadioRadio TelescopeTelescope DataData CorrelationCorrelation zz AchievedAchieved 512Mb512Mb TransfersTransfers fromfrom USAUSA andand SwedenSweden toto MITMIT zz ResultsResults StreamedStreamed toto iGrid2005iGrid2005 inin SanSan DiegoDiego

Optical Connections Dynamically Managed Using the DRAGON Control Plane and Internet2 HOPI Network Source: Jerry Sobieski, DRAGON 19 iGridiGrid SScientificcientific InstrumentInstrument Services:Services: EnableEnable RemoteRemote InteractiveInteractive HHDD ImagingImaging ofof DeepDeep SeaSea VentVent

Canadian-U.S. Collaboration

Source John Delaney & Deborah Kelley, UWash 20 High Definition Video - 2.5 km Below the Ocean Surface

21 TeamworkTeamwork andand ScienceScience Technology-enabledTechnology-enabled NeurosurgeryNeurosurgery

Radiologists and neurosurgeons at Brigham and Women’s Hospital, Harvard Medical School exploring transmission of 30/40 MB brain images (generated during surgery) to SDSC for analysis and alignment • PROBLEM: Neuro-surgeons Transmission repeated seek to remove as much tumor every hour during 6-8 tissue as possible while hour surgery. minimizing removal of healthy Transmission and brain tissue output must take on the order of minutes • Brain deforms during surgery Finite element simulation • Surgeons must align preoperative on biomechanical model brain image with intra-operative for volumetric images to provide surgeons the deformation performed best opportunity for intra-surgical at SDSC; output results navigation are sent to BWH where updated images are 22 Fran Berman, SDSC shown to surgeons TrackingTracking thethe UniverseUniverse

Hubble Telescope “The Universe is now being explored systematically, in a panchromatic way, over a range of spatial and temporal scales that lead to a more complete, and less biased understanding of its Palomar constituents, their evolution, Telescope their origins, and the physical processes governing them.”

Towards a National Virtual Sloan Observatory Telescope

23 Fran Berman, SDSC TheThe VirtualVirtual ObservatoryObservatory

zz Premise:Premise: mostmost observatoryobservatory datadata isis (or(or couldcould be)be) onlineonline zz So,So, thethe InternetInternet isis thethe world’sworld’s bestbest telescopetelescope::

„„ ItIt hashas datadata onon everyevery partpart ofof thethe skysky

„„ InIn everyevery measuredmeasured spectralspectral band:band: optical,optical, x-ray,x-ray, radio..radio..

„„ It’sIt’s asas deepdeep asas thethe bestbest instrumentsinstruments

„„ ItIt isis upup whenwhen youyou areare upup

„„ TheThe “seeing”“seeing” isis alwaysalways greatgreat

„„ It’sIt’s aa smartsmart telescope:telescope: linkslinks objectsobjects andand datadata toto literatureliterature onon themthem zz SoftwareSoftware hashas becamebecame aa majormajor expenseexpense

„„ Share,Share, standardize,standardize, reuse..reuse..

Alex Szalay, NVO 24 DownloadingDownloading thethe NightNight SkySky

The National Virtual Hubble Observatory (NVO) Telescope z Astronomy community came together to set standards for services and data „ Interoperable, multi-terabyte online databases „ Technology-enabled, science-driven. Palomar z NVO combines over 100 TB of data from 50 Telescope ground and space-based telescopes and instruments to create a comprehensive picture of the heavens

„ Sloan Digital Sky Survey, Hubble Space Sloan Telescope, Two Micron All Sky Survey, Telescope National Radio Astronomy Observatory, etc. 25 Fran Berman, SDSC UsingUsing TechnologyTechnology toto EvolveEvolve AstronomyAstronomy

zz LookLookinging forfor „„ NeedlesNeedles inin haystackshaystacks –– tthehe HiggsHiggs particleparticle „„ HaystacksHaystacks ---- DarkDark matter,matter, DarkDark energyenergy

zz StatisticalStatistical analysanalysisis oftenoften dealsdeals withwith „„ CreatingCreating uniformuniform samplessamples „„ DataData filteringfiltering „„ AssemblingAssembling relevantrelevant subsetssubsets „„ CensoringCensoring badbad datadata „„ “Likelihood”“Likelihood” calculationscalculations „„ HyHypothespothesisis testing,testing, etc.etc.

zz TraditionallyTraditionally thesethese areare performedperformed onon files,files, mostmost ofof thesethese taskstasks areare muchmuch betterbetter donedone insinsiidede aa databasedatabase

Alex Szalay, NVO 26 NVONVO atat SDSCSDSC

SDSS – The USNO-B all-sky catalogue was New Mexico obtained from various sky surveys during the last 50 years. USNO provides all-sky USNO-B coverage and 85% accuracy for distinguishing stars from non-stellar objects

The Sloan Digital Sky Survey 2MASS – Chile provides a 3D map of a million galaxies and quasars covering more than a quarter of the sky.

2MASS gathers data from a northern facility 2MASS -- in Arizona and a Arizona southern facility in Chile

The 2 Micron All Sky Survey (2MASS) provides direct answers to questions on the large-scale structure of the Milky Way and the Local Universe MACHO

Photometric data from Mt. The Palomar Oschin SDSC’s NVO Stromlo observatory in telescope provides a SDSC collection is nearly Australia on several million catalogue of the entire 100 TB and has stars gathered since 1992 northern sky in blue, red grown over 5-fold and near-infrared to explore constitution of DPOSS – CA since 2002 dark matter in the halo of colors. 27 the Milky Way Fran Berman, SDSC MakingMaking DiscoveriesDiscoveries UsingUsing thethe NVONVO

Scientists at Johns Hopkins, Caltech and other institutions confirmed the discovery of a new brown dwarf. Search time on 5,000,000 files went from months to minutes using NVO database tools and technologies.

Brown dwarfs are often called the “missing link” in the study of star formations. They are considered small, cool “failed stars”.

28 Fran Berman, SDSC CurrentlyCurrently DevelopingDeveloping OptIPuterOptIPuter SoftwareSoftware toto CoherentlyCoherently DriveDrive 100100 MegaPixelMegaPixel DisplaysDisplays zz 55-Panel55-Panel DisplayDisplay *100*100 MegapixelMegapixel zz DrivenDriven byby 3030 Dual-OpteronsDual-Opterons (64-bit)(64-bit) zz 6060 TBTB DiskDisk zz 3030 10GE10GE interfacesinterfaces *1/3*1/3 TeraTera bit/secbit/sec zz LinkedLinked toto OptIPuterOptIPuter

Source: Jason Leigh, Tom DeFanti, EVL@UIC, OptIPuter Co-PIs 29 TeraShakeTeraShake SimulationsSimulations

Simulation of Southern of 7.7 earthquake on lower San Andreas Fault

„ Physics-based dynamic source model – simulation of mesh of 1.8 billion cubes with spatial resolution of 200 m

„ Builds on 10 years of data and models from the Southern California Earthquake Center

„ Simulated first 3 minutes of a magnitude 7.7 earthquake, 22,728 time steps of 0.011 second each

„ Simulation generates 45+ TB data

30 Fran Berman, SDSC Shaking up quake research. NEESgrid

One of the beauties of the NEESgrid will be its power as a teleobservation and teleoperation tool. In other words, researchers will be able to control experimental tools – such as a seismograph, a camera, or even a robot – at remote sites from their desktop workstation.

CalREN-HPR High Performance Research 31 HDTVHDTV ConferencingConferencing SpanningSpanning TwoTwo OceansOceans EnabledEnabled byby PacificPacific WaveWave

32 John Dundas, Caltech CalREN’sCalREN’s UseUse forfor InnovationsInnovations inin TeachingTeaching andand LearningLearning

33 CENIC helps UC prepare high school students for college.

U.C. College Prep Online

It is not possible to provide a teacher of advanced mathematics within every high school in California. There are not enough teachers in enough places to meet the need. UCCP delivers Advanced Placement (AP), honors, and pre- AP courses throughout the state.

CalREN-HPR High Performance Research 34 CENIC takes the distance out of learning. Virtual Education in Orange County

Instead of reading about space history in textbooks, students from Brea Junior High School toured the Smithsonian National Air and Space Museum guided by LeRoy London, director of educational outreach.

Educators in Orange County enjoy direct access to nationally renowned researchers and practitioners and to their colleagues both in the county and beyond.

CalREN-DC Videoconferencing Services 35 CENIC enables interactive learning.

The Biology Workbench

The Biology Workbench supports remote identification and manipulation of protein sequences. It has been used by university faculty nationwide in biology courses.

CalREN-DC 36 CENIC does digital media.

ACME Animation

Twice weekly ACME links classrooms high schools, occupational centers, community colleges and California State Universities to studio professionals at Disney, DreamWorks, and Warner Brothers. The college matriculation rate of ACME high school participants has reached 91%

CalREN-DC 37 CENIC enables interactive learning.

CCC Confer CCC Confer leverages CalREN’s high speed to offer students and faculty the opportunity to combine phone calls with online chat and simultaneous application sharing.

CalREN-DC 38 FutureFuture DirectionsDirections zz NetworksNetworks (DC(DC andand HPRHPR netsnets needneed refreshing/upgrading)refreshing/upgrading) zz Communities/educationalCommunities/educational institutionsinstitutions acquiringacquiring fiberfiber zz NeedNeed forfor multiplemultiple dedicated/privatededicated/private researchresearch networksnetworks (iGRID(iGRID conferenceconference demonstrateddemonstrated yesterdayyesterday includesincludes manymany examples)examples) zz UsesUses ofof networknetwork forfor teachingteaching andand learninglearning zz NLR/InternetNLR/Internet 22 MergerMerger

39 PotentialPotential ListList ofof FutureFuture CENICCENIC NetNet ServicesServices zz EndEnd toto endend opticaloptical lambda/wavelambda/wave servicesservices

99 EndsEnds areare labs/desktopslabs/desktops atat campusescampuses

99 CrossCross nationalnational andand internationalinternational networknetwork boundariesboundaries

99 AbilityAbility toto obtainobtain thesethese forfor shortshort periodsperiods ofof timestimes onon shortshort noticenotice (user(user switched??)switched??) zz End-to-endEnd-to-end switchedswitched ethernetethernet servicesservices (same(same asas above)above) zz New-experimentalNew-experimental routedrouted servicesservices (layer(layer 3,3, toto complementcomplement experimentalexperimental routedrouted servicesservices ofof NLR)NLR) 40 Questions?Questions? http://www.cenic.orghttp://www.cenic.org

JimJim DolgonasDolgonas [email protected]@cenic.org

(714)(714) 220-3464220-3464

41