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v1.0
WhitePaper
04-2017
Artificialintelligence:poweringthedeep-learningmachinesoftomorrow
Deeplearningneuralnetworksdemandsophisticatedpowersolutions
Abstract
Onceverymuchasciencefictiondream,artificialintelligence(AI)israpidlybecomingpartofourdailylives.WhileAItakesmanyforms,thesystemsthatmimicthehumanbrain'slearningandproblemsolvingcapabilitycompriseincreasinglycapablecomputerbased“neural”networksconsistingofmanyparalleledprocessorsthatruncomplexlearningandexecutionsoftwarealgorithms.
Whilethealgorithmsarekeytothistechnology,thecomputerpowersystemdemandsarestretchingtheboundariesofexistingpowerdeliverytechnology.Inthiswhitepaper,InfineonwilllookatthepowerdemandsforAIsystems,aswellaspresentingsomeofthelatest,state-of-the-art,powertechnologiesthatareenablingtheadvancesinthisexcitingarena.
By
DannyClavette,Director,SystemsApplicationsInfineonTechnologiesAG
Artificialintelligence:poweringthedeep-learningmachinesoftomorrow
PAGE
10
04-2017
Tableofcontents
Abstract 1
Tableofcontents 2
Overviewofartificialintelligence 3
Challengesforpowerdesigners 4
Digitalvsanalogcontrol 5
RecentpowertechnologyadvancessupportingAI 6
Multi-rail&multiphasedigitalcontrollers 6
IR35411andTDA21470OptiMOS?powerstages 9
Summary 11
Overviewofartificialintelligence
Humansaresmart,achievingintelligencethroughyearsoflearninganddataaccumulationaswellasarguablygetting“wiser”withage.Computerscouldbeconsidered“smart”duetodataretentioncapabilitiesbutuntilrecentlylackedthecapabilitytoautonomouslylearnfromtheselargedatabasesinordertoexecutetasksormakedecisions.Whileahumanbrainconsumes20-30Wofpower,thelatestlearningsystemsareconsumingpoweratlevelsthatwouldsupportasmalltownastheylearntobecome'artificiallyintelligent'.Whilewecandebatewhethercomputingisgetting'smarter'thanhumans,itisimpossibletodebatethattherequirementsforpoweringthisnewgenerationofsupercomputerhavechangeddramatically.
Insomeways,theapproachtakentoAIdeeplearningisquitesimilartohumandevelopmentwherecomputerscontinuetolearnthroughexposure.Intheexamplebelow,aneuralnetworkisfedwiththousandsoftrainingimagesthatareprocessedviamultiplelayersinordertobuildexperienceandknowledge.
Asaresultofthiscomputerintensiveandpowerhungrylearningprocess,thenetworkiseventuallyabletodistinguishasquirrelfromachipmunkorafox.ThegoalistoachieveAIlearningintheshortestamountoftime,thusparallelcomputingpowerismaximizedtolinearlyimprovecomputationtimes.
Thehighpowerconsumptionoftoday'sAIisdrivingchangesinthecomputingarchitecturetoreplicateneuralnetworksthatmimicthehumanbraininanefforttoreducepowerneeds.TraditionalCentralProcessingUnits(CPUs)arearchitectedtobeveryflexibletosupportawidevarietyofgeneral-purposeprogramsandarenotoptimizedforveryspecificandrepetitivetaskssuchasAIlearning.
ManyofthenecessaryfunctionsforAIcanbeperformedbyGraphicsProcessingUnits(GPUs).TheseGPUsaredesignedtorepeatedlyperformcomplexmathematicalfunctionsmoreefficiently,canbeconvenientlyconnectedinparalleltofurtherincreasecomputingpowerandbeopportunisticallyappliedtolearningapplications.Withslightmodifications,theselatestGPUdevicesprocess3xto10xfasterwhileconsumingthesamepowerasaCPU.TheearlyAImarkethasbeendominatedbyNVIDIA;theirDX1GPUsupercomputercontainseightTeslaP100GPUs,eachcapableof21.2TeraFLOPs,andrequires3200Woftotalsystempower.MultipleDX1sconnectedinparallelarerequiredtoformaneffectiveneuralnetwork.
Honingthetechnologyevenfurther,TensorProcessingUnits(TPUs)areASICsthathavebeendevelopedspecificallyformachinelearning.BasedonGPUplatforms,reducedfloating-pointaccuraciesallowmorecomputecapabilityperclockcycle.Rasterizationandtexturemappingfeaturesarealsoremovedtofurtherimprovecomputationefficiency.GooglelaunchedthefirstTPUin2015andIntelisexpectedtolaunchLakeCrestthisyear,targetingDeepNeuralNetwork(DNN).
Tolearn,networksneedtobeabletosense.Local'edgedevices'includesensors,cameras,datacollectorsandlocalactuators.ConnectedtothecentralAIserversviahigh-speedwirelessconnections,theselowpowerdevicesaretheeyes,earsandhandsoftheneuralnetwork.Estimatespredictthattherewillbeover50billionedgedevicesconnectedtothenetworkby2020.
Itshouldcomeasnosurprisethat,despitethepowerchallenges,themarketforAIisgrowingrapidlyasdemonstratedbythe(approximately)40-foldgrowthatGoogleinthepasttwoyears.
Challengesforpowerdesigners
Thepowerlevelsrequiredforthisnewtechnologyaresimplystaggering.Inordertomatchtheprocessingpowerofahumanbrain,asystemwouldneedtoperformmorethan38thousandtrillionoperationspersecond(or38PetaFLOPSaccordingtoDharmendraModha,IBMFellowandChiefScientistattheAlmadenResearchCenter).Foraninterestingcomparison,aserverfarmusingNVIDIA’sDX1’s21.2TeraFLOPsper3200Wadvertisedperformancewouldrequireapproximately1800DX1sconsumingnearly6Megawatts(3200W*38e15/21.2e12).Thehumanbrainontheotherhand,requiresonly20Wofpower.
Thechallengefacingpowerdesignersismulti-faceted.Simplydeliveringtheselevelsofpowerischallengingenough.Efficiencyisabsolutelycritical,notonlyasenergycostsarerising,butalsoaseverywattofwasteenergydissipatedasheatincreasestheairconditioningrequirementsinthedatacenter,furtherincreasingoperationalcostsandcarbonfootprint.
Realestateisalsorisingincostand,asdatacenterscontainhundredsorthousandsofprocessingunits,sizeisimportant.Asmallreductioninthesizeofasingleunitisreplicatedmanytimesover,allowingmoreprocessingpowertobelocatedinthesamespaceaslargersolutions.Yet,thissmallersizerequirementrapidlyincreasespowerdensityandreducesthesurfaceareaavailablefordissipatingheat,makingthermalmanagementoneofthesignificantchallengesindesigningpowerforthisnewgenerationofAIsupercomputers.
Computingsystemsarecomplexloads;whilelearningtheyarerunningatfullpower.Astheactivitydrops,sodoesthepowerrequirement,buttheefficiencyisrequiredtoremainashighaspossiblethroughoutthepowerband.Withtoday'smulti-phasepowersolutionsthisentailsthedesignerbuildinginprovisionforcontrollingthenumberofphasesusedtoensurethatefficiencyisoptimizedatalltimes.
Digitalvsanalogcontrol
Clearly,amoresophisticatedapproachtopowerdesignisgoingtoberequiredtomeettheneedsofthisrapidlygrowingsector.Inordertoaddressthisneed,Infineonhasintroducedadvanceddigitalcontroltechniques,replacingthelegacyanalog-basedsolutions.
Digitalcontrolbringsmanybenefitswhendesigninghigh-endpowersolutions,notleastoverallsystemflexibilityandadaptability.Withdigitaltechnology,controllerscanbecustomizedwithouttheneedforexpensiveandtime-consumingsiliconspins.Thecustomizationextendstodefiningtheconfiguration,telemetryforgatheringsystemperformancedata,settingfaultmanagementandcalibratingthedevice.
Aspowersystemsbecomemoreintegratedintotheoverallsolution,communicationbetweenthepowersolutionandthemainCPU/GPU/TPUisanewrequirement.Infineon’smaturedigitalcontrollertechnologyfacilitatesmarket-leadingsolutionsandincludesaGUIthatenablesreal-timesystemdesign,configuration,validationandmonitoring.
DigitalsolutionssimplifybuildingthescalablepowersolutionsrequiredforAI.Yetwithalloftheincludedfunctionalityandprecisiondeliveryofpower,theyarenowpricecompetitivewiththeanalogsolutionstheyareultimatelyreplacing.
RecentpowertechnologyadvancessupportingAI
Infineonisoneoftheleadingdesignersandmanufacturersofadvancedpowercontrolandswitchingtechnologies.TheirproductofferingishighlyintegratedandprovidesallofthekeysiliconelementsrequiredtobuildhighlyadvancedpowersolutionsforAIapplications.
Infineon'scompleteportfolioincludeshugebreadthofproductsincludingdigitalcontrollers,integratedpowerstages,integratedpowermanagementICs,Point-of-Load(POL)convertersaswellasdiscretesolutionsincludingdriverICs,powerblocksanddiscreteMOSFETs.TherangeisbuiltuponInfineon'slonghistoryofinnovationandcomprisesmultiplemarket-leadingtechnologiessuchasOptiMOS?,DrMOS?andμDrMOS?.
Figure1 Infineonoffersfullflexibilityintermsofspace,performanceandcost
Multi-rail&multiphasedigitalcontrollers
CentraltoInfineon'sofferingforservers(aswellasworkstationsandhigh-enddesktops)isacompletecontrollerproductfamilyofmulti-rail/multiphasedigitalcontrollers.TheseadvancedcontrollersarecomplianttoIntel?,AMD?andsupportPMBUSwithAVS(AdaptiveVoltageScaling)forvoltageset-pointcontrolandsystemtelemetrywithupto50MHzmaxoperation.
Infineonsolutionsareprogrammabletoprovideone,twoorthreefullydigitallycontrolledvoltagerailswithupto10phases.InfineonalsooffersafamilyofdoublingICsandDriverstofurtherincreasephasecount.
Figure2 Infineon’srangeofadvancedcontrollersarecompliantwithIntel?andAMD?standardsandalsosupportPMBUSwithAVS(AdaptiveVoltageScaling)
Efficiencyacrossawideloadrangeissupportedthroughtheabilityofdesignerstoprogramautonomousphaseadditionorshedding.OtherprogrammablefeaturesincludePIDloopcompensation,loadlineslopeandoffsetaswellasdigitaltemperaturecompensation.
Externalloadlinesettingcomponentsareeliminatedbythedigitallyprogrammableloadline.ThecontrollerisdesignedtoworkwithRDS(ON)&DCRcurrentsensepowerstagesandprovidesaccurateinputandoutputcurrentreporting.
Digitalcontrolenablesproprietarynon-linearcontrolalgorithmsandprovidesexcellenttransientresponsewithreducedoutputcapacitance.Mostofourcontrollersalsosupportprogrammablecycle-by-cycleperphasecurrentlimitforsuperiordynamiccurrentlimiting.
ThesedevicesareeasilyconfigurableusingouroptimizedGraphicalUserInterface(GUI)toolswithfinalconfigurationsettingsthatcanbestoredinourdigitalcontroller’son-chipnon-volatilememory.
Aswouldbeexpectedofasophisticatedcontroller,significantfaultdetectionandprotectionisin-builtincludingIUVP,IOVP,CFP,OUVPandOOVP(InputUndervoltageProtection,InputOvervoltageProtection,CatastrophicFaultProtection,OutputUndervoltageProtectionandOutputOvervoltageProtection).Overcurrentprotection(OCP)isprovidedasaninstantaneousvalue,averagedfortotalcurrent,bychannelaswellaspulse-to-pulse.TherearemultipleOverTemperatureProtection(OTP)thresholds(internalandexternal)aswellasopen/shortvoltagesenselinedetectionandnegativecurrentlimitprotection.
InsomeofInfineon'slatestcontrollers,thecombinedstate-machineandintegratedmicrocontrollercorearchitectureallowformaximumflexibilityandtheinternalNon-VolatileMemory(NVM)storestheparametersofanycustomconfigurations.
Figure3 IR35215blockdiagram
IR35411andTDA21470OptiMOS?powerstages
TheIR35411powerstagecontainsalowquiescentcurrentsynchronousbuckgate-driverIC,high-sideandlow-sideMOSFETsandaSchottkydiodeinthesamepackagetofurtherimproveefficiency.ThepackageisoptimizedforPCBlayout,heattransfer,driver/MOSFETcontroltiming,andminimalswitchnoderingingwhenlayoutguidelinesarefollowed.ThepairedgatedriverandMOSFETcombinationenableshigherefficiencyatloweroutputvoltagesrequiredbycuttingedgeCPU,GPUandDDRmemorydesigns.
TheIR35411internalMOSFETcurrentsensealgorithmwithtemperaturecompensationachievessuperiorcurrentsenseaccuracyversusbest-in-classcontrollerbasedinductorDCRsensemethods.Protectionincludescycle-by-cycleOCPwithprogrammablethreshold,VCC/VDRVUVLOprotection,phasefaultdetection,ICtemperaturereportingandthermalshutdown.
Figure4 IR35411blockdiagram
TheIR35411featuresdeep-sleeppowersavingmode,whichgreatlyreducesthepowerconsumptionwhenthemultiphasesystementersPS3/PS4mode.
Operationofupto1.5MHzswitchingfrequencyenableshighperformancetransientresponse,allowingminiaturizationofoutputinductors,aswellasinputandoutputcapacitorswhilemaintainingindustry-leadingefficiency.
WhencombinedwithInfineon’sdigitalcontrollers,theIR35411incorporatestheBody-Braking?featurethroughPWMtri-statethatenablesreductionofoutputcapacitors.ThisquicklydisablesbothMOSFETsinordertoenhancetransientperformanceorprovideahighimpedanceoutput.TheIR35411isoptimizedforCPUcoreandmemorypowerdeliveryinserverapplications.
TheIR35411isanidealcompaniontotheIR35215multi-phasecontroller.
Figure5
belowshowshowtheIR35215combineswithfourIR35411stocreateaVRpowerstageina6+1configuration.
Figure5 VRusingIR35215controllerandIR35411powerstagein6+1configuration
Summary
WhileAIisstillearlyinitsdevelopment,itisalreadybeingrecognizedtobeanimportantandrapidlygrowingapplicationwithexpectedsubstantialimpactsonoursocieties.ThesepioneeringAIalgorithmsareenabledthroughseveralhighperformancecomputersystemsthatarechallengingdesignersonmanyfronts.Thetraditionaldatacenterdesignsarerapidlymigratingfromgeneral-purposeCPU-onlysolutionstowardscombinationsofCPUsandGPUsorTPUs,bringingnewandmorestringentdemandsondesignofserverpowersolutions.
Infineonoffersindustry’shighestefficiencypowerstagesthatutilizeInfineon’smarketleadingOptiMOS?MOSFETtechnology.ThroughcontinuedInfineonadvancementsinitspowersemiconductortechnology,ourdevicesarebecomingincreasinglyefficientresultingincontinuedpowerlossreductionswhileincreasingoursolutiondensities.
Infineondigitalcontrollersbringunprecedentedflexibilityandadaptabilityaswellasprecisecontrol,telemetryandprotectionfeatures.AsaleaderinthisAIpowerdeliverymarket,InfineonoffersabroadrangeofcontrollersandOptiMOS?powerstagesthatcansupportallknownAIhardwareplatformsandtheirdemandingcurrentlevels.Infineonenablesdesignerstocreatestate-of-the-artpowersolutionswithhighestefficiencyandpowerdensityfort
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