Having fun with Google Cloud + RasPi

Having fun with Google Cloud + RasPi

91aeb42c5d9548918d1459f64240e503?s=128

Kazunori Sato

January 30, 2016
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  1. Having fun with Google Cloud + RasPi

  2. +Kazunori Sato @kazunori_279 Kaz Sato Staff Developer Advocate, Tech Lead

    for Data & Analytics Cloud Platform, Google Inc.
  3. = The Datacenter as a Computer

  4. None
  5. Enterprise

  6. Jupiter network 40 G ports 10 G x 100 K

    = 1 Pbps total CLOS topology Software Defined Network
  7. Borg No VMs, pure containers Manages 10K machines / Cell

    DC-scale proactive job sched (CPU, mem, disk IO, TCP ports) Paxos-based metadata store
  8. Google BigQuery

  9. 1 B 1 B 100 B 900 M

  10. At Google, MapReduce is classic. We use BigQuery. Confidential &

    Proprietary Google Cloud Platform 10
  11. Google BigQuery Demo: RegEx + GROUP BY on 10 B

    rows response read RegEx 10B ~10sec 372GB
  12. SELECT your_data FROM billions_of_rows WHERE full_disk_scan_required = true; Scanning 1

    TB in 1 sec with 5,000 - 10,000 disk spindles
  13. BigQuery Analytic Service in the Cloud BigQuery Analyze Export Import

    How to use BigQuery? Google Analytics ETL tools Connectors Google Cloud BI tools and Visualization Google Cloud Spreadsheets, R, Hadoop
  14. “The World's Largest IoT platform” with RasPi + BigQuery

  15. Blazingly Fast Capable of scanning 100B rows in ~20 sec

    Low Cost Storage: $0.020 per GB per month Queries: $5 per TB Fully Managed Use thousands of servers with zero-ops SQL Simple and Intuitive SQL with JS UDF Benefits of BigQuery
  16. Confidential & Proprietary Google Cloud Platform 16 Google Brain

  17. None
  18. None
  19. • Google Now • Google Photos • Gmail • YouTube

    • and more Google Brain: The Brain of Google services
  20. None
  21. None
  22. Confidential & Proprietary Google Cloud Platform 22 Google Cloud Vision

    API
  23. Demo Video

  24. 24 Types of Detection • Label • Landmark • Logo

    • Face • Text • Safe search
  25. 25 Types of Detection Face Detection ◦ Find multiple faces

    ◦ Location of eyes, nose, mouth ◦ Detect emotions: joy, anger, surprise, sorrow Entity Detection ◦ Find common objects and landmarks, and their location in the image ◦ Detect explicit content
  26. Making a request { "requests":[ { "image": { "content": "base64ImageString"

    }, "features": [ { "type": "LABEL_DETECTION", "maxResults": 10 }, { "type": "FACE_DETECTION", "maxResults": 10 }, // More feature detection types... ] } ] }
  27. Confidential & Proprietary Google Cloud Platform 27 TensorFlow

  28. A new system for distributed, parallel machine learning: • Based

    on general-purpose dataflow graphs • Targeting heterogeneous devices ◦ single PC with CPU ◦ single PC with GPU(s) ◦ mobile device ◦ clusters of 100s or 1000s of CPUs and GPUs What is TensorFlow?
  29. Portable • Runs on many platforms ◦ Data Center ◦

    CPUs and GPUs ◦ Mobile phones
  30. Yet another dataflow systemwith tensors MatMul Add Relu biases weights

    examples labels Xent Edges are N-dimensional arrays: Tensors
  31. Distributed

  32. Simple Example

  33. Thank you