{"id":9257,"date":"2016-03-21T21:37:26","date_gmt":"2016-03-21T18:37:26","guid":{"rendered":"http:\/\/blog.altoros.com\/?p=9257"},"modified":"2021-03-03T16:36:48","modified_gmt":"2021-03-03T13:36:48","slug":"distributed-multi-device-execution-of-tensorflow-for-iot","status":"publish","type":"post","link":"https:\/\/www.altoros.com\/blog\/distributed-multi-device-execution-of-tensorflow-for-iot\/","title":{"rendered":"Distributed Multi-Device Execution of TensorFlow for IoT"},"content":{"rendered":"<p><img decoding=\"async\" src=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2016\/08\/munich_tensorflow_meetup-v11.jpeg\" alt=\"\" width=\"130\" class=\"alignright size-full wp-image-28658\" \/><\/p>\n<p>Below are the videos\/slides from the <a href=\"https:\/\/www.meetup.com\/data-science-on-aws-munich\/events\/226921065\/\" target=\"_blank\" rel=\"noopener noreferrer\">TensorFlow Munich meetup<\/a>\u2014sponsored and organized by Altoros on March 1, 2016.<\/p>\n<p>&nbsp;<\/p>\n<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_79_2 counter-hierarchy ez-toc-counter ez-toc-transparent ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">Table of Contents<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" aria-label=\"Toggle Table of Content\"><span class=\"ez-toc-js-icon-con\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #999;color:#999\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewBox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #999;color:#999\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewBox=\"0 0 24 24\" version=\"1.2\" baseProfile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/span><\/a><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1 ' ><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/www.altoros.com\/blog\/distributed-multi-device-execution-of-tensorflow-for-iot\/#TensorFlow_overview\" >TensorFlow overview<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/www.altoros.com\/blog\/distributed-multi-device-execution-of-tensorflow-for-iot\/#Distributed_multi-device_execution_of_TensorFlow\" >Distributed multi-device execution of TensorFlow<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/www.altoros.com\/blog\/distributed-multi-device-execution-of-tensorflow-for-iot\/#Fireside_chat\" >Fireside chat<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/www.altoros.com\/blog\/distributed-multi-device-execution-of-tensorflow-for-iot\/#Further_reading\" >Further reading<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/www.altoros.com\/blog\/distributed-multi-device-execution-of-tensorflow-for-iot\/#About_the_speakers\" >About the speakers<\/a><\/li><\/ul><\/nav><\/div>\n<h3><span class=\"ez-toc-section\" id=\"TensorFlow_overview\"><\/span>TensorFlow overview<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>In his session, <a href=\"https:\/\/www.linkedin.com\/in\/ankitbahuguna\" target=\"_blank\" rel=\"noopener noreferrer\">Ankit Bahuguna<\/a> of Cliqz provided an insight into TensorFlow usage, the library\u2019s mechanics, and implementation. To demonstrate <a href=\"https:\/\/www.altoros.com\/blog\/visualizing-tensorflow-graphs-with-tensorboard\/\">TensorBoard\u2019s capabilities<\/a> in visualizing learning, he exemplified two demos on <a href=\"https:\/\/www.altoros.com\/blog\/using-linear-regression-in-tensorflow\/\">linear regression<\/a> and visualizing word embeddings in TensorFlow. Finally, he shared the results of the recent benchmarks and outlined the likely scenarios of evolution.<\/p>\n<p><center><script charset=\"ISO-8859-1\" src=\"\/\/fast.wistia.com\/assets\/external\/E-v1.js\" async><\/script><\/p>\n<div class=\"wistia_embed wistia_async_f6a4tzsidy\" style=\"height:360px;width:640px\">&nbsp;<\/div>\n<p><\/center><\/p>\n<p>&nbsp;<\/p>\n<p>Below, you can check out the full slides by Ankit.<\/p>\n<p><center><script async class=\"speakerdeck-embed\" data-id=\"de4dae679d234dc393ac1931a6f37018\" data-ratio=\"1.33333333333333\" src=\"\/\/speakerdeck.com\/assets\/embed.js\"><\/script><\/center><\/p>\n<p>&nbsp;<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Distributed_multi-device_execution_of_TensorFlow\"><\/span>Distributed multi-device execution of TensorFlow<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><a href=\"https:\/\/www.linkedin.com\/in\/rusitschka\" target=\"_blank\" rel=\"noopener noreferrer\">Sebnem Rusitschka<\/a>, Senior Key Expert for Cyber-physical Systems at Siemens, provided an overview of TensorFlow from a <a href=\"https:\/\/www.altoros.com\/blog\/distributed-tensorflow-and-classification-of-time-series-data-using-neural-networks\/\">distributed computing perspective<\/a>. She also elaborated on the perculiarities of embedded systems when using TensorFlow and highlighted the associated challenges. Finally, Sebnem talked about multi-dimensional IoT data, tensor networks, and arrays\/indexing.<\/p>\n<p><center><iframe loading=\"lazy\" src=\"\/\/www.slideshare.net\/slideshow\/embed_code\/key\/lFodLv0mT9wVLP\" width=\"595\" height=\"485\" frameborder=\"0\" marginwidth=\"0\" marginheight=\"0\" scrolling=\"no\" style=\"border:1px solid #CCC; border-width:1px; margin-bottom:5px; max-width: 100%;\" allowfullscreen><\/iframe><\/center><\/p>\n<p>&nbsp;<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Fireside_chat\"><\/span>Fireside chat<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>Later on, <a href=\"https:\/\/www.linkedin.com\/in\/aosterloh\" target=\"_blank\" rel=\"noopener noreferrer\">Alex Osterloh<\/a> of Google and <a href=\"https:\/\/www.linkedin.com\/in\/artyom-topchyan-36254284\" target=\"_blank\" rel=\"noopener noreferrer\">Artyom Topchyan<\/a> of Reply discussed:<\/p>\n<ul>\n<li>What kind of tasks TensorFlow is built for?<\/li>\n<li>The <a href=\"https:\/\/www.altoros.com\/blog\/deep-learning-in-healthcare-finance-and-iiot-tensorflow-use-cases\/\">industries \/ projects<\/a> TensorFlow is applied within and the feedback received<\/li>\n<li>Recommendations for those getting started with TensorFlow<\/li>\n<li>The biggest challenges TensorFlow has at the moment<\/li>\n<li>Contributions of the community that can be of help<\/li>\n<li>The impact of open-sourcing TensorFlow<\/li>\n<\/ul>\n<p><center><script charset=\"ISO-8859-1\" src=\"\/\/fast.wistia.com\/assets\/external\/E-v1.js\" async><\/script><\/p>\n<div class=\"wistia_embed wistia_async_kdch1f0c64\" style=\"height:360px;width:640px\">&nbsp;<\/div>\n<p><\/center><\/p>\n<p>&nbsp;<\/p>\n<p>Join <a href=\"https:\/\/www.meetup.com\/data-science-on-aws-munich\/\" target=\"_blank\" rel=\"noopener noreferrer\">our group<\/a> to stay updated with information on the upcoming meetups.<\/p>\n<p>&nbsp;<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Further_reading\"><\/span>Further reading<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<ul>\n<li><a href=\"https:\/\/www.altoros.com\/blog\/visualizing-tensorflow-graphs-with-tensorboard\/\">Visualizing TensorFlow Graphs with TensorBoard<\/a><\/li>\n<li><a href=\"https:\/\/www.altoros.com\/blog\/distributed-tensorflow-and-classification-of-time-series-data-using-neural-networks\/\">Distributed TensorFlow and Classification of Time-Series Data Using Neural Networks<\/a><\/li>\n<li><a href=\"https:\/\/www.altoros.com\/blog\/adopting-tensorflow-for-manufacturing-and-industrial-internet-of-things\/\">Adopting TensorFlow for Manufacturing and Industrial Internet of Things<\/a><\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<h3><span class=\"ez-toc-section\" id=\"About_the_speakers\"><\/span>About the speakers<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<div>\n<div style=\"float: right;\"><a href=\"https:\/\/www.linkedin.com\/in\/ankitbahuguna\" target=\"_blank\" rel=\"noopener noreferrer\"><img decoding=\"async\" src=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2016\/03\/ankit-bahuguna-cliqz.png\" alt=\"\" width=\"110\" class=\"alignright size-full wp-image-60119\" \/><\/a><\/div>\n<div style=\"width: 600px;\"><small><a href=\"https:\/\/www.linkedin.com\/in\/ankitbahuguna\" target=\"_blank\" rel=\"noopener noreferrer\">Ankit Bahuguna<\/a> is Software Engineer at Cliqz, where he develops deep learning solutions to tackle the problem of low latency in web search. Ankit&#8217;s current work is focused on query embeddings, where the semantics of a user query is preserved in a fixed dimensional mathematical vector\u2014trained using deep neural networks.<\/small><\/div>\n<\/div>\n<p>&nbsp;<\/p>\n<div>\n<div style=\"float: right;\"><a href=\"https:\/\/www.linkedin.com\/in\/rusitschka\" target=\"_blank\" rel=\"noopener noreferrer\"><img decoding=\"async\" src=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2016\/03\/sebnem-rusitschka-siemens.png\" alt=\"\" width=\"110\" class=\"alignright size-full wp-image-60120\" \/><\/a><\/div>\n<div style=\"width: 600px;\"><small><a href=\"https:\/\/www.linkedin.com\/in\/rusitschka\" target=\"_blank\" rel=\"noopener noreferrer\">Sebnem Rusitschka<\/a> has 10 years of experience in translating Internet-scale innovations to the world of industrial machines and processes. The area of her expertise includes digitized automation of infrastructures, especially, electrification. In 2015, she became Senior Key Expert for Cyber-Physical Systems at Siemens with a mission to bring together experts from various disciplines of machine learning, control theory, and distributed computing to achieve adaptive automation systems.<\/small><\/div>\n<\/div>\n<p>&nbsp;<\/p>\n<div>\n<div style=\"float: right;\"><a href=\"https:\/\/www.linkedin.com\/in\/aosterloh\" rel=\"noopener noreferrer\" target=\"_blank\"><img decoding=\"async\" src=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2016\/03\/alex-osterloh-google.png\" alt=\"\" width=\"110\" class=\"alignright size-full wp-image-60121\" \/><\/a><\/div>\n<div style=\"width: 600px;\"><small><a href=\"https:\/\/www.linkedin.com\/in\/aosterloh\" rel=\"noopener noreferrer\" target=\"_blank\">Alex Osterloh<\/a> is Big Data Solutions Engineer at Google. He graduated from Ludwig Maximilian University of Munich with a master\u2019s degree in computer science and had experience as Presales Engineer at Hewlett-Packard before joining Google in 2010. Alex\u2019s current job involves converting big data to smart data and leveraging Google Cloud Platform for doing large-scale data crunching.<\/small><\/div>\n<\/div>\n<p>&nbsp;<\/p>\n<div>\n<div style=\"float: right;\"><a href=\"https:\/\/www.linkedin.com\/in\/artyom-topchyan-36254284\" rel=\"noopener noreferrer\" target=\"_blank\"><img decoding=\"async\" src=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2016\/03\/artyom-topchyan-reply.png\" alt=\"\" width=\"110\" class=\"alignright size-full wp-image-60122\" \/><\/a><\/div>\n<div style=\"width: 600px;\"><small><a href=\"https:\/\/www.linkedin.com\/in\/artyom-topchyan-36254284\" rel=\"noopener noreferrer\" target=\"_blank\">Artyom Topchyan<\/a> is Technical Lead at Data Reply. He graduated from Technical University of Munich with a master\u2019s degree in robotics. As Research Assistant, Artyom managed to integrate a number of machine learning\u2013based methods into the university\u2019s computer vision library. He also has experience in natural language processing. Artyom developed a system for large-scale extraction and analysis of job descriptions, helping to analyze the required competencies and competency dynamics in the job market.<\/small><\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<\/p>\n<p>Below are the videos\/slides from the TensorFlow Munich meetup\u2014sponsored and organized by Altoros on March 1, 2016.<\/p>\n<p>&nbsp;<\/p>\n<p>TensorFlow overview<\/p>\n<p>In his session, Ankit Bahuguna of Cliqz provided an insight into TensorFlow usage, the library\u2019s mechanics, and implementation. To demonstrate TensorBoard\u2019s capabilities in visualizing learning, he exemplified two demos on linear regression and [&#8230;]<\/p>\n","protected":false},"author":3,"featured_media":60115,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"content-type":"","footnotes":"","_links_to":"","_links_to_target":""},"categories":[214],"tags":[117,748,749],"class_list":["post-9257","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-tutorials","tag-iot","tag-machine-learning","tag-tensorflow"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.6 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Distributed Multi-Device Execution of TensorFlow for IoT | Altoros<\/title>\n<meta name=\"description\" content=\"Learn about TensorBoard\u2019s capabilities in visualizing learning, the challenges of using TensorFlow for embedded systems, and multi-dimensional IoT data.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.altoros.com\/blog\/distributed-multi-device-execution-of-tensorflow-for-iot\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Distributed Multi-Device Execution of TensorFlow for IoT | Altoros\" \/>\n<meta property=\"og:description\" content=\"Below are the videos\/slides from the TensorFlow Munich meetup\u2014sponsored and organized by Altoros on March 1, 2016. &nbsp; TensorFlow overview In his session, Ankit Bahuguna of Cliqz provided an insight into TensorFlow usage, the library\u2019s mechanics, and implementation. 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