Oracle SPARC M7 for SAS...Figure 4 shows four data points for SPARC T7-1 compared to a SPARC T5-2 at...
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Oracle SPARC M7 for SAS ® Vertical Scaling for Secure, Rapid, Agile Environments Simplify IT The Oracle SPARC M7 processor introduced unique Software in Silicon innovations combined with new levels of extreme memory bandwidth, compute performance and throughput. Features such as Silicon Secured Memory and on-chip crypto acceleration enable the strongest foundation for platforms that demand the highest level of security. The combination of M7 based systems with Solaris 11.3 brings new levels of security, performance, IT agility to meet the most demanding requirements of business critical SAS analytics and business intelligence applications. SPARC M7 systems are an excellent choice for running SAS High Performance Analytics Applications. Large-scale SAS environments can be deployed in either scale-out horizontal fashion or scale up in vertical fashion. Application deployments are not one-size fits all. Scale out deployments are perfectly suited in some environments and scale-up deployments are better suited in others. Performance studies often convey one dimensional or narrow views of application performance. Below is a brief survey of several different facets of SAS application performance to highlight a landscape of different considerations.
Transcript of Oracle SPARC M7 for SAS...Figure 4 shows four data points for SPARC T7-1 compared to a SPARC T5-2 at...
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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