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YARN GPU Support, Get Started with Tensor Flow, Data Science Experience Demo

San Jose Convention Center – Room 211
PLEASE NOTE – YOU DO NOT HAVE TO BE REGISTERED FOR THE DATAWORKS SUMMIT TO ATTEND THIS MEETUP.

Mix, Mingle and Learn from speakers on such topics as IBM’s Data Science Experience, Scalable TensorFlow Deep Learning as a Service with Docker and OpenPOWER with GPUs, and Hortonworks.

First class GPU support for big-data apps on your Apache Hadoop YARN clusters – Vinod Vavilapalli & Wangda Tan, Hortonworks
GPUs are increasingly becoming a key tool for many big data applications. Applications like deep-learning / machine learning, data analytics, Genome Sequencing, etc. all rely on GPUs for tractable performance. In many cases, GPUs can get 10x speed ups. And in some reported cases, GPUs can get up to 300x speed ups. Many modern deep-learning applications directly build on top of GPU libraries like cuDNN (CUDA Deep Neural Network library). It’s not a stretch to say that many applications like deep-learning cannot live without GPU support. By adding first class support (including configuration/discovery/scheduling/isolation) for GPUs in Apache Hadoop YARN, applications running on YARN are finally able to leverage the capability of GPUs in the shared cluster. This talk covers the details of how we add GPU support to YARN and how application developers can use this new feature and how cluster administrators can facilitate elastic sharing of these powerful devices.

Getting Started with TensorFlow Deep Learning Training on OpenPOWER – Andrei Yurkevich, CTO, Altoros
The disruptive power of applications using cognitive models is enormous, bringing both unprecedented value to humanity as well as open questions and cause for concern. This presentation will explain the popularity of TensorFlow, a powerful Deep Learning framework and arguably the most popular, including how it works, where it fits, and what to look out for. I’ll demonstrate how to train a TensorFlow model and how IBM Power Systems with OpenPOWER architecture make TensorFlow models even more powerful.

Improving Data Scientist Productivity with Data Science Experience – Patrick Pitre
Data Science is often hampered by the inability of data scientists to collaborate on a shared code base. In this demonstration, I will discuss the use of composable data services and a collaborative development space to increase the speed to market of analytics using IBM’s Data Science Experience and IBM Bluemix.

Hors d’oeuvres and beverages will be served. We look forward to seeing you there!

Wednesday, June 14, 2017
San Jose Convention Center: 150 West San Carlos Street, San Jose, CA