メルカリ写真検索における Amazon EKS の活用事例と プロダクトにおけるEdgeAI technologyの展望

AWSLoftで行われた AWS Containers talk with Mercari で使用した資料です
https://awscontainertalkwithmercari.splashthat.com/

Transcript

1. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
   ϝϧΧϦࣸਅݕࡧʹ͓͚Δ Amazon EKS ͷ׆༻ࣄྫͱ

   ϓϩμΫτʹ͓͚ΔEdgeAI technologyͷల๬
   !1
   גࣜձࣾϝϧΧϦ தՏ ޺จ
   

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2. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
   தՏ ޺จ
   • 2017೥7݄ೖࣾ
   • ॴଐ͸SRE→AI/MLνʔϜ
   • σόΠευϥΠό։ൃ͔ΒϑϩϯτΤϯυ
   ։ൃ·Ͱ΍ΔԿͰ΋԰
   Twitter: hnakagawa14
   GitHub: hnakagawa
   !2
   ࣗݾ঺հ
   

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3. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
   Introduction
   !3
   

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4. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
   What is ࣸਅݕࡧ
   • ࣸਅݕࡧͱ͸ɺ͍ΘΏΔը૾ݕࡧػೳ
   • ΞϓϦ͔ΒࣸਅΛݩʹ঎඼Λݕࡧ͢Δ
   • ঎඼໊Λ஌Βͳͯ͘΋ը૾͔Β঎඼Λݕࡧ
   Ͱ͖Δ
   !4
   ಈըϦϯΫ: https://youtu.be/kTni8EvOCgI
   

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5. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
   جຊతͳࣸਅݕࡧͷ࢓૊Έ
   !5
   Deep Neural Networks
   (DNN)Λ࢖༻ͯ͠঎඼ը૾
   ͔Βಛ௃ϕΫτϧΛऔಘ
   औಘͨ͠ಛ௃ϕΫτϧΛ
   Approximate Nearest
   Neighbor Index(ANN Index)
   ʹ௥Ճͯ͠ը૾indexΛߏங
   ݕࡧ࣌ʹ͸ಉ͘͡঎඼ը૾͔Β
   DNNΛհͯ͠ಛ௃ϕΫτϧΛऔ
   ಘ͠ɺANN Index͔Βݕࡧ
   2 3
   1
   

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6. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
   What is Kubernetes
   • KubernetesʢҎԼk8sʣͱ͸Φʔϓϯιʔε
   ͷίϯςφɾΦʔέετϨʔγϣϯγες
   Ϝ
   • k8sʹ͸Custom Resource Definitionͱݺ͹
   ΕΔಠࣗͷϦιʔεΛఆٛͰ͖Δػೳ͕͋
   Γɺ։ൃऀ͸ͦͷػೳΛհͯ͠k8sͷػೳΛ
   ֦ுͰ͖Δ
   • Amazon Elastic Container Service for
   Kubernetes (Amazon EKS) ͱ͸k8sͷϚω
   ʔδυɾαʔϏεɺίϯτϩʔϧϓϨʔϯ
   ͷ؅ཧΛߦͬͯ͘ΕΔ
   !6
   

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7. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
   What is Custom Resource Definition
   • Custom Resource DefinitionʢҎԼCRDʣͱ
   ͸ಠࣗʹϦιʔεΛఆٛͰ͖Δk8sͷػೳ
   • CRDɾϦιʔεͱɺΧελϜɾίϯτϩʔ
   ϥͰߏ੒͞ΕΔ
   • ΧελϜɾίϯτϩʔϥ͕CRDɾϦιʔε
   ͷϥΠϑαΠΫϧ/ঢ়ଶʹԠͯ͡Ϋϥελͷ
   ঢ়ଶΛίϯτϩʔϧ͢Δ
   !7
   

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8. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
   ML Platform Lykeion
   ࣸਅݕࡧ͸Lykeionͱݺ͹ΕΔ಺੡ͷML Platform্
   ʹߏங͞Ε͓ͯΓɺԼهͷػೳ͸Platformଆͷػೳ
   Λ࢖༻͍ͯ͠Δ
   !8
   • Training/Serving CRD & ΧελϜίϯτϩʔϥ
   • ίϯςφϕʔεɾύΠϓϥΠϯ
   • Training/Serving ίϯςφΠϝʔδɾϏϧμʔ
   • ϞσϧɾϨϙδτϦ
   

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9. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
   Architecture
   !9
   

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10. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    Architecture֓ཁਤ
    !10
    S3
    EKS
    

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11. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    1.TrainingɾϦιʔεͷ࡞੒
    !11
    S3
    EKS
    

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12. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    TrainingɾϦιʔεͷ࡞੒
    • Training custom resourceΛCronJob͕࡞੒
    • ΧελϜɾίϯτϩʔϥ͕CRDɾϦιʔε
    Ͱઃఆ͞ΕͨίϯςφϕʔεɾύΠϓϥΠ
    ϯΛ࣮ߦ
    • ࣮ߦ͢Δόον୯Ґͱͯ͠͸Hourly, Daily,
    Monthly͕ଘࡏ
    !12
    

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13. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    ίϯςφϕʔεɾύΠϓϥΠϯ
    • ֤޻ఔΛݸผͷίϯςφɾΠϝʔδͰ࣮ߦ
    • ϥΠϒϥϦͷґଘؔ܎ͳͲ؀ڥφΠʔϒͳMLύΠϓϥΠϯͷ໰୊Λղܾ
    • ύΠϓϥΠϯDAG͸YAMLͰهड़
    • ֤޻ఔͷೖग़ྗ͸Persistent VolumeʢҎԼPVʣΛհ͢
    !13
    

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14. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    Batch Execution as Custom Resource
    • શͯͷόον࣮ߦ৘ใ͕CRDɾϦιʔεͱͯ͠
    k8s্ʹ࢒Δ
    • ಉ͡ॲཧΛ࠶࣮ߦग़དྷΔͨΊɺόονͷ࠶࣮ߦ
    Λ൐͏ো֐෮چ࡞ۀ͕༰қ
    !14
    

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15. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    2.ը૾ͷμ΢ϯϩʔυ
    !15
    S3
    EKS
    

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16. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    ը૾ͷμ΢ϯϩʔυ
    • Amazon S3্ʹଘࡏ͢ΔϝϧΧϦɾΠϝʔδετΞ͔Β঎඼ը૾Λμ΢
    ϯϩʔυ
    • ύΠϓϥΠϯ্΋ͬͱ΋͕͔͔࣌ؒΔ޻ఔʢը૾਺͕๲େͳͨΊ)
    • ͦͷͨΊPVʹҰఆظؒΩϟογϡ͢ΔࣄʹΑͬͯ࠶ΠϯσοΫε͕
    ඞཁͳ࣌ʹ͸ૉૣ͘ύΠϓϥΠϯΛճͤΔΑ͏ʹ͍ͯ͠Δ
    • PVͷ࣮ମ͸ Amazon EBS
    !16
    

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17. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    3.ΞηοτͷΞοϓϩʔυ
    !17
    S3
    EKS
    

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18. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    ΞηοτͷΞοϓϩʔυ
    • ύΠϓϥΠϯͷ੒Ռ෺Ͱ͋Δಛ௃ϕΫτϧͱANN IndexΛϞσϧɾϨϙδτϦʹอଘ
    • શͯͷ੒Ռ෺͸όʔδϣϯ؅ཧ͞Εͨঢ়ଶͰอଘ͞ΕΔ
    • ϞσϧɾϨϙδτϦ͸GCS্ʹߏங
    !18
    

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19. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    4.ServingΠϝʔδͷϏϧυ
    !19
    S3
    EKS
    

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20. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    ServingΠϝʔδͷϏϧυ
    1. ϞσϧɾϨϙδτϦΛImage Builderͱݺ͹ΕΔdaemon͕؂ࢹ
    2. ৽͍͠Serving͢΂͖Ϧιʔε͕௥Ճ͞ΕΔͱࣗಈͰServingίϯςφɾΠϝʔδΛϏϧυ
    • ίϯςφɾΠϝʔδ͸શͯͷANN Index౳ͷαʔϏϯάʹඞཁͳϦιʔεΛશؚͯΜͰ͍Δ
    3. Ϗϧυ͞ΕͨίϯςφɾΠϝʔδΛίϯςφɾϨδετϦʹϓογϡ
    !20
    

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21. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    5.ServingɾϦιʔεͷ࡞੒
    !21
    S3
    EKS
    

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22. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    ServingɾϦιʔεͷ࡞੒
    • Image Builder͸ίϯςφɾΠϝʔδΛϏ
    ϧυͨ͋͠ͱɺServingΧελϜɾϦιʔ
    εΛ࡞੒
    • ServingΧελϜɾίϯτϩʔϥ͸CRDɾ
    ϦιʔεͷઃఆΛݩʹඞཁͳ
    DeploymentɺService౳Λ࡞੒
    • ຊγεςϜͰ͸ߏங͞ΕͨANN IndexΛ
    ݸผͷIndexαʔϏεͱͯ͠σϓϩΠ
    !22
    

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23. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    6.αʔϏεɾσΟεΧόϦ
    !23
    S3
    EKS
    

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24. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    αʔϏεɾσΟεΧόϦ
    • Ϋϥελ্ʹଘࡏ͢ΔIndexαʔϏεΛ
    k8sΛհͯࣗ͠ಈతʹऔಘ͢Δ
    • ͳΔ΂͘େ͖ͳཻ౓ͷIndexΛ࢖༻͢ΔΑ
    ͏ɺҟͳΔظؒɾཻ౓ͷIndexαʔϏε
    (Hourly, Daily, Monthly) Λࣗಈతʹ૊Έ߹
    ΘͤΔ
    • REST <-> IndexαʔϏεؒͷϓϩτίϧ
    ͸gRPCΛ࢖༻
    !24
    

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25. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    ֓ཁਤͷৼΓฦΓ
    !25
    S3
    EKS
    

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26. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    Conclusion
    !26
    

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27. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    ࣸਅݕࡧͷόοΫΤϯυɾΠϯϑϥ
    1. ίϯςφɾϕʔεͷ࠶ݱੑͷߴ͍γεςϜ
    2. k8sͷCRD/ΧελϜɾίϯτϩʔϥ΍αʔϏεɾσΟεΧόϦ౳ͷػೳΛ׆༻
    3. Batch Execution as Custom Resource౳ɺML PlatformͰ࣮ݱ͞Ε͍ͯΔػೳΛ࢖༻
    ͠ɺϩόετͳγεςϜΛߏங
    4. Ϋϥ΢υɾΠϯϑϥΛk8sͰந৅Խ͢ΔࣄʹΑͬͯɺ֤Ϋϥ΢υɾϕϯμͷྑ͍ͱ͜औΓ
    Λ͍ͯ͠Δ
    !27
    

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28. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    Amazon EKSʹ͍ͭͯ
    • k8sͱ͍͑͹GCPͱ͍͏Πϝʔδ͕͋Δ͕(։ൃݩ͔ͩΒ౰વ)ɺEKS΋͜ͳΕ͖ͯͯ҆ఆͨ͠ӡ
    ༻͕ग़དྷΔΑ͏ʹͳͬͨɻ͔͠͠Pros/Cons͸౰વଘࡏ͢Δɻ
    • Pros
    • ૉͷk8sʹۙ͘ɺͦ͏͍ͬͨҙຯͰ͸ॊೈͳߏ੒Λ૊Έ΍͍͢
    • Cons
    • ଞࣾͷϚωʔδυk8sαʔϏεʹൺ΂ɺk8sʹ͍ͭͯඞཁͳࣄલ஌͕ࣝଟ͍
    • ͔͠͠࢖͍উखͷྑ͍AWSͷS3΍RDS౳ͷଞαʔϏεΛɺk8sͱڞʹ࢖͍͍ͨϢʔβ͕᪳᪯͢
    Δཧ༝͸΋͸΍ͳ͍
    !28
    

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29. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    AWSͷྑ͍ͱ͜Ζ
    • AWSͷྑ͍ॴ͸Կͱݴͬͯ΋RDSɺAuroraʹ୅ද͞ΕΔɺϚωʔδυɾRDBMSαʔϏε
    • ࠷ॳRDSͰ࡞ͬͯɺύϑΥʔϚϯεʹࠔͬͨΒAuroraΛ࢖͏
    • Persistent૚͕ॏཁͳɺಛʹRDBΛ࢖༻͢ΔγεςϜͰ͸ɺ࠷ॳͷબ୒ࢶʹͳΔ
    • ࠓճͷߏ੒ྫͱ͸গ͠ҧ͏͕ɺk8s(EKS)ͰϏδωεɾϩδοΫ͕ͷΔΠϯϑϥ෦෼Λ
    ந৅Խ͠Persistent૚ʹRDS౳ͷαʔϏεΛ࢖༻͢Δͷ͸͓͢͢Ίߏ੒ͷ̍ͭ
    !29
    

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30. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    Next Future?
    !30
    

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31. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    Realtime image search
    • ॴҦ Edge AI TechnologyΛ࢖༻ͯ͠ɺݕࡧʹඞཁͳਪ
    ࿦ॲཧͷେ෦෼ΛEdgeଆͰߦ͍ͬͯΔ
    • ϦΞϧλΠϜͳΠϯλϥΫγϣϯΛ࣮ݱ
    • UX্େ͖ͳϝϦοτ͕༗Δ
    !31
    

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32. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    Listing Dispacher
    • ద੾ͳग़඼ϝιουΛαδΣετͯ͘͠ΕΔ
    • ෳࡶͳग़඼ϑϩʔΛ؆ུԽ
    • ࠷ऴతʹ͸͔͚ͩ͟͢Ͱग़඼͕׬ྃ͢ΔॴΛ໨ࢦ͢!!
    !32
    

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33. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    What must happen to make DNN work on edge
    • ༷ʑͳτϨʔυΦϑ໰୊͕ଘࡏ͢Δ
    • Accuracy
    • Latency
    • Energy consumption
    • Model size
    • ໨తͷUXΛୡ੒͢ΔͨΊʹɺΞϧΰϦ
    ζϜɺΤϯδχΞϦϯά྆ํͰͦΕΒͷ
    όϥϯεΛߟྀ͢Δඞཁ͕͋Δ
    !33
    Image credit: [1] Image credit: [1]
    Image credit: [2]
    ɾΦϖϨʔγϣϯʹΑͬͯίετ͕ҧ͏[1]
    ɾmobile deviceͰαϙʔτ͍ͯ͠ΔGPUΠϯλʔϑΣʔεͷγΣΞ[2]ɹ
    

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34. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    Landscape of execution environment
    Image credit: [2] Image credit: [2]
    ※ FacebookͷϨϙʔτ͔ΒͷҾ༻[2]
    ೗Կʹ໨తͷUXΛ࣮ݱͰ͖ΔσόΠεͷΧόϨοδΛ޿͛Δ͔?
    !34
    

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35. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    Designing efficient networks: Manual efforts
    - Mobile Nets V1, V2 and V3([4], [5], & [6])
    • Depthwise separable
    conv Λ࢖༻͠ܭࢉྔΛ
    ௿ݮ
    • Inverted residual
    with linear
    bottleneck Λ࢖༻͠
    ϝϞϦΞΫηεྔΛ
    ௿ݮ
    Image credit: [4] Image credit: [5] Image credit: [6]
    • ׆ੑԽؔ਺ʹh-swishΛ࢖༻
    • squeeze & excitationΛ࢖
    ༻ͨ͠channelͷAttention
    • ܰྔͳfinal blockͷ࠾༻
    etc...
    !35
    

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36. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    Designing efficient networks: Automated ways
    - ௨ৗͷϞσϧͷτϨʔχϯά
    ΛτϨʔχϯάɾύϥϝʔλͱͨ͠Ϟσϧ Λೖྗɺ Λग़ྗͱͯ͠ɺ Λ࠷খԽ͢Δ ୳ࡧ͢Δ
    - ΞʔΩςΫνϟɾαʔνͰͷ୳ࡧ&τϨʔχϯά
    ΞʔΩςΫνϟɾύϥϝʔλ ௥Ճ Λ࠷খԽ͢Δ Λ୳ࡧ͢Δ
    ͱ
    !36
    

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37. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    Two influential yet costly approaches
    !37
    MnasNet[7] (RL-Based) FBNet[8]
    (Differentiable)
    • ୳ࡧۭ͔ؒΒ਺ઍͷmodelΛsampling͢Δ
    • sample͞Εͨchild modelΛεΫϥον͔
    ΒτϨʔχϯά͢Δ
    • ڊେͳ୳ࡧۭ͔ؒΒ୳ࡧͰ͖Δ͕ɺݱ࣮త
    ͳΠςϨʔγϣϯΛߦ͏ҝʹɺڊେͳܭࢉ
    ػϦιʔε͕ඞཁʹͳΔ
    • DARTSϕʔεͷ୳ࡧख๏Λ࠾༻͍ͯ͠Δ
    • ୳ࡧۭؒ಺ͷ֤ΦϖϨʔγϣϯΛGPUϝϞϦ
    ʹ৐ͤΔඞཁ͕͋Δҝɺ݁ہGPUϝϞϦͷ࢖
    ༻ྔ͕໰୊ͱͳΓɺsample͞Εͨproxy
    dataset͕ඞཁʹͳͬͨΓɺbatch sizeΛ্͛
    ΒΕͳ͔ͬͨΓ͢Δ
    Image credit: [7] Image credit: [8]
    

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38. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    Our approach
    !38
    Single-Path NAS[9]
    Device
    SoC Generation
    (Snapdragon) Model
    ImageNet Top-1
    Accuracy* Latency (ms)*
    A 845 SPNAS 74.48 77.90
    A 845 MobileNetV2 71.80 76.36
    B 808 SPNAS 73.07 113.92
    B 808 MobileNetV2 71.80 162.82
    C 670 SPNAS 73.15 92.14
    C 670 MobileNetV2 71.80 111.85
    D 801 SPNAS 71.93 84.65
    D 801 MobileNetV2 71.80 120.82
    Image credit: [9]
    * All results are for float32
    • superkenelͱ͍͏୳ࡧۭؒͷઃఆ
    ख๏Ͱɺ਺ඦʙ਺ઍGPU͔͔࣌ؒ
    Δ୳ࡧ࣌ؒΛ࡟ݮ͢Δ͜ͱ͕Ͱ͖Δ
    • MobileNet-V2ͱSingle-Path
    NAS(SPNAS)Ͱੜ੒ͨ͠Ϟσϧͱ
    ͷੑೳൺֱ
    MobileNet-V3Λϕʔεʹ୳ࡧۭؒΛઃఆ͠ɺSPNAS౳ͷϦʔζφϒϧͳNASख๏Ͱ୳ࡧ
    Λߦ͏ͷ͕ݱ࣮త?
    

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39. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    Edge function architecture
    !39
    39
    Server side Client side
    • αʔόଆͷDNN frameworkʹ͸
    TensorFlowΛ࢖༻
    • LykeionʹΑͬͯύΠϓϥΠϯΛ
    ߏங
    • ΫϥΠΞϯτଆͰ͸TensorFlow
    Lite + MediaPipeΛ࢖༻
    • MediaPipeΛ࢖༻͢Δ͜ͱͰલॲ
    ཧ΍ޙॲཧ΋SIMD౳Λ࢖༻ͯ͠
    ޮ཰ԽͰ͖Δ
    (TF Lite)
    (Optional)
    

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40. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    Conclusion Again
    !40
    

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41. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    Edge AI Technology
    !41
    41
    • ϦΞϧλΠϜͳΠϯλϥΫγϣϯΛ࣮ݱ͠UX্େ͖ͳϝϦοτ͕༗Δ
    • ͔͠͠Model΍Runtimeɺ͞Βʹ͸Backendͱߟྀ͢΂͖ࣄฑ͕ଟ͘ͳΔͷ΋ࣄ࣮
    • ໨తͷUXΛ࣮ݱ͢ΔͨΊʹɺ Accuracy΍Latency౳ͷόϥϯεΛऔΔඞཁ͕͋Δ
    • ඞͣ͠΋Accuracy͕࠷༏ઌͰ͸ͳ͍
    • ࠓޙҰൠԽ͞ΕΔաఔͰɺҾ͖ଓ͖Runtime΍Modelingख๏ͷٸܹͳਐԽ͕༧૝͞ΕΔ
    

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42. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    References
    !42
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43. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    Thank you all for coming today
    !43
    

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