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From Computational Science to Science Discovery

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From Computational Science to Science Discovery FromComputationalSciencetoScienceDiscovery:The NextComputingLandscape GiladShainer,BrianSparks,ScotSchultz,EricLantz,WilliamLiu,TongLiu,GoldiMisra HPCAdvisoryCouncil {Gilad,Brian,Scot,Eric,William,Tong,[email protected]} Computationalscienceisthefieldofstudyconcernedwithconstructingmathematicalmodelsand numericaltechniquesthatrepresentscientific,socialscientificorengineeringproblemsandemploying thesemodelsoncomputers,orclustersofcomputerstoanalyze,exploreorsolvethesemodels. Numericalsimulationenablesthestudyofcomplexphenomenathatwouldbetooexpensiveor dangeroustostudybydirectexperimentation.Thequestforeverhigherlevelsofdetailandrealismin suchsimulationsrequiresenormouscomputationalcapacity,andhasprovidedtheimpetusfor breakthroughsincomputeralgorithmsandarchitectures.Duetotheseadvances,computational scientistsandengineerscannowsolvelargeͲscaleproblemsthatwereoncethoughtintractableby creatingtherelatedmodelsandsimulatethemviahighͲperformancecomputeclustersor supercomputers.Simulationisbeingusedasanintegralpartofthemanufacturing,designanddecisionͲ makingprocesses,andasafundamentaltoolforscientificresearch.ProblemswherehighͲperformance simulationplayapivotalroleincludeforexampleweatherandclimateprediction,nuclearandenergy research,simulationanddesignofvehiclesandaircrafts,electronicdesignautomation,astrophysics, quantummechanics,biology,computationalchemistryandmore. Computationalscienceiscommonlyconsideredthethirdmodeofscience,wherethepreviousmodesor paradigmswereexperimentation/observationandtheory.Inthepast,sciencewasperformedby observingevidenceofnaturalorsocialphenomena,recordingmeasurabledatarelatedtothe observations,andanalyzingthisinformationtoconstructtheoreticalexplanationsofhowthingswork. WiththeintroductionofhighͲperformancesupercomputers,themethodsofscientificresearchcould includemathematicalmodelsandsimulationofphenomenonthataretooexpensiveorbeyondour experiment'sreach.Inturn,wecanforecastweatherconditionssooner,explorealternativeenergy sources,buildsafervehiclesandpackageconsumedgoodsinamoreeconomicalway.Inorderto performthosenumericalsimulationeffectivelyandproductively,costͲeffectiveorcommoditybased supercomputersarchitectureswerecreatedhighͲperformanceclusteringofcomputers. HighͲperformancecomputing(HPC)clustersarescalableperformancecomputesolutionsbasedon industryͲstandardhardwareconnectedbyaprivatesystemhighͲspeednetwork.Themainbenefitsof clustersareaffordability,flexibility,availability,highͲperformanceandscalability.Aclusterusesthe aggregatedpowerofcomputeservernodestoformahighͲperformancesolutionforparallel applications.Whenmorecomputepowerisneeded,itcanbesimplyachievedbyaddingmoreserver nodestothecluster.TheLosAlamosNationalLab(US)Roadrunnercluster(figure1)wasthefirst systemtoprovidePetaflop(athousandtrillionCPUfloatingpointoperationsorinstructionspersecond) performanceforscientificsimulations(nationalnuclearweapons,astronomy,humangenomescience andclimatechange).RoadrunnerwasbuiltusingIBMCellCPUsandAMDOpteronCPUsboards,and MellanoxInfiniBandtoconnectbetweenthem.OakRidgeNationalLab(US)Spidersystemisoneof theworldslargestandfasteststorageclusterfilesystemthatincludesthousandsofconnections(based onInfiniBandinterconnect)andover10.7PetaBytestoragecapacitytoservethehighͲperformance systemsatthelab.TheNationalUniversityofDefenseTechnology(China)TianHesystem(figure2)is thefirstPetascalesysteminAsia.ThesystemisusingthousandsofIntelCPUandATIGPUs,all connectedviaMellanoxInfiniBandnetworking. Figure1LosAlamosNationalLabRoadrunnersystemstheworldsfirstPetaflopsystem Figure2NationalUniversityofDefenseTechnologyTianHesystem WiththecreationofbiggerandfasterhighͲperformancecomputingsystemsforscientificand engineeringsimulations,newgenerationsofsensorͲcomputerapplianceshavebeencreatedforspecific applications.Oneexampleisthe,theAustralianSquareKilometreArrayPathfinder(ASKAP),anarrayof radiotelescopesthatwillcompriseof36antennaseach12mindiameter,capableofhighdynamicrange imagingandusingwideͲfieldͲofͲviewphasedarrayfeeds.ASKAPwillbeatelescopethatcancapture radioimageswithunprecedentedsensitivityoverlargeareasofsky.WithalargeinstantaneousfieldͲofͲ viewASKAPwillbeabletosurveythewholeskyvastlyfasterthanispossiblewithexistingradio telescopes. Figure3IllustrationoftheAustralianSquareKilometreArrayPathfinder PetaflopSupercomputersCreateExaͲfloodofData Theeverincreasingdemandsforcomputationalpowerdeliveredbytheeverincreasingsupercomputer capabilityandcapacityproduceanoverwhelmingflowofdata.InoneweektheAustralianSquare KilometreArrayPathfinderwillgeneratemoreinFormationthaniscurrentlycontainedonthewhole WorldWideWeb,andinonemonthitwillgeneratemoreinformationthaniscontainedintheworld's academiclibraries.APetaflopsupercomputerequals150,000computationsforeveryhumanonthe planetpersecond,andasingledaysusageworldTOP500supercomputers(accordingtotheNovember 2009list)isequalto240billionpeoplearmedwithcalculatorsfornearly50years. Withtheincreasingrampofdatagenerationfromscientificandengineeringsimulationsand observationtargetedsupercomputers,futuretechnologydevelopmentshouldbefocusedoncreating scalablehighͲperformanceclustersofcomputersthatcanmanageandprocessallofthisdata.The futurepremiseofcomputeinfrastructuresshouldbeaimedintobuildingorprovidingtoolsandsystems forsciencediscovery,inwhichallofthecomputationalscienceliteratureanddatabasescanbe availableonlineandbesharedbyscientists,researchersandengineersaroundtheglobe.Distributed sciencecanbeseenasthefourthmodeorparadigmwheresciencebecomescentralizedthroughout centralizationofcomputingfacilities,andthosecomputingfacilitiesarethentargetedintomanaging, visualizingandanalyzingthedataflood.Computationalsciencedrivesthevastcreationofdatawhichis beyondourcapabilitiestoanalyzeandunderstand,andtheroleofsciencediscoverywillextendto createthetoolstoextractthefuturesciencediscoveriesoutofthedataflood. Furthermore,inmanyscientiFicfieldsofstudies,theinstrumentsareextremelyexpensive,andassuch, thedatamustbeshared.WiththisdataexplosionandashighͲperformancesystemsbecomea commodityinfrastructure,thepressuretosharescientificdataisincreasing.Thatresonateswellwith theemergingcomputingtrendknownasthecloudorcloudcomputing.Whileforthemomentcloud computingappearstobeacosteffectivealternativeforITspending,ortheshiftofenterpriseITcenters fromcapitalexpensetooperationalexpense,researchinstituteshavestartedexploringhowcloud computingcancreatethedesiredcomputecentralizationandanenvironmentforresearcherstoshare andcrunchthefloodofdata.OneexampleisthenewsystemattheNationalEnergyResearchScientific ComputingCenter(US),namedMagellan.WhileMagellansinitialtargetistoprovideatoolfor computationalscienceinacloudenvironment,itcanbeeasilymodifiedtobecomeacenterfordata processingaccessedbymanyresearchersandscientists. CentralizedDataCrunchingComputeEnvironmentThroughoutCloudComputing Theconceptofcomputinginacloudistypicallyreferredasahostedcomputationalenvironment (couldbelocalorremote)thatcanprovideelasticcomputeandstorageservicesforusersperdemand. Thereforethecurrentusagemodelofcloudenvironmentsisaimedforcomputationalscience.Future cloudscanbeservedasenvironmentsfordistributedsciencetoallowresearchersandengineersto sharetheirdatawiththeirpeersaroundtheglobeandallowexpensiveachievedresultstobeutilizedfor moreresearchprojectsandscientificdiscoveries. Toallowtheshifttothefourthmodeofsciencediscoverythosecloudenvironmentswillneednot onlytoprovidecapabilitytosharethedatacreatedbythecomputationalscienceandthevarious observationsresults,butalsotobeabletoprovidecostͲeffectivehighͲperformancecomputing capabilities,similartothatoftodaysleadingsupercomputers,inordertobeabletorapidlyand effectivelyanalyzethedataflood.Moreover,animportantcriteriaofcloudsneedtobefastprovisioning ofthecloudresources,bothcomputeandstorage,inordertoservicemanyusers,manydifferent analysisandbeabletosuspendtasksandbringthembacktolifeinafastmanner.Reliabilityisanother concern,andcloudsneedtobeabletobeselfhealingcloudswherefailingcomponentscanbe replacedbysparesoronͲdemandresourcestoguaranteeconstantaccessandresourceavailability. TheuseofGridsforscientificcomputinghasbecomesuccessfulinthelastfewyearsandmany internationalprojectsledtotheestablishmentofworldͲwideinfrastructuresavailableforcomputational science.TheOpenScienceGridprovidessupportfordataͲintensiveresearchfordifferentdisciplines suchasbiology,chemistry,particlephysics,andgeographicinformationsystems.EnablingGridfor ESciencE(EGEE)isaninitiativefundedbytheEuropeanCommissionthatconnectsmorethan91 institutionsinEurope,Asia,andUnitedStatesofAmerica,toconstructthelargestmultiͲscience computingGridinfrastructureoftheworld.TeraGRIDisanNSFfundedprojectthatprovidesscientists withalargecomputinginfrastructurebuiltontopofresourcesatnineresourceproviderpartnersites.It isusedby4000usersatover200universitiesthatadvanceresearchinmolecularbioscience,ocean science,earthscience,mathematics,neuroscience,designandmanufacturing,andotherdisciplines. WhileGridscanprovideagoodinfrastructureforsharedscienceanddataanalysis,severalissuesmake theGridsproblematictoleadthefourthmodeofsciencelimitedsoftwareflexibility,applications typicallyneedtobepreͲpackaged,nonelasticityandlackofvirtualization.Thosemissingitemscanbe deliveredthroughcloudcomputing. Cloudcomputingaddressesmanyoftheaforementionedproblemsbymeansofvirtualization technologies,whichprovidetheabilitytoscaleupanddownthecomputinginfrastructureaccordingto givenrequirements.ByusingCloudͲbasedtechnologiesscientistscanhaveeasyaccesstolarge distributedinfrastructuresandcompletelycustomizetheirexecutionenvironment.Furthermore, effectiveprovisioningcansupportmanymoreactivitiesandsuspendorbringtolifeactivitiesinan
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