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Having fun with Google Cloud + RasPi

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+Kazunori Sato @kazunori_279 Kaz Sato Staff Developer Advocate, Tech Lead for Data & Analytics Cloud Platform, Google Inc.

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= The Datacenter as a Computer

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Enterprise

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Jupiter network 40 G ports 10 G x 100 K = 1 Pbps total CLOS topology Software Defined Network

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Borg No VMs, pure containers Manages 10K machines / Cell DC-scale proactive job sched (CPU, mem, disk IO, TCP ports) Paxos-based metadata store

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Google BigQuery

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1 B 1 B 100 B 900 M

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

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Google BigQuery Demo: RegEx + GROUP BY on 10 B rows response read RegEx 10B ~10sec 372GB

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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

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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

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“The World's Largest IoT platform” with RasPi + BigQuery

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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

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Confidential & Proprietary Google Cloud Platform 16 Google Brain

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● Google Now ● Google Photos ● Gmail ● YouTube ● and more Google Brain: The Brain of Google services

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Confidential & Proprietary Google Cloud Platform 22 Google Cloud Vision API

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Demo Video

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24 Types of Detection ● Label ● Landmark ● Logo ● Face ● Text ● Safe search

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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

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Making a request { "requests":[ { "image": { "content": "base64ImageString" }, "features": [ { "type": "LABEL_DETECTION", "maxResults": 10 }, { "type": "FACE_DETECTION", "maxResults": 10 }, // More feature detection types... ] } ] }

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Confidential & Proprietary Google Cloud Platform 27 TensorFlow

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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?

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Portable ● Runs on many platforms ○ Data Center ○ CPUs and GPUs ○ Mobile phones

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Yet another dataflow systemwith tensors MatMul Add Relu biases weights examples labels Xent Edges are N-dimensional arrays: Tensors

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Distributed

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Simple Example

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Thank you