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AdvancedComputerArchitecture

FedericoDominguez

WardVanHeddeghem

Literaturestudy:theTriMedia,C6000,SODAandEVPprocessorarchitectures

December19,2008

1 IntroductionThisreportdescribesandcomparesthemicro‐architecturalaspectsandISArationaleof4processors:

• theTriMediamediaprocessor(NXP,formerlyPhilipsSemiconductor),

• theC6000platform(TexasInstruments),

• theSODAarchitecture(UniversityofMichigan)

• andtheEVP(NXP).

These4processorscanallbebroadlycategorizedasapplicationspecificdigitalsignalprocessors(DSPs).Thefirsttwoprocessors(TrimediaandTI’sC6000)aretargetedasmediaprocessors,thelattertwo(SODAandEVP)areprocessorsdevelopedalmostexclusivelyforSoftwareDefinedRadio(SDR).

MediaprocessorsaretypicallyfoundonDVDplayers,digitalTV,IPTV,videosecuritysystems,videoeditingsystems,etc.SDRprocessorstrytoreplacetheRFprocessinghardwarebysoftware,andareaimedmainlyatconsumerhandhelddevicessuchasPDAs,SmartPhones,MobilePhonesetc.

2 GeneralcomparisonofmediaandSDRprocessors

2.1 MultimediaProcessing

Multimediaprocessingisthehandlingofvideoandaudiodatainelectronicdevices.Thisissometimesaccomplishedbyspecificpurposeintegratedcircuits,butthelackofflexibilityandhighcostofthisapproachhasledtothedevelopmentofmultimediaprocessors,programmableprocessorsspeciallydesignedtoefficientlyexecutealltasksrelatedtomultimediaprocessing.MultimediaprocessorsaretypicallyfoundonDVDplayers,digitalTV,IPTV,videosecuritysystems,videoeditingsystems,etc.[5]

Themostcommontasksforamultimediaprocessorare[10]:

• Image,videoandaudiodecodingandencoding• Image,videoandaudiocompression• Image,videoandaudiotransmission• Image,videoandaudioenhancement,filtering• Patternrecognition• Motiondetection

Sincemultimediaprocessorsaremostoftenfoundonbatteryoperatedembeddeddevicesandsincethenatureofmultimediaprocessingrequiresrealtimedeadlines,thedesignchoicesinthisfamilyofmicroprocessorsaimtoachievehighperformanceprocessingofmultimediadatastreamswithminimumpowerconsumptionandunitcost.[5]

Multimediaprocessorsachievethesegoalsbyoptimizingtheexecutionofthemultimediatasksmentionedabove.Thisimplies:

• Highlevelofparallelism:VLIW,SIMDtoboostperformanceandtoallowforalowcostsiliconimplementation.

• Largecachememories:Toaccommodatetypicallylargeimagesandvideoframesclosetotheprocessorsavingcostlymemoryaccessandbandwidth.

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• Penaltyfreeun­alignedmemoryaccess:Processingalgorithmstypicallyaccessimageblocksinanun‐alignedmanner.

• Datapre­fetching:Multimediaprocessingalgorithmsaccessmemorylocationsinpredictablestridesandblocks.

• Largeregisterfiles:Largedataworkingsetscanbekeptinregisters,preventingcostlyloadandstoreoperations.

• DMA­stylememorytransfers:Increasesoverallsystemperformance.• Applicationspecificinstructions:Typicalmultimediaoperationscanbedoneinoneora

fewclockcycles,savingenergyandgainingperformance.• Smalldatawords:8and16‐bitdatawordsaretypicallysufficientformostmultimedia

processingtask.Limitingthesizeofdatawordsallowsforhighermemorydensityandparallelism.

TriMediaandTIC6000aretwocompetingfamiliesofmultimediamicroprocessorsthatinonewayoranotherimplementthearchitecturaldesignchoiceslistedabove.

2.2 Software‐definedradio(SDR)

Thephysicallayerofmostwirelessprotocolsistraditionallyimplementedincustomhardwaretosatisfytheheavycomputationalrequirementswhilekeepingpowerconsumptiontoaminimum.Theseimplementationsaretimeconsumingtodesignanddifficulttoverify.Aprogrammablehardwareplatformcapableofsupportingsoftwareimplementationsofthephysicallayer,orsoftware­definedradio(SDR),hasanumberofadvantages:supportformultipleprotocols(i.e.multimodeoperation),fastertime‐to‐market,higherchipvolumes,andsupportforlateimplementationchanges.SDRcanbeconsideredasahigh‐enddigitalsignalprocessing(DSP)application.[13]

ThedigitalbasebandprocessingforSDRcanbedividedintothreestages:filterstage,modemstage,andcodecstage.

• Thefilterstagerequiresahighcomputationalloadanditsimplementationisuniformbetweendifferentstandardsandalgorithms,aprogrammablesolutionwouldnotbethemostefficientone.

• Themodemstageisdiverseamongdifferentstandards,inthisstagethereisplentyofspacefordifferentvendorstodifferentiatetheirproductsbyapplyingdifferentalgorithmsandstandards.Thisstageisidealforafullyprogrammablesolution.

• Thecodecstageisimplementedbysimilaralgorithmsacrossseveralstandardsmakingaprogrammablesolutionnotdesirable.[17]

ThemodemstageofdigitalbasebandprocessingisanidealapplicationforaprogrammableSDRprocessor.SODAandEVParetwosuchprocessors.

ThemaindesigngoalsoftheseSDRprocessorsaretypicallyhighperformance(imposedbythehighthroughputrequirementsofcurrentwirelessprotocols),energyefficiency(batteryoperateddevices)andprogrammability(multi‐protocolsupport,higherchipvolumes).

2.3 Commoncharacteristics

Asisclearfromthediscussionabove,bothmediaandSDRprocessorsarecharacterizedbyanumberofcommonproperties:theyshouldachievehighperformanceprocessingofdatastreams,mustmeetreal­timedeadlines,shouldbeenergyefficientsincetheyaretypicallyusedonmobile(batteryoperated)devices,andtheyshouldbehighlyprogrammableastoprovidesupportfordifferentandnewmediaandradioprotocols.Thedatastreamstheyoperateonarerelativelysmall(8or16bit).

Figure1showsthethroughputandpowerrequirementsofanumberofwirelessprotocols,aswellastheperformanceoftwoprocessorsdiscussedinthispaper:theTIC6000andtheSODAprocessor.Thisfiguregivesagoodnotiononthepowerefficiencytheseprocessorstargettoachieve.

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Figure1–Throughputandpowerrequirementsoftypical3Gwirelessprotocols[13]

2.4 DifferencesbetweenmediaandSDRprocessors

Asmuchastheyhaveincommon,thesetwogroupsofprocessorsalsoaredistinctlycharacterizedbytheirintendedapplication:mediaandSDR.Inthenextparagraphswewillhighlightsomeofthemajordesigndistinctionsbetweenthesetwoprocessorgroups.

Differencesbetweenthetwomediaprocessors,anddifferencesbetweenthetwoSDRprocessorswillbediscussedin§3.3and§4.3respectively.Table1givesthespecificationofeachofthefourprocessors.

SIMDwidth—Sincemediaprocessorstypicallyoperateonsmallmacroblocks(amacroblockisausedinvideocompressingandrepresentsablockof16by16pixels[1]),smallervectorssuffice.ThistranslatesinnarrowSIMDdesignsformediaprocessors.ForSDR,ontheotherhand,mostofthecomputationallyintensivealgorithmshaveabundantdatalevelparallelism,muchmorethaninstructionlevelparallelism,sowideSIMDisveryefficient.[13]ItshouldalsobenotedthatSIMDingeneralispowerefficientcomparedtootherarchitectures,sincethe‘overhead’ofaddresscalculation,addressdecoding,instructionfetchingetc.issharedperpoperations.[16]

Predication—Predicationisavailableonbothmediaprocessors.Thisseemslogicalsinceinvideocompressing,acommonthingtodoiscomparedatawithpreviousdata(e.g.inmotionestimation).Predicationcouldthenbeapowerefficientwaytomakedecisions,asopposedtocostlybranching.Wehavenotfoundanyhardreferencestobackupthisassumption.However,onedocumentexplicitlymentionspredicationastechniqueforincreasingperformanceinmediaprocessors.[2]ForSDRprocessorswedidn’tfindanyindicationsthatpredicationisused.

Datawidth—Bothmediaprocessorshaveadatawidthof32bits,incontrastwiththeSDRprocessorswhichhaveonlyhalfofthat.Thisprovidesmediaprocessorswithamuchlargeraddressablememoryrange,notinvaingivennewvideostandardslikeHDTV,whichcurrentlyreachesuptoresolutionsof1920x1080pixels(i.e.atotalof2.073.600pixels,farbeyondwhatisaddressablewith16bits).[1]AlgorithmsrunningonSDRprocessorstypicallyoperateonvariableswithsmallvalues.Analysisoftwotypicalwirelessprotocolsshowsthatthereshouldbestrongsupportfor8and16‐bitoperations.[13]Also,wirelesspacketshandledbytheseprocessorsdon’tpotentiallyconsumeasmuchmemoryspaceasthemediaprocessors.

Unalignedloads—Mediaprocessingalgorithmstypicallyaccessimageblocksinanun‐alignedmanner.Asalreadymentioned,whendealingwithvideocompression,mediaprocessorshandlemacroblocks.Thelocationofthesemacroblocksisnotfixed,neitheronscreen,norinmemory.Itseemslogicalthatprovidingforunalignedloadsallowstheseblockstobefetchedfaster.We

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don’thaveanyreferencestobackupthisassumption.ForSDRprocessorswedidn’tfindanyindicationsthatunalignedloadsaresupported.

Cache—Onmediaprocessors,cachesareimplemented(oroptional),toaccommodatefortypicallylargeimagesandvideoframesclosetotheprocessor,savingcostlymemoryaccessandbandwidth.SDRprocessorsdon’timplementcachessincetheyoperateonstreamingdata(cachingisofusethen),andtheyrequirereal‐timebehavior.[13]

Delayslots—Delayslotsareavailableonmediaprocessorstoimproveperformance.OnSDRprocessors,delayslotsarenotusedsincebranchpredictionisn’tuseeither.

Table1–Processorspecifications

Mediaprocessors SDRprocessorsFeature

TriMedia C6000 SODA EVP

Architecture Uni‐processor5issueslotVLIWguardedRISC‐like

operations

Uni‐processor 1ARMprocessor+4PEs(processingelements)staticscheduled

Uni‐processorSIMDthroughvector

processingcapabilities.13issueslotVLIWscalarand

vectoroperationsVLIW Yes Yes Yes YesPipelinedepth 7–12stages 11stages 5stages ‐‐Datawidth 32bits 32bits 16bits 16bitsRegisterfile Unified,12832‐bit

registersClustered,1632‐bitregisters

PerPE:32x16SIMD16‐bitregisters,16scalar16‐bitregisters

16vectorregisters(eachregistercontains16

words).32scalarregisters.

Functionalunits

31 8 PerPE:32+1 6vector,3scalar

SIMDcapabilities

1x32‐bit,2x16‐bit,4x8‐bit

C62/67:noC64:4x8‐bit,2x

16‐bit

PerPE:32x16‐bit

16x16‐bits

Memorystructure

Cache Optionalcache Clustered,ScratchpadGlobal:64KB

PerPE:4KBscalar,8KBSIMD

Scratchpad

• Instructioncache

64Kbyte,128‐bytelines,8wayset‐associative,LRUreplacementpolicy

(modeldependent)

No No

• Datacache 128Kbyte,128bytelines4wayset‐associative,LRU

replacementpolicy,Allocate‐on‐writemiss

policy

(modeldependent)

No

No

Frequency 240MHz(300MHz) 300MHz(1GHz)

380MHz 300MHz

Delayslots 5forbranchinstructions

1formultiplyinstruction,4foraloadinstructionand5forabranch

instruction

No No

Compression Yes(10bittemplate)

Yes(usingstopbits)

NDA NDA

Predication Yes Yes NDA NDA

Forwarding Yes Yes No NDAUnalignedloads

Yes Yes DNA DNA

Compiling/programming

Hard.C,C++withspecial

extensions.

Hard.C,C++,assembly.

Hard.SPIRontopofhighlevellanguage

Hard.EVP‐C

NDA:nodataavailable

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3 Multimediaprocessors:TriMediaandTIC6000

3.1 TriMedia

Remark:unlessotherwisespecified,theinformationinthissectionistakenfromthemainTriMediapaperbyVandeWaerdt,etal.[3]

3.1.1 Introduction

TriMediaisafamilyofmicroprocessorsdevelopedbyNXP.ThemainapplicationoftheTriMediamicroprocessorsismultimediadataprocessinginembeddedsystems.ThisparticularapplicationdomainshapestheTriMediamicroprocessordesign,divergingdrasticallyfromgeneralpurposeprocessors.

TriMediaprocessorsaredeployedonconsumerdevicesasaSystemOnChipsolution.TriMediaisprogrammable,sothatitcanbeadaptedtomanydifferentapplicationsandsothatproductscanbechangedthroughsoftwaretomeetevolvingstandardsrequirements[5].

TriMediaprocessorsemployVLIWarchitecture.Thelatestmodel’sCPUcore(TM3270)has31functionalunitswithfiveissueslots.ThisfamilyofprocessorsalsosupportsSIMDoperations.VLIWandSIMDprovideahighdegreeofinstructionparallelism,optimizingtheoverallperformanceofthesystem.

3.1.2 Architectureoverview

TriMediainstructionanddatalevelparallelism

TriMediaimplementsinstructionanddatalevelparallelismthrougha5‐issueslotVLIWandthroughSIMD,respectively.VLIWsupportsupto5operationsperinstructionword.SIMDinstructionscanworkontwo16‐bitdatawordsorfour8‐bitdatawords.

Figure2showsthefunctionalunitsoftheTM1000,thefirstmemberoftheTriMediafamily.TheTM1000has28functionalunitsdividedamongfiveissueslots.TheTM3270hasaddedthreenewfunctionalunits(totaling31units)butmaintainsthesamebasicdesignstructureastheTM1000.Ascanbeseeninthefigure,eachissueslothasmultipletypesoffunctionalunits,allowingthecompilermorefreedomwhenschedulingtheVLIWinstructions.

TheTM3270implementssuper­operationsortwo‐slotoperations.Theseoperationsareexecutedbytwofunctionalunitsthatoccupytwoneighboringissueslots.Theseoperationscantakeuptofouroperandsanduptwodestinationoperands.Two‐slotoperationscanimproveoverallsystemperformancesincetheequivalentseparateoperationsrequiremorecyclestocomplete.

Figure2­TriMediaTM1000FunctionalUnits[5]

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Cachepoliciesandmemoryprefetching

TheTM3270hasa128Kbytedatacachewith128cachelines.Thecachesupportspenalty‐freeunalignedaccesses;imageprocessingtypicallyrequiresfetchingblocksofunalignedimagedatafrommemory.Thecachehasawrite‐backpolicyandanallocate‐on‐write‐misspolicy.Thecombinationofthesetwopoliciesreducestherequiredbandwidthtooff‐chipmemory.

TheTM3270supportsprefetchingandisbasedonmemoryregions.Theprefetchingpatternandregioncanbespecifiedbytheprogrammerandisdesignedtomatchthememoryaccesspatternoftypicalmultimediacodecalgorithms(typicallyunalignedandnon‐sequential).TheTM3270supportsfourseparatememoryregions.Thepatternisdefinedbyastartandendaddressandastride.Theregionspecifiedbythestartandendaddressisusuallyacompleteimageorframe,andthestridecorrespondstothesizeoftheblockswithintheimagethatarebeingprocessed.Themaingoalofprefetchingistoreducecachemissesandthereforeavoidcostlystallcyclesandimprovesystemperformance.

Pipeline

Figure3showsabasicblockdiagramoftheTM3270pipeline.Thepipelinehasaminimumdepthof7stagesforsinglecyclelatencyoperationsandamaximumof12stagesformorecomplexinstructions.Thefrontendofthepipelineconsistsofinstructionfetch(I1–I3)andinstructionpre‐decode(P).Theinstructionfetchcontrolunitatthefrontendofthepipelinesupports5delayslotsforthejumpoperation,thenumberofdelayslotscorrespondstothedistancebetweenthefirststageandthefunctionalunits.Thebackendofthepipelineconsistsofoperationdecode(D),execution(X1‐X6)andwrite(W).

DataforwardingfromtheCacheWriteBufferiscurrentlynotimplementedintheTriMediapipelinebecauseitsinclusioncausespathdelaysbeyondthedesireddesignparameters.Predicationissupportedbyusingguardregisters;eachoperationexecutionispredicatedwiththeleastsignificantbitofitsguardregister.[6]

3.1.3 Compilersupport

TheTriMediaprocessorfamilycomeswithcompilersupportfromthemanufacturer.Binarycompatibilityisnotguaranteedbetweendifferentmodelswithinthefamilyrequiringadifferentcompilerforeachmodel.ThesupportedprogramminglanguageisC/C++.

ProgramswritteninC/C++arecompatiblebetweenmodelsprovidedtheyarerecompiledforeachmodel.Someperformanceislostwhenportingprogramswrittenforonemodeltoanewermodelwithoutincludingmodelspecificoptimizations.ForexamplewhenportingaprogramfromtheTM3260totheTM3270,aperformancegainof20%canbeobtainedwhenapplyingnewdataprefetchingtechniques.

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Figure3­TriMediaTM3270Pipeline[3]

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3.2 TIC6000

Remark:unlessotherwisespecified,theinformationinthissectionistakenfromanumberofTexasInstrumentsreferencedocuments.[7][8][9][10]

3.2.1 Introduction

TheTMS320C6000digitalsignalprocessor(DSP)platformispartoftheTMS320DSPfamilydevelopedbyTexasInstruments.

TheTMS320familyconsistsof16‐bitand32‐bitfixed‐andfloating‐pointDSPs.Therearethreemainplatforms,includingtheTMS320C2000(controlapplications),theTMS320C5000(power‐efficientapplications),andtheTMS320C6000(high‐performancesapplications).Theseprocessorsareusedincellphones,digitalcameras,modemsetc.

TheC6000platformisaverylonginstructionword(VLIW)architecturetargetedathigh‐performanceDSPtasks.Itcomprisesthefollowingthreemaingenerations(i.e.versions):

• TMS320C62x(‘C62x)offeringfixed­pointarithmeticupto300MHz,

• TMS320C64x(‘C64x)offeringfixed­pointarithmeticupto1GHz,

• TMS32067x(‘C67x)offeringfloating­pointarithmeticupto300MHz.

3.2.2 Architectureoverview

Overview

The‘C6000processorconsistsofthreemainparts:aCPU,peripherals(notdiscussedfurther)andmemory.Theprocessorsoperateatvariousfrequencies,rangingfrom150MHzupto1GHz.

Theprocessorexecutesuptoeight32‐bitinstructionseverycycle.ThecoreCPU,asshowninFigure4,consistsofeightfunctionalunits,tworegisterfilesandtwodatapaths.

Figure4–The‘C6000blockdiagram

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CPU

TheCPUhastwoclusters(labeleddatapath1and2inFigure4)inwhichprocessingoccurs.Eachdatapathhasfourfunctionalunits(.L,.S,.M,and.D)andaregisterfilecontaining1632‐bitregisters(32forthe‘C64xgeneration).

Thefunctionalunitsexecutelogic,shifting,multiply,anddataaddressoperations.Allinstructionsexceptloadsandstoresoperateontheregisters.Thetwodata‐addressingunits(.D1and.D2)areexclusivelyresponsibleforalldatatransfersbetweentheregisterfilesandmemory.Thecrosspathsbusconnectingbothdatapaths,supportsonereadandwriteoperationpercycle.

VLIWprocessingflowbeginsbyfetchinga256‐bitwidepacket(eight32‐bitwords)fromprogrammemory,whichisthendynamicallydispatchedoverthedifferentfunctionalunits(FUs).DynamicdispatchingreferstothefactthattheorderofinstructionsinaVLIWshouldnotmatchtheorderofthefunctionalunits;insteadinstructionsintheVLIWaredispatchedtotheappropriateFU.

Thepipelinestagesaregroupedinto3phases:instructionfetch(4stages),instructiondecode(2stages)andinstructionexecute(maximum5stages).Thepipelinealsosupportsdelayslotsformultiply(1delayslot),load(4delayslots),andbranch(5delayslots)operations.

Memory

Dataandprogrammemory—TheC6000DSPhasa32‐bit,byte‐addressableaddressspace.Internal(on‐chip)memoryisorganizedinseparatedataandprogramspaces,whichmaybeconfiguredascacheonsomedevices.Whenoff‐chipmemoryisused,thesespacesareunifiedonmostdevicestoasinglememoryspaceviatheexternalmemoryinterface(EMIF).

Memoryports—TheC6000DSPhastwo32‐bitinternalportstoaccessinternaldatamemory.TheC6000DSPhasasingleinternalporttoaccessinternalprogrammemory,withaninstruction‐fetchwidthof256bits.

Memoryalignment—TheC6400,unliketheC6200andC6700,supportsunalignedmemoryaccessforloadandstoreoperations.Wordanddouble‐worddatadoesnotalwaysneedalignmentto32‐bitor64‐bitboundariesasintheothermodels.

‘C64xextensions

Thekeyextensionsbetweenthe‘C62x/’C67xarchitectureandthe‘C64xarchitecturethatallowmoreworkeachclockcycleinclude(seealsoFigure5):

• widerdatapaths(dual64‐bitload/storepathsinsteadof32‐bit),

• alargerregisterfile(32registersinsteadof16),

• moreorthogonality,i.e.moregeneralityinthearchitecture(forexample,the.DFUcanperform32‐bitlogicalinstructionsinadditiontothe.Sand.Lunits).

• unalignedmemoryaccessforloadandstoreoperations.

• MoreSIMDsupport.Forexample,thefunctionalunitsontheC64xcannowexecutetwo32‐bitmultipliesandfour16‐bitmultiplies.OnFigure5,theyellowboxesineachfunctionalunitontheC64xrepresenttheincreaseinSIMDsupport.ThisincreaseinSIMDparallelismispossibleduetotheincreasedregisterfilesizeanddatapathwidth.

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Figure5–Differences‘C62/67xand‘C64xgeneration

3.2.3 Compilersupport

TheC6000platformcanbeprogrammedusingC,C++orassemblylanguage.

TexasInstrumentsprovidesaproprietarytoolchainandIDE,calledCodeComposerStudio,todoso.NoothercompilersareavailablefortheC6000platform;however,adepartmentattheChemnitzUniversityofTechnologydevelopedpreliminarysupportfortheTMS320C6xseriesintheGNUCompilerCollection(GCC).[12]

ThefactthatonlyonepropertoolchainisavailablefortheC6000platform,andthatTIprovideshand‐optimizedlibrariesforvariousalgorithms(forexample,FFT),seemstoindicatethatitcanbeacomplextaskfortheprogrammertomanuallydevelopsoftwarethatefficientlyusesthearchitecturalresourcesandcapabilitiesoffered.

ThisassumptionisenforcedbyanInternetforumpostcitingaTICcompilerdeveloper:“Hisanswer[tothequestionwhytherearenoothercompilerssupportingC6000]wasthatwhenTIdevelopedtheC6000core,itwasaside­by­sidedevelopmenteffortbyboththehardwareandsoftwaredevelopers,andthattheCcompilerbynecessitywouldberathercomplexandhenceveryhardforathirdpartytodevelop.”[11]

3.3 ComparingTriMediaandTIC6000

Remark:unlessotherwisespecified,theinformationinthissectionistakenfromanumberofTexasInstrumentsreferencedocuments[7][8][9][10]andthemainTriMediapaperbyVandeWaerdt,etal.[3]

TriMediaandTIC6000achievehighperformance,lowpowerconsumptionandlowunitcostbyimplementingthearchitecturalfeaturesdescribedin§2.1.However,thedetailsofhowtheyaccomplisheachfeaturemaydifferbetweenthem.Eacharchitecturalfeatureimpliesdesigncompromisesthatweresometimessolveddifferentlyineachprocessor.

Mostofthearchitecturaldesignchoicescanbedividedbythegoaltheytrytoreach:highperformanceorlowpowerconsumption.Althoughthesetwogoalscertainlyoverlapattimes,forclaritythemaincomparisonbetweenthetwoprocessorfamiliesisdividedassuch.

3.3.1 Highperformance

ParallelismonTriMedia—ThealgorithmsrequiredtoimplementvideoprocessingcodecsaresuitableforparallelizationusingVLIWandSIMD.Theytypicallyrequiresimilarindependentoperationsonmultiplesmalldatawords.TriMediaprocessorsprovideinstructionsandsuperinstructionsthataccomplishtypicaltasksinthesecodecsinfewcyclesandwithminimummemorybandwidthconsumption.TheVLIWinTriMediaisimplementedwith5issueslotsandcompressedwitha10‐bittemplatefield.

ParallelismonTIC6000—VLIWandSIMDprovideinstructionanddatalevelparallelismintheTIC6000.Inaddition,compressionthroughstopbitsissupported:parallelismofinstructionsin

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thefetched256‐bitVLIWcanbecontrolledbyusingastopbit,whensettingtheleastsignificantbit(LSB)ofeachoftheeightcontainedindividualinstructionstoeither0or1.Whensetto1,theindividualinstructionwillbeexecutedinparallelwiththesubsequentindividualinstruction.Thisallowseightinstructionstobeexecutedfullyserial,partiallyserialorfullyparallel.

LargeregisterfileonTrimedia—Videoprocessingrequiresworkingwithalargedataset;alargeregisterfilepreventsoveruseofexpensiveloadandstoreinstructions.TriMediaprocessorTM3270hasaunifiedregisterfilewith12832‐bitregisters.

SpecificdomainISAinstructions—Notalltasksfoundinvideoprocessingcodecsareparallelizable,forexampleinH.264Context‐BasedAdaptiveBinaryArithmeticCoding(CABAC)intrinsicsequentialbehaviorcannotbeproperlyoptimizedwithSIMD.TheTriMediaISAisequippedwithseveralnativeinstructionstosimplifyCABACprogrammingtocompensateforthisdisadvantageandminimizesequentialexecution.TIC6000providesalsospecificdomaininstructionsdesignedtooptimizetheexecutionofimageprocessingkernels.

Fixed­pointarithmetic—OntheTIC6000processorsfixed‐pointarithmeticislesscomputationallydemandingthanfloating‐pointarithmetic,andthusasuitabledesignchoicetoincreasearithmeticprocessingspeed.

Predication—Bothfamiliesofprocessorsallowinstructionstobeexecutedconditionally(predication),thusreducingcostlybranching.

Delayslots—OntheTIC6000,forfixed‐pointinstructions,anumberofdelayslotsareavailable.Thenumberofdelayslotsisequivalenttothenumberofadditionalcyclesrequiredafterthesourceoperandsarereadfortheresulttobeavailableforreading:foramultiplyinstructionthisis1,foraloadthisis4,andforabranchthisis5.OnTriMedia,fivedelayslotsareprovidedonlyforbranchinstructions.

3.3.2 Lowpowerconsumption

ClockgatingandfrequencyscalingonTriMedia—TriMediaappliestwomainpowersavingtechniques:clockgatingandvoltage‐frequencyscaling.ThelatestTrimediaimplements70clockdomains,forexampleallstagesofallfunctionalunitsaregated.Thenormalsupplyvoltageis1.2VbuttheTriMediaguaranteesnormaloperationsat0.8Vatalowerfrequency.ThemaximumoperatingfrequencyfortheTM3270is350Mhz,ampleroomforscalingdownitsfrequencywhenprocessingtypicaltaskssuchasMP3decoding(only8Mhzneeded).

ClusteringonTIC6000—Ontheotherhand,theTIC600family,toavoidaslowandpower‐hungryregisterfile(read/writeportsfromeachregistertoeachofthe8FUs)andalargeforwardingnetwork,twodatapaths(i.e.clusters)areavailable.Thisallowshigherfrequenciesandlowerpowerconsumption.TriMedia’sregisterfileistwicethesizeoftheTIC6000andisunified.InthiswayTriMediadesignerschoosetosavememorybandwidthwithalargeregisterfileandTIC6000designerschoosetosaveonpowerconsumptionandtoreachhigherfrequencieswithasmallerdividedregisterfile.

MemoryAccess—OnTIC6000,4interleavedsingle‐portedmemorybanksassurelowerpowerconsumption.ThishowevercanleadtoreducedperformanceinaVLIWarchitecture:onlyoneaccesstoeachbankisallowedpercycle;iftwoparallelloadinstructionsarebothtryingtoaccessthesamebank,oneloadmustwait,resultinginamemorystall.OnTriMedia,lowpowerconsumptionisalsoaccomplishedwitha4‐waysetassociativecache.

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4 SDRprocessors:SODAandEVP

4.1 SODA

Remark:unlessotherwisespecified,theinformationinthissectionistakenfromthemainSODApaperbyYuanLinetal.[13]

4.1.1 Introduction

SODA(Signal‐processingOn‐DemandArchitecture)isa(proposed)SDRprocessorarchitecturedevelopedattheUniversityofMichigan.Itsmaindesigngoalsare:highperformance,energyefficiency,andprogrammabilitythroughacombinationoffeaturesthatincludesingle‐instructionmultiple‐data(SIMD)parallelism,andhardwareoptimizedfor16‐bitcomputations.

Theproposedarchitecturehasbeenimplementedon180nmprocesstechnologies,anditisprojectedtomeetthethroughputandpowerrequirementsofcurrentwirelessprotocols(seeFigure1)whenimplementedon65nm.

4.1.2 Architectureoverview

Overview

TheSODAsystemiscomposedof(seeFigure6):fourprocessingelements(PEs),ascalarARMcontrolprocessorandaglobalscratchpadmemory,allconnectedthroughasharedbus.

Figure6–OverviewofSODAmulti­coreDSParchitecture

ProcessingElement

EachPEconsistsof3pipelinesthatruninlockstep:awideSIMDpipeline,ascalarpipelineandanAGU(addressgenerationunit)pipeline.

• ThewideSIMDunitrunsmostofthecomputeintensivealgorithms(FFT,Viterbi,Turbodecoder,etc.).TheSIMDpipelineconsistsof32clusterswitha16‐bitdatapath(seeFigure7).Eachclustercontains1ALUandasimpleregisterfilewith2readportsand1writeport.Ashuffleexchangenetworkinterconnectstheclusters.

• ThescalarunitisusedtosupportmanyoftheDSPalgorithmsthatarescalarinnatureandcannotbeparallelized.Thescalarpipelineconsistsofone16‐bitdatapath.

• AnAGU(addressgenerationunit)pipelinehandlesDMAtransfersandmemoryaddresscalculationsforboththescalarandSIMDpipelines.

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TheSIMDShuffleNetwork(SSN)supportintra‐processordatamovements.Itcontainsashuffleexchangenetworkandaninverseshuffleexchangenetwork,whichallowstoefficientlyperformpermutationsonvectors,acommontaskinwirelesscommunicationalgorithms.

Figure7–ProcessingElementarchitecture

Controlprocessor

TheARMprocessorismainlyusedasasystemcontrollertohandleprotocols’controlcodeandstatetransitions.

Memory

Therearenocachestructures:boththelocalPEmemories(4KBscalar,8KBSIMD)andtheglobalscratchpadmemory(64KB)aremanagedbysoftwarethrougheachPE’sDMAcontrollertowhichalllocalandglobalmemoriesarevisible.

TheSIMDmemorycontainstwo512‐bitports(oneread,onewrite).Thescalarmemorycontainstwo16‐bitports(oneread,onewrite).

CommunicationsbetweenPEsareviascalarstreams,butintra‐PEcomputationsarevectoroperations.Therefore,supportforascalar‐vectorinterfacebetweenthescalarandSIMDpipelineisnecessary.ThisisshowninFigure6asWtoSandStoW.

4.1.3 Compilersupport

ItisclearthatheterogeneousmultiprocessorchipssuchasSODAprovidedifficultchallengesforprogrammersandcompilerstoefficientlymapapplicationsontothehardware.Especiallysincemanyoftheprojectedhigh‐performancefeaturesrelyonstaticscheduling.

Anewdataflowprogrammingmodel,calledSPIR(SignalProcessingIntermediateRepresentation),designedformodelingSDRapplicationshasbeenresearchedbyLinetal[14].Itactsasanintermediaterepresentationthatcanbeautomaticallygeneratedfromexistinghigh‐levellanguages(suchasC)throughacompilerfront‐end.ThegeneralideaisthatSPIRrepresentsataskgraphconsistingofasetofnodes(tasks,forexampleadescrambler)interconnectedwitharrows(dataflow).Eacharrowspecifiestheinputandoutputstreamratesforthesourceanddestinationnodes.Thispropertyallowsacompilertogeneratestaticexecutionschedules.

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4.2 EVP

Remark:unlessotherwisespecified,theinformationinthissectionistakenfromthemainEVPpaperbyVanBerkeletal.[16]

4.2.1 Introduction

EmbeddedVectorProcessor(EVP)isanapplicationspecificprocessordevelopedbyNXP.TheEVPwasdevelopedalmostexclusivelyforSDRapplicationsandisaimedmainlyatconsumerhandhelddevicessuchasPDA,SmartPhones,MobilePhones,etc.

EVPhasbeendesignedtoexecutethetypicalalgorithmsfoundinthemodemstage(see§2.2)inrealtimeandinapowerefficientmanner.EVPaccomplishesthiswithdataandinstructionlevelparallelism(vectorprocessingandVLIW)andbyprovidingapplicationspecificinstructions.

4.2.2 ArchitectureOverview

Figure8showsablockdiagramoftheEVParchitecture.Theprocessorconsistsofageneralscratchpadprogrammemory,aVLIWcontroller,anAddressCalculationUnit(ACU),avectorregisterfile,ascalarregisterfile,avectormemory,asetofvectorfunctionalunits(FUs),andasetofscalarfunctionalunits.Themainwordis16bits.

TheVLIWcontrollerdispatchesaVLIWinstructionoverthevariousvectorandscalarfunctionalunits.ThemaximumVLIW‐parallelismavailableequalsfivevectoroperationsplusfourscalaroperationsplusthreeaddressupdatesplusloop‐control.

ThevectorFUssupportSIMD,allowingfordataparallelism.TheSIMDwidthoftheEVPis16(256bits).ThisimpliesthattheEVPcanexecutethesameinstructionon16wordsof16bits,32wordsof8bitsor8wordsof32bits.

SomeofthevectorFUsareveryspecific:theMACunitprovidesforMultiply‐Accumulates,theshuffleunitcanrearrangetheelementsofsinglevector,theintravectorunitprovidesvectorspecificoperationssuchasdeterminingthemaximumelementofavector,thecodegenerationunitprovidessupportorCDMAspecificfunctionality(i.e.socalled“codechip”generation).

Figure8­EVPArchitecture

4.2.3 CompilerSupport

TheEVPcomeswithitsownlanguageandowncompiler.EVPprogramsarewritteninEVP‐CasupersetofANSI‐C.CprogramsaremappedexclusivelytothescalarunitsoftheEVP.ToexploittheVLIW,SIMD,andvectorparallelismitismandatorytousetheEVPlanguageextensionsandsomelibraries.ItisstillataskoftheprogrammertomanuallymaptheDSPbasebandalgorithmstotheir“vectorized”versioninEVP‐C.

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Furthermore,manualoptimizationisrequiredtoachieveefficientvectorizedcode.Asanexample,thecodeproducedbyaprototypeEVP‐CcompilerforaspecificFFTimplementationrequired25%morecyclesthanhand‐scheduledassemblycode.[16]

4.3 ComparingSODAandEVP

ThissectionwilldiscusswhycertaindesigndecisionswerechosenforbothSODAandEVP.

4.3.1 Designgoals

Asstatedin§2.1,themaindesigngoalsforanSDRprocessorarehighperformance,energyefficiency,andprogrammability.Thetablebelowsummarizesthetechniquesusedtoachievethis.Moredetailonthedifferenttechniquesisprovidedinthesubsequentparagraphs.

Unlessotherwisementioned,alltechniquesanddiscussionsapplytobothSODAandEVP.

Highperformance Energyefficiency Programmability

• Multipleparallelism

• VLIW• SIMD• Multiplecores(SODA

only)

• Nobranchprediction • VLIW/SIMD

• Hardwareoptimizedfor16‐bitfixed‐pointoperations

• Fixed‐pointoperations

• Scratchpadmemory • Nocache

• SpecialDSPinstructions • SpecialDSPinstructions

• SeparatedSIMDmemory

4.3.2 Wirelessprotocolcharacteristics

Wirelessprotocolsarecharacterizedbyanumberofspecificproperties,whichhaveanimportantimpactonthedesignofaDSPsystem.

• HighData­LevelParallelism—MostofthecomputationallyintensiveDSPalgorithmshaveabundantdatalevelparallelism(forexamplethe“searcher”inaW‐CDMAprotocol,canberepresentedby320‐widevectors),muchmorethaninstructionlevelparalellism.[13]Parallelismiselaboratedonin§4.3.3.

• 8to16­bitdatawidth—Mostalgorithmsoperateonvariableswithsmallvalues.Analysisoftwotypicalwirelessprotocolsshowsthatthereshouldbestrongsupportfor8and16‐bitfixed–pointoperations.32‐bitfixed‐pointoperationsandfloating‐pointsupportisnotnecessary.[13]

• Real­timerequirements—Strictreal‐timerequirementinwirelessprotocolsrequiresdeterministicarchitecturalbehaviour.Thereforefeaturessuchascaching,multi­threadingandpredictionarenotwellsuited.[13]

• Vectoroperations—Intravectoroperations(vectorreductions)andshufflingofdatawithinavectoriskeytoanumberofcommonalgorithms(e.g.FFT).Thereforespecific,powerandperformanceoptimal,supportfortheseoperationsshouldbeprovided.[16]Thisiselaboratedonin§4.3.4.

4.3.3 Parallelism

ThekeytoachievethehighperformancerequiredforSDRistomaximallyexploittheparallelismavailable.

SODAprovidesthreelevelsofparallelism:multiplecores(PEs),VLIWandSIMD.[13]

• Multiplecores—Periodicreal‐timedeadlinesrequirealgorithmstocomputewithdifferentdataratesanddifferentlatencies.Realizingthisforcomplexprotocolsusingasinglethreadedsystemistooexpensive(forexample,complexcontextswitchingsoftware).

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However,itisnecessarytosupportefficientconcurrentDSPalgorithmexecution.Theretomultiplecores,implementedasPEs,areused.(Eachprotocolpipelineisbrokenupintokernels,andeachkernelisassignedtoaPE.)Sincethetaskinthewirelessprotocolsanalysedcanbepartitionedinto4majortaskgroups,4PEshasbeenchosen.

• VLIW—Thethreepipelines–scalar,SIMDandAGU–canbeconsideredasanasymmetricVLIWpipeline(asymmetric,sincee.g.scalarinstructionscannotbescheduledontheSIMDpipelineandviceversa).Thescalarpipelineisnecessarybecausetherearemanysmall,importantscalaralgorithms.WideSIMDunitswouldbetooinefficientinsupportingthesescalarandnarrowSIMDoperations.

• SIMD—ThecomputationintensiveDSPalgorithmsinwirelessprotocolsusuallycontainoperationsonverywidevectors.Inaddition,vectorwidthsandstridesareknownatcompiletime.Althoughthismakesagoodfitforvectorarchitectures,theextrahardwaresupportfordynamicvectormanagementisunnecessary,asalldataoperationscanbestaticallyscheduled.ThisfavorsawideSIMD‐styleexecution.ThewidthoftheSIMDunitisnotchosentobe32clustersbyaccident.Itistheoptimalpowerconsumptionconfiguration,giventheestimatedcomputationrequirementof10GOPSperPE.Figure9mapsthepowerconsumptiontoSIMDwidth.Therequired10GOPScanbeachievedthroughanumberofSIMD/frequencycombinations,forexamplea2‐wideSIMDrunningat5GHz.Highfrequenciesrequireunrealisticdeeppipelines(indicatedby‘I’),andsufferfromhighpowerconsumption.

Figure9–AveragenormalizedpowerrequirementsofaPE(180nm)

EVPonlyprovidestwolevelsofparallelism:VLIWandSIMD.However,EVPdiffersinitsVLIWorganization:itcanexecutemultipletypesofwideSIMDoperationsinparallel.WhilethisprovidessupportforahigherdegreeofILP,italsorequiresamorecomplexregisterfile.BecausethereisverylimitedILPamongvectorcomputations(i.e.datalevelparallelismismuchmoreprevalentthaninstructionlevelparallelism),thisextralevelofparallelismdoesnotaddmuchtoperformance.[13]

TheEVPSIMDwidthisscalable,buthasbeensetto16forthefirstEVPprototype,labeledEVP16.[16]Theexactreasonofchoosing16isnotspecificaswasthecaseforSODA.Ofcourse,higherSIMDwidthwillprovideforhigherdataparallelism.

4.3.4 SpecialDSPinstructions

SODAcontainsspecialDSPinstructions,bothtooptimizeperformanceandpowerconsumption.ProvidedarespecialvectoroperationssupportedbytheSIMDshufflenetwork(forexample,thebutterflyoperationtoenhanceFFTperformance)andvectortoscalaroperations(forexample,determiningthemaximumvalueinavector).Multiply‐Accumulate(MAC)instructionsarenotprovidedbutinsteadhandledbyvectorlogicoperations(predicatednegation)sincemanyofthesemultiplicationoperationsarewith1bitvalues,consumingsignificantlylesspower.[13]

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EVPprovidesanumberofspecializedFUs(seealsoFigure8).TheshuffleunitprovidesfunctionalitysimilartoSODA’sSSN(SIMDshufflenetwork).TheintravectorunitprovidesfunctionalitysimilartoSODA’sspecialinstructionsforvectortoscalaroperations(forexampleitcanalsodeterminethemaximumvalueinavector).ThecodegenerationunitsupportsCDMA‘codechip’generation(acodechipisafundamentalunitoftransmissioninCDMA,awirelesschannelaccessmethod).Inasingleclockcycle16successivecomplexcodechipsaregenerated.Theunitisconfigurablefordifferentstandard(UMTS,GPS,etc.).ContrarytoSODA,theMACunitprovidessupportforMACinstructions.[16]

4.3.5 Other

Nobranchprediction—Branchpredictionisnotimplemented,becauseformostDSPalgorithmsthecorekernelsconsistofshallownestedloops.Instead,forSODA,aloopcounter‐basedbranchinstructionisavailable.[13]

Scratchpadmemory/nocache—Tomeettheneedforhighmemorybandwidthandlowpowerconsumption,anon‐chipscratchpadmemoryisusedwhichissmallandhencefast.Withnodatatemporallocality(streamingdata),cachestructuresprovidelittleadditionalbenefits,intermsofpowerandperformance,oversoftwarecontrolledscratchpadmemories.[13]

SeparatedSIMDmemory—BothSODAandEVPhaveadedicatedSIMDmemory.Ingeneraltwomemoriesconsumelowerpowerthanoneunifiedmemory.Inaddition,thisseparationallowsoptimizationoftheread/writeportsforitsintendeduse(inthecaseofSODA:512‐bitfortheSIMDmemoryand16‐bitforthescalarmemory).[13]

Powerconsumption—At180nm,SODA’spowerconsumptionis3W.Thisistoohighforembeddedmobiledevices(200mWisatypicalcellularphone’spowerbudgetforthephysicallayer).Scalingto65nmpredictsthepowerconsumptiontoaround250mW.[13]NopracticalcomparabledataisgivenfortheEVP’spowerconsumption,althoughEVPliteraturesomewhatunclearlymentionsthatrunningcertainUMTSprotocolsontheEVPresultsinapowerconsumptioncloseto1W(at90nm);otherprotocolsperformbetter.[16]

BothEVPandSODAliteraturedoesnotmentionsupportunalignedloads,forwardingandcompression,whichseemstoindicatethatitisnotsupported.

4.4 FinalthoughtsonSODAandEVP

ItshouldbeclearfromthepreviousoverviewthatkeytoachievingtheperformancerequiredforSDRliesinexploitingasmuchaspossibletheavailableparallelism.How,then,canbothSODAandEVPreachthisperformance,giventhatSODAismuchbetterequippedforexploitingparallelism(runningatapproximatelythesamefrequency)?SODAinadditionnotonlyhasfourcores,itsSIMDpipelineis2timeswider.

AresponsefrombothaSODAandEVPdevelopertothissamequestionclarifiesanumberofthings:

• BothcitethedifferenceinVLIWorganization—theEVPcanexecutemultipletypesofwideSIMDoperationsinparallel.[15][18]

• TheEVP‘outsources’anumberofalgorithmstootherprocessors(suchastheViterbidecoding),whereasSODAperformsthesefunctionalitiesonchip(i.e.ondesignatedPEs).[15]

• ForEVPtocatchupwithnewandmoredemandingprotocols,multiplecoresareindeednecessary.[18]

• Finally,SDRisarelativelynewresearchtopic.Itislackingstandardizedbenchmarks,andeachwirelessprotocolhascountlessnumberofdifferentimplementationsandconfigurations.Thesedifferentconfigurationsandimplementationscanaffectperformance/powersignificantly.Hence,itisveryhardtocomparetwoseparateddevelopedandtestedprocessors.[15]

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5 Literature

5.1 General[1] Wikipedia[2] JasonFritts,WayneWolfandBeddeLiu,Understandingmultimediaapplication

characteristicsfordesigningprogrammablemediaprocessors,1999

5.2 TriMedia

TheTriMediasectionwasbasedmainlyonVanDeWaerdt’spaper.Hedesignedthisprocessorforhisthesisthereforehewasabletoexplainthoroughlymanytechnicaldetailswithenoughclarityandtothepoint.Theremainingsourceswereusedmainlytoseethe“bigpicture”oftheTriMedia,theyarelesstechnicalandmoreconcernedwithconsumerapplicationsandbusinessaspects.[3] VandeWaerdt,etal.TheTM3270Media­Processor.Proceedingsofthe38thAnnual

IEEE/ACMInternationalSymposiumonMicroarchitecture(MICRO’05).2005[4] HoogerbruggeJanetal.InstructionSchedulingforTriMedia.PhilipsResearchLaboratories.[5] BoresSignalProcessing.TriMediaOverview.

http://www.bores.com/courses/tm_overview/index.htm.Lastupdated:March2007.[6] VandeWaerdt,TheTM3270Media­processor,October2006,TUDelft,ISBN90‐9021060‐1,

PhDThesis

5.3 TIC6000

TexasInstrumentsprovidesextensivedocumentationontheC6000platformandthedifferencesbetweenspecificgenerations.Thesedocumentsareingeneralverycomplete,however,informationonwhycertainfeaturesareimplementedarenotincluded.[7] TexasInstruments,TMS320C6000CPUandInstructionSetReferenceGuide,SPRU189d,July

2006[8] TexasInstruments,TMS320C6000TechnicalBrief,SPRU197d,February1999[9] TexasInstruments,TMS320C64xTechnicalOverview,SPRU395b,January2001[10] TexasInstruments,TMS320C62xDSPCPUandInstructionSetReferenceGuide,SPRU731,July

2006[11] Internetforumpost“CcompilersforTITMS320DSPs”,2005‐3‐02,

http://www.dsprelated.com/showmessage/30734/1.php[12] JanPartheyandRobertBaumgartl,PortingGCCtotheTMS320­C6000DSPArchitecture,

AppearedintheProceedingsofGSPx’04,SantaClara,September2004

5.4 SODA

Thepaper“SODA,ALow­powerArchitectureForSoftwareRadio”seemsverycompleteandthorough,discussingtheSODAarchitectureaswellastherationalebehindthedifferentdesigndecisions,whilealsosettingthemofagainstthealternatives.Itwaslackinghoweverindiscussinghowsuchacomplexarchitecturecanbereasonablyprogrammed.[13] YuanLinetal.SODA,ALow­powerArchitectureForSoftwareRadio.InProceedingsofthe

33rdAnnualInternationalSymposiumonComputerArchitecture,2006.[14] YuanLinetal,HierarchicalCoarse­grainedStreamCompilationforSoftwareDefinedRadio,In

CASES’07,2007[15] PersonalemailcommunicationwithKeesMoerman,2008‐12‐16.

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5.5 EVP

TherewasaverylimitedamountofinformationavailableintheWebontheEVP.ThissectionwasbasedmainlyonVanBerkel’spaper.ThispaperdoesnotfocusontheEVPbutonSDRapplicationsonvectorprocessorsandofferstheEVPasanexample;itdoesnotexploreindepthitsarchitecturalfeatures.Moerman’sarticleoffersabriefbusinessorientedviewoftheEVPcapabilitiesandapplications.[16]VanBerkeletal.VectorProcessingasanEnablerforSoftware­DefinedRadioinHandheld

Devices.EURASIPJournalonAppliedSignalProcessing2005.[17]Moerman,Kees.Embeddedvectorprocessorisonewaytotunesoftware­definedradios.

WirelessNetDesignLine.http://www.wirelessnetdesignline.com/202403292;jsessionid=5UPHUZ4YXPVRYQSNDLRSKHSCJUNN2JVN?pgno=1.Lastupdated:October2007.

[18] PersonalemailcommunicationwithKeesMoerman,2008‐12‐16.