OracleSPARCM7forSAS®VerticalScalingfor
Secure,Rapid,AgileEnvironmentsSimplifyIT
TheOracleSPARCM7processorintroduceduniqueSoftwareinSiliconinnovationscombinedwithnewlevelsofextremememorybandwidth,computeperformanceandthroughput.FeaturessuchasSiliconSecuredMemoryandon-chipcryptoaccelerationenablethestrongestfoundationforplatformsthatdemandthehighestlevelofsecurity.ThecombinationofM7basedsystemswithSolaris11.3bringsnewlevelsofsecurity,performance,ITagilitytomeetthemostdemandingrequirementsofbusinesscriticalSASanalyticsandbusinessintelligenceapplications.SPARCM7systemsareanexcellentchoiceforrunningSASHighPerformanceAnalyticsApplications.Large-scaleSASenvironmentscanbedeployedineitherscale-outhorizontalfashionorscaleupinverticalfashion.Applicationdeploymentsarenotone-sizefitsall.Scaleoutdeploymentsareperfectlysuitedinsomeenvironmentsandscale-updeploymentsarebettersuitedinothers.Performancestudiesoftenconveyonedimensionalornarrowviewsofapplicationperformance.BelowisabriefsurveyofseveraldifferentfacetsofSASapplicationperformancetohighlightalandscapeofdifferentconsiderations.
• ComputeStrandPerformance• ScaleUp–Multi-Stream• ScaleUp–Multi-ThreadedStream• ScaleUp–Both(ManyMulti-ThreadedStreams)• CombinedSAS&OracleDatabase12c• RapidDeployment–MeanTimeToAnalytics
HardwareConfiguration:
• SPARCT7-1– 1x4.13GHzSPARCM7(32cores),256GBRAM– Storage:SingleZFSfilesystem-4FCALHBAconnectionsto3PARSAN– Solaris11.3
• SPARCM7-8(48coredomain,referredtoasM7-8DOM)– Domain:1.5x4.13GHzSPARCM7(48cores),512GBRAM– Storage:SingleZFSfilesystem–3xF160NVMEStorageDevices– Solaris11.3
ComputeStrandPerformanceUsingaconsistentsetofstandardSASprograms,comparativeperformanceisshown.ThetestsconsistoftypicalSAStestsutilizingDatastepandtypicalPROCssuchaslogistic,reg,glm,mixed;eachtestisruninserialfashionandthetotalruntimeiscomparedagainsthistoricaldata.Figure1showsthatSPARCM7performs~40%fasterthatthesametestsrunonSPARCT4ScaleUp-Multi-StreamFromasinglestreamtest,thenextquestionis:howdoesaworkloadbehaveasyouscaleupconcurrentjobstreams?Thetestutilizedisanactual,realworldworkloadusedinaglobaltradingapplication.Theworkloadspawnsparallelflowsorjobstreamsinascaleupmodeuntilthenumberofconcurrentflowsmatchesthenumberofcores.Eachflowhasthefollowingcharacteristics:
• Consistsofanumberofresourceintensive
Figure1:ComparativeSPARCM7performance
Figure2:T7-1-Scaleupto32concurrentflows
datastep,PROC:SUMMARY,SQL,SORT,etc.• IdenticalandreplicatedNtimesinparalleluptothenumberofprocessorcores• Eachflowconsumesupto750MBofRAM• Eachflowprocessesover80GBofI/OtotheSASWORKfilesystem
FortheT7-1configuration,thenumberofflowsisscaledfrom1to32;fortheM7-8DOMconfiguration,thenumberofflowsisscaledfrom1to48.Thetimesshownareaveragesteptimesacrossalltheflowsthatarerunningconcurrentlyforagivenrun.Forboththe32coreand48coresystems,thatworkloadperformstothesamelevelofscalability.Figures2and3showthatasthenumberofconcurrentflowisincreasedfrom1tothenumberofcores(32fortheT7-1and48fortheM7-8DOM)theperformancescalesin
excellentfashion.It’simportanttorealizethatasingleflowpresentsamassiveworkload.Figure2showsthatontheT7-1,32Xtheamountworkofasingleflowisaccomplishedinjust2xthetime.Figure3showsthesimilarpatternfortheM7-8-DOMwhere48xtheworkisaccomplishedinjust2xthetimeofasingleflow.SASsoftwareislicensedbycoresothisisanimportantconsideration.Goodperformanceunderloadisnotonlycriticalinlarge,multi-userenvironmentsbutalsoneedstobepredictableastheloadscalesup.
ScaleUp-Multi-ThreadedStreamManyofthenewerSASHighPerformanceAnalytics(HPA)procedurescanscalehorizontallyindistributedfashionorscaleverticallybytakingadvantageofthreadedalgorithms.Inthissection,verticalscalabilityisdemonstratedforvariousSASHPAprocedures.Figure4showsfourdatapointsforSPARCT7-1comparedtoaSPARCT5-2at16threads.
Figure3:M7-8DOM-Scaleupto48concurrentflows
Figure4:ComparativePerformanceofT7-1withT5-2forMulti-ThreadedProcedures
Figure4demonstratescomparativescalabilityatagiventhreadcount,buthowwelldotheprogramsscaleindividually?Figure5showsthescalabilityontheM7-8DOM(48corepartition)asthethreadcountisincreased.InFigure5below,timesareshownforeachHPAprocedureasthethreadcountisincreased.Lowerisbetter.PROCHPCOUNTREGisshowntorunat11hourswith2threads,comparedto19minwith96threads.
Figure5:ScalabilityofSASHighPerformanceAnalyticsProcedures
Figure6belowareresultscomparingtheseHPAprocedurestorunningthesameproceduresovera9nodedistributedenvironment.Note,thisisnotanapples-to-applescomparisonduetodifferencesinstorageandnetworkconfigurations,buttheresultsarecomparablebecausethesasapplicationlogic,datacontentsandresultsareequivalent.Thereareprosandconstoeachdeploymentarchitecture.Thegraphontheleftshowsrawperformancecomparison–3of4resultsareverycloseincomparison;
whilethegraphontherightshowsnormalizedperformance(time/#cores)wheretheT7-1showsexcellentlicensingvalue.
Figure6:SASHPAPerformance-Verticalvs.HorizontalScale
ExtremeCPU<->MemoryBandwidthWhat’sthesecrettoexceptionalscalabilityandperformance?EachM7sockethastheCPU<->Memorybandwidthtoprocess~120GB/sec.Figure7showsthebandwidthwhilerunningPROCHPREDUCE(variablereduction)withthreadcountequalto64.Ontheleft,isutilizationperCPUthread.WhilethePROCisrunning,~207GB/secCPUtomemorybandwidthissustained.
Figure7:CPU<->MemoryBandwidthforPROCREDUCEat64threads:~207GB/sec
ScaleUp–Both(ManyMulti-ThreadedStreams)Goodresultshavebeenpresentedforvariousworkloads–single,singlethreadedjobs,multiplesingle-threadedjobsrunningconcurrently,multi-threadedworkloads,etc.Whatresultscanbefoundwhenrunningmultiplestreamsofhighlyresourceintensivemulti-threadedSASHPAprograms?Figure8showstheresultsfromfiveSASjobswhicharerunconcurrently;eachjobisextremelyresourceintensivewhereitprocessesaverylargeandverywideSASdataset:106GBinsize,1100+variablesand12millionrows.Thejobscollectivelyconsumeover130threadsandarerunonthe48coreM7-8DOM(basically1.5M7CPUs).Thecollectivesetcompletesin~52min.Thisisoneofthemostcompellingresultspresentedhere.
Figure8:Runningfiveextremelyresourceintensive,multi-threadedSASjobsconcurrently
CombinedSAS&OracleDatabase12cLet’stakealookatadifferentSASworkloadweremultipleSASapplicationsarerunontheM7-8DOMthatisco-residentwithOracleDatabase12cwithIn-Memorytables.Figure9demonstratestheworkload.Figure10highlightsthetestsummaryandresults.50concurrentSASjobs,eachofwhichprocesses235Mrowsofa700Mrowtable,returns5.4Mrowscollectivelywritingover14GBtothelocalZFSfilesystem.Alljobsfinishin2secondswithtotalelapsedtimeforthejobsetat14seconds.
Figure9:CombinedOracleDatabase12candSASapplicationjobset
Figure10:ResultsummaryfromcombinedSASworkloadaccessingDatabase12c
RapidDeployment–MeanTimetoAnalytics?Withverticallyscaledenvironments,installation,deploymentcanprovidemoreagiledeploymentarchitectures.Combinedwiththescaleuptest,theinstallationcomponentwasaddedintotheoverallperformancetime.Figure11showsinstallANDruntimeresultabovefromfivesimultaneousjobs.
Figure11:SASInstallANDRun-Resultsin<1hr
SummarySPARCM7systemsbringnewlevelsofperformance,throughputanduniqueinnovationthroughSoftwareinSiliconfeaturesmakingitanexcellentplatformforSASapplications.Exampleswereshownwhichexaminedmultiplefacetsofperformance–singlecomputestrand,threadedcomputestrand,I/Operformance,networkperformance,andtheabilitytodriveworkloadsatfullsystemutilizationinapredictablefashion.Additionally,workloadswithco-residentDatabase12cwerealsoshownwithimpressiveresults.Solaris11.3providesfeatureswhichbringsecurefeaturesandflexiblevirtualizationoptions.ThisistrulyaplatformtoallowenterpriseslookingtoSimplifyIT.
MaureenChew,PrincipalSoftwareEngineer,Oracle,[email protected]–SolutionsArchitect,Oracle,[email protected]
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