摩根士丹利-人工智能供應(yīng)鏈跟蹤-動態(tài)發(fā)展-unlocked

MorganstanleyRESEARCH

February19,202409:00PMGMT

AsiaTechnology|AsiaPacific

AISupplyChainTracker–

DynamicDevelopments

GPUdesignupgrades,offeringexpansionandincreasingsupplychainengagementarepushingforwardAItechdevelopments.

AIdownstreamsupplychain:

?OurchecksindicateNVDAplanstomovetheB100GPUproductionscheduletomid-2024withB100GPUmoduleshipmentrolloutinJulyandmass

productioninAugust.Currentordersfor3Q24are~50-60Kunits.

?OurchecksindicatethatUnimicronhasbeenapprovedasaqualifiedNvidiaB100ABFsubstratevendor,secondtoIbiden.However,ourchecksindicatethatitsyieldrateremainslowerthanIbiden,sothisismoreofa+ve

sentimentforthestockbutnotforearnings(link).

?Giga-Byte'sJanrevenueat~NT$16.9bn(+32%m/m,+106%y/y)impliesthatitlikelydid800-900unitsofAIserversduringthemonth,whichissimilartoOctandNov.

?LambdaraisedUS$320mnSeriesCfundingonFeb15.ThisnewfundingwillaccelerategrowthforitsGPUcloudandensureAIengineeringteamshaveaccessto"thousands"ofNvidiaGPUswithhigh-speedNvidiaQuantum-2

InfiniBandnetworking.

AIsemisupplychain-AIASIC/GPU/Memory

?ReutersreportedNVIDIAisbuildingagroupworkingoncustomchipsfor

hyperscalers.JoeMoorebelievesthisispartofNVIDIA’snewstrategyto

focusonmarketshareandpreventgrowthofcompetition(link).Joedoesn’tthinkit'sdirectlynegativetoMarvellbecauseit'daffirmthegrowthpotentialofASICandpartofthepointofASICistodiversifyawayfromNVIDIA.OurglobalviewisGPUcanstilldominateAItrainingdemandgivenNVIDIA’sfastnewproductramp,whileASICdesignservices,suchasAlchip,canstillgrownicelygiventheirexposuretoinferencechipsandAIsemistart-ups.

?AddingsalesofalternativecloudAIsemis(e.g.,ASIC),cloudAIsemiTAMisalreadyUS$100bnin2024.Foralonger-termperspective,weintroduceournewAIsemidemandmodeltogaugethelong-termASICdesignserviceTAM,estimatedat~US$30bnby2030(~3xvs.2024).

?MaeilBusinessNewsKoreareportedthatTSMCandSKHynixhaveformedtheso-calledAISemiconductorAlliance.AccordingtoTrendForce,HBM4

(expectedtodebutin2026)willbethefirsttousea12nmlogicprocess

technologyforitsbasedie,whichfoundries,notDRAMmakers,willnow

make.WethinkthisdemonstratesTSMC’stechnologyleadershipinthe

futureAIchipadvancedpackaging,andpositivereadacrosstoASMPT,whichiscurrentlysupplyingbothSKHynix(HBM)andTSMC(logic)withTCBtools.

Update

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Morganstanley

RESEARCH

Update

2

Keyupdates

?WehaveupdatedAIGPUdemand(NVIDIA’sforecast)andsupply(CoWoS)inExhibit6andintroducedASICdesignservicemarketsizeatUS$30bnin2030(seeExhibit10).

?WehaveupdatedNvidiaserversupply/demandshareanalysisbasedonJoeMoore'srecentlyupdatedNvidiaforecastsinExhibit25toExhibit30.

(kwpm)

Non-TSMC(UMC/SPIL/Others)TSMC

Source:Companydata,MorganStanleyResearch(e)estimates

Exhibit3:TSMC'sCoWoSconsumptionbycustomer

TSMCCoWoScapacitydemandbykeycustomer

250

200

100

50

020222023e2024e

150

100

50

0

Source:TrendForce,MorganStanleyResearch(e)estimates

Exhibit4:HBMdemandisnearlytwicevs.2023

HBMdemand(kGB)

700,000

600,000

500,000

400,000

300,000

200,000

100,000

0

2023e2024e

NVIDIAAMDHabanaGoogleAWSTeslaMicrosoftChineseGPU/ASIC

2023e2024e

HynixSamsungMU

Update

Supply-chainTracker–AISemis

Majorsupplybottleneck–CoWoScapacitytrend

Exhibit1:CoWoScapacityexpansionbyvendor

Exhibit2:HBMTSVcapacityalsosettodoublein2024

CoWoSsupplycapacitybreakdown

HBMTSVcapacity(kwpm)

35

30

25

202715

1011

1035

20222023e2024e

250

200

150

Source:TrendForce,MorganStanleyResearch

NVIDIABroadcomAMDXilinxAWS+AlchipMarvellGUCOthers

Source:Companydata,MorganStanleyResearch(e)estimates

Exhibit5:WhatisCoWoS?ChiponWafer(interposer)on

Substrate

Source:TSMC

MorganStanleyResearch3

Morganstaney

RESEARCH

Update

Exhibit6:

NVIDIAAIGPUrevenueimpliedCoWoSdemand–Doublebookingatfoundries?

CY23eCY24eCY25eCY26e

NVIDIArevenueforecastimpliedGPUvolume

NVIDIAAIGPUrevenue(US$mn)

37,432

70,593

72,065

83,843

Y/Y%

177%

89%

2%

16%

AIGPUASP(US$)

25,403

28,354

30,656

35,313

AIGPUvolume(kunits)

1,474

2,490

2,351

2,374

Y/Y%

30%

69%

-6%

1%

CoWoSbookingsimpliedAIGPUvolume

1,600

4,000

GPUchipcostcalculation

Waferfrontendcost

#ofgrossdieperwafer

65

64

59

44

Productionyield

60%

65%

70%

70%

#ofgooddieperwafer

39

42

41

31

TSMCblendedwaferpriceforNVIDIAAIGPU

16,000

18,000

18,000

20,000

WaferdierevenuetoTSMCperchip

410

432

435

645

Advancedbackendcost

#ofchipperCoWoSwafer

29

28

25

18

CoWoSwaferpriceforNVIDIAAIGPU

6,000

8,000

8,500

9,000

CoWoSrevenuetoTSMCperchip

209

286

347

502

Chipprobe(wafertest)revenuetoTSMCperchip

199

314

381

552

TotalrevenuetoTSMCperchip

818

1,031

1,163

1,699

NVIDIAAIGPUimplicationstoTSMC

DemandforTSMCCoWoScapacity

kwaferperannum

51

89

96

132

kwaferpermonth

DemandforTSMC4nm/7nmcapacity

4

7

8

11

kwaferperannum

38

60

57

77

kwaferpermonth

3

5

5

6

RevenuecontributiontoTSMC(US$mn)

1,205

2,568

2,733

4,035

Y/Y%

65%

113%

6%

48%

Revenuecontribution%ofTSMC

1.7%

3.0%

2.7%

3.4%

Source:Companydata,MorganStanleyResearch(e)estimates

4

US$mn

Morganstanley

RESEARCH

Update

AIsemialternatives–Customchips(ASIC)

Exhibit7:Datacentercompanies'customAIchipstrategy

Firstofficial

announcementforAIASIC

AIASICproject

ASICpartners

ASIC'sbenefits

vs.merchantsolutions

Chipsourcingstrategies

Google

2016

TPU

Broadcom

2-3xgreaterenergyefficiency

Googlestartedtoincreasein-housecustomchip(TPU)adoptionsince

2017.Currently,mostoftheinternaltrainingandinferenceworkloadsarenowcompletedbyTPUs,whileNVIDIA'ssolutionsarealsoavailablefor

Google'scloudcustomers.

AWS

2018

Inferentia

Trainium

Alchip,Marvell

50%greater

performanceperwatt

AWSusesmultiplesourcesofchipstosupportcustomers'differentworkloads.Forexample,customASICs(Trainium/InferentiaAIchips,GravatonCPU)andGPCPU/GPUs(Intel,NVIDIAandAMD).

Tesla

2018

D1(Dojosupercomputer)FSD(on-carAD/ADAS)

Alchip,Samsung

33%ofcostsavings

Teslastartedtoincorporateitsin-housecustomchips(D1andFSD)since2019toreplaceNVIDIA'sgeneral-purposesolutions.

Microsoft

2023

Maia100AIAcceleratorCobalt100CPU

GUC

40%performance

improvement

Microsoft'sAthenaprojectadoptsAIsolutionsfrommultiplesources,suchasin-houseASIC(Maia100AIAccelerator&Cobalt100CPU),

AMD's/NVIDIA'sGPUs,d-Matrix'sAIchip,etc.Weexpectitsowncustomchipstoentervolumeproductionin2024.

Meta

2023

MTIA

MSVP

N/A

2xperformance

Metausesin-houseASICforAIinferenceworkload,butstickswithNVIDIA'sA100foritstrainingsupercomputer.Itscustomaccelerator(MTIA)adoptsRISC-Vcores.

Source:Companydata,MorganStanleyResearchestimates

willrepresent

WeestimatecustomAIASIC

~US

Exhibit9:

Exhibit8:WeexpectcustomAIchips(ASICs)tooutgrow

$11bnof

marketvaluein

2024e

CustomAIASICvaluemix,2024e

MicrosoftMeta(MTIA)

(AthenaASICs)$50mnOtherAIASICs

GPUsandpotentiallytakeupto30%ofthecloudAIsemimarket

infourtofiveyears

Cloudsemibreakdown:GeneralAIvs.CustomAI

250,000

AlibabaT-Head$100mnN/$159mn$400mn

200,000

$800mn-

Tesla(Dojo&FSD)

150,000

AWS

(Inferentia&

Trainium)

100,000

$2,000mn

70%

50,000

Google(TPU)$7,500mn

0

202120222023e2024e2025e2026e2027e

CustomAI

General-purposeAI(GPU,FPGA,merchantAI)

Source:Companydata,MorganStanleyResearch(e)estimates

Source:Morgan

StanleyResearch(e)estimates

Research

5

MorganStanley

US$mn

US$mn

Morganstanley

RESEARCH

Update

Exhibit10:Weexpectbackenddesignservicestobecomemoreimportantassystemhousesbuilduptheirownchipfront-end

designteams

Exhibit11:AIprojectsbydesignservicecompaniescouldbeanimportantdriverforthefoundryindustry

Foundryrevenue:DesignserviceCloudAIprojects(basecase)

CloudAIsemis:Customvs.General-purpose(basecase)

250,000

200,000

150,000

100,000

50,000

0-202120222023e2024e2025e2026e2027e2028e2029e2030e

20,000 18,000 16,000 14,000 12,000 10,000 8,000 6,000 4,000

2,00-

202120222023e2024e2025e2026e2027e2028e2029e2030e

CustomAI(ASIC)GeneralAI(e.g.,GPU,FPGA)

Source:Companydata,Gartner,MorganStanleyResearch(e)estimates

Source:Companydata,Gartner,MorganStanleyResearch(e)estimates

Exhibit12:

MajorcustomAIchipprojects

Source:Google,AWS,Meta,Intel,Tesla

6

Google

TPUv

4

TSMC7nm

275

8,800

400

AMD

MI300

TSMC5nm

383

12,256

1,017

146

12.05

Yes

IntelHabana

Gaudi2

TSMC7nm

?

?

768

?

?

?

NVIDIA

A100

TSMC7nm

312

9,984

826

54

12.09

Yes

Processnode

TensorFloat16(TFLOPS)

TPP("TotalProcessingPerformance")

Diesize(mm^2)

Transistorcount(bn)

PD("PerformanceDensity")

Exceedingthreshold?

22.00

Yes

Morganstaney

RESEARCH

Update

Whatare"TPP"and"PD"?

"TotalProcessingPerformance"("TPP")is2x"MacTOPS"x"bitlengthoftheoperation",

aggregatedoverallprocessingunitsontheintegratedcircuit.Forexample,NVIDIA'sA100

TPP=2*312*16=9,984.BelowisadetailedexplanationofTPP:

?2x:Itisbasedonindustryconventionofcountingonemultiply-accumulate

computationastwooperationsforpurposeofdatasheets.

?MacTOPS:ThetheoreticalpeaknumberofTOPS(TeraOperationsPerSecond)for

multiply-accumulatecomputation.

?Bitlengthoftheoperation:Itisthelargestbit-lengthoftheinputstothe

multiply-accumulate.

?AggregatetheTPPsforeachprocessingunitontheintegratedcircuittoarriveata

total(mainlyforchipletdesigns).

"PerformanceDensity"("PD")is"TPP"dividedby"applicablediearea,"whichismeasuredin

millimeterssquaredandincludesalldieareaoflogicdiesmanufacturedwithaprocess

nodethatusesanon-planartransistorarchitecture.Forexample,NVIDIA'sA100PD=

9,984/826=12.09.

Exhibit13:SpeccomparisonofmajorAIGPUsandASICs

NVIDIA

L40S

TSMC5nm

362

11,584

609

76

19.02

Yes

Source:Companydata,MorganStanleyResearch.Note:TPPandPDcalculationsarebasedonBIS'slatestrulings.

Exhibit14:IntelsaysthatHabana'sGaudi2hascomparableAIcapabilitywithNVIDIA's

A100(80GB)GPU

Source:Intel

MorganStanleyResearch7

AWS

5%

Habana

1%

Update

2024AIsemi

waferrevenueandHBMdemandcalculation

Exhibit15:HBMconsumptionin2024e–Upto640mnGB

TotalHBM

TotalHBMsizeHBM

HBMchipunitsHBMvendordemand

(GB)generation

(kGB)

AIGPU(2024e)

CoWoScapacity

allocation

(kwafers)

AIchipvendorProductname

Implied

shipments(k)

Chipsper

CoWoSwafer

HBMchip

density(GB)

NVIDIA

H100

B100

130

20

29

14

3,770

280

16

25

5

8

80

200

HBM3

HBM3e

Hynix

Hynix/Micron/Samsung

301,600

56,000

AMD

MI300

25

12

300

24

8

192

HBM3

Samsung

57,600

Habana

Gaudi3

3

30

81

16

6

96

HBM2e

Samsung

7,776

AIASIC(2024e)

Google

TPUv5training

TPUv5inference

30

30

30

50

900

1,500

16

16

6

4

96

64

HBM2e

HBM2e

Samsung

Samsung

86,400

96,000

AWS

Inferentia2

Trainium2

17

7

20

15

340

105

24

24

2

4

48

96

HBM2e

HBM3

Samsung

Samsung

16,320

10,080

Tesla

Dojo1

FSD

NA

NA

NA

NA

300

1,600

32

NA

5

NA

160

NA

HBM2e/HMB3

NA

Samsung

NA

1,920

-

Microsoft

Maia100

0.3

29

8

16

4

64

HBM2e

Samsung

520

ChineseGPU/ASIC

Total

ChineseGPU/ASIC

5

267

20

100

9,344

16

4

64

na

Samsung

6,400

640,616

Source:Companydata,MorganStanleyResearch(e)estimates

Exhibit16:HBMconsumptionin2024e–NVIDIAtobethelargestcustomer

Chinese

GPU/ASIC

1%

TeslaMicrosoft

0%0.1%

AMD

11%

NVIDIA

66%

Google

16%

Source:Companydata,MorganStanleyResearch(e)estimates

Exhibit17:AI

computingwaferconsumptionin2024e–UptoUS$3bnrevenue

Wafer

consumption

(kwafers)

Waferrevenue

TAM(US$mn)

Computedie

units

Waferprice

(US$)

Implied

shipments(k)

Computedie

size

Chipsper

CoWoSwafer

Geometry

AIchipvendor

Productname

CoWoScapacity

allocation

(kwafers)

3,770

280

300

81

1,606

224

175

47

18,000

18,000

20,000

20,000

20,000

20,000

11,000

20,000

11,000

11,000

20,000

11,000

29

14

12

30

H100

B100

MI300

Gaudi3

TPUv5training

TPUv5inference

Inferentia

2

Trainium

2

Dojo

1

FSD

Maia100

ChineseGPU/ASIC

130

89

12

9

2

814

700

110

768

1

2

8

1

4nm

4nm

5nm

5nm

5nm

5nm

7nm

5nm

7nm

7nm

5nm

7nm

AIGPU(2024e)

NVIDIA

20

25

3

AMD

Habana

30

30

50

20

15

NA

NA

29

20

900

1,500

340

105

300

1,600

8

100

9,344

325

325

700

700

645

10

17

8

5

6

14

0.2

4

177

199

331

83

93

67

152

4

44

3,060

1

1

1

2

1

1

1

1

AIASIC(2024e)

Google

30

17

AWS

7

NA

NA

0.3

5

267

Tesla

300

700

1,000

Microsoft

ChineseGPU/ASIC

Total

Source:Companydata,MorganStanleyResearch(e)estimates

8

(NT$mn)

(NT$bn)

(NT$mn)

Tesla

7%

Google

17%

AWS

6%

Habana

2%

AMD

6%

M

or

st

ey

an

gan

RESEARCH

Update

Leading-edgewafer

Exhibit18:

consumptionbycustomersin2024e

Meta

0.1%

Microsoft

1.2%

ChineseGPU/ASIC

1%

NVIDIA

60%

Research(e)estimates

Source:

Companydata,MorganStanley

Monthlysales

chain

of

AI

Taiwan's

semisupply

enablers

KYECandTSMC–

Y/Yperformance

AIupstream

KeyAI

20:Key

Exhibit19:

Exhibit

upstreamenablers:Alchip,

Y/YPerformanceofupstreamAIenablers

Monthlysales

Monthlysalesof

upstreamAIenablers

170%

260

240

220

200

4,000

120%

3,500

70%

3,000

20%

2,500

-30%

180

160

140

120

2,000

Jul-22Aug-22Sep-22Oct-22Nov-22Dec-22Jan-23Feb-23Mar-23Apr-23May-Jun-23Jul-23Aug-23Sep-23Oct-23Nov-23Dec-23

23

1,500

KYEC(AIGPUFinalTest)

TSMC(AIChipManufacturing)

Alchip(AIASIC)

1,000

500

Source:Companydata,TEJ,MorganStanleyResearch

Jul-22Sep-22Nov-22Jan-23Mar-23May-23Jul-23Sep-23Nov-23

Alchip(AIASIC)

KYEC(AIGPUFinalTest)

TSMC(AIChipManufacturing;RHS)

Research

Source:Companydata,TEJ,MorganStanley

9

Research

MorganStanley

10

US$mn

1Q14

3Q14

1Q15

3Q15

1Q16

3Q16

1Q17

3Q17

1Q18

3Q18

1Q19

3Q19

1Q20

3Q20

1Q21

3Q21

1Q22

3Q22

1Q23

3Q23

1Q24e

3Q24e

1Q25e

3Q25e

Morganstaney

RESEARCH

Update

MajorAIGPUvendors–NVIDIAsalesandinventorytrend

Exhibit22:NVIDIA'sinventorydays/level

Exhibit21:GeneralpurposeAIchipquarterlyrevenue

Datacenter/HPCsemirevenue:NVIDIA+AMD/Xilinx

300%250%200%150%100%50%

0%

-50%

30,000

25,000

20,000

15,000

10,0