NVIDIA at Strata Data Conference 2018

September 11-13, 2018
Javits Center, New York City

GPU Computing for the Intelligent Enterprise

Fueled by Massive Amounts of Data.
Driven by Purpose-Based Innovation.
Powered by AI Computing.

NVIDIA, the GPU computing company with the world’s leading compute power, is paving the way for companies to become intelligent enterprises.

Strata Data Conference in New York, NVIDIA and our ecosystem partners will showcase the GPU-accelerated solutions powering AI-enabled machine learning and big data analytics applications. In our sessions, we will take a deep dive into emerging AI techniques and technologies and how they are implemented across many industries. We’ll show real world use cases in how AI has been implemented in all industries. Join us for one or all of our sessions.

Follow Us Live at @NVIDIAAI, #StrataData

NVIDIA Talks - Deep Learning Track Sponsored by NVIDIA

NVIDIA Talks - Deep Learning Track Sponsored by NVIDIA

Join us to learn how NVIDIA is leading the discussion in AI innovation.

Join us to learn how NVIDIA is leading the discussion in AI innovation.

Wednesday, September 12th

11:20am - 12:00pm

Ward Eldred

Deep learning: Assessing Analytics Project Feasibility and Requirements
Ward Eldred
(NVIDIA)
Location: 1E15

Ward Eldred offers an overview of the types of analytical problems that can be solved using deep learning and shares a set of heuristics that can be used to evaluate the feasibility of analytical AI projects. Ward then covers the computational profile of the deep learning workload and the infrastructure components that need to be set in place to fuel the successful deep learning training process, leaving you with the key tools you need to initiate an analytical deep learning project.

Learn more about GPU-Accelerated Data Analytics.

 1:15pm - 1:55pm

Darrin Johnson

Simplifying AI Infrastructure: Lessons in Scaling a Deep Learning enterprise
Darrin Johnson
(NVIDIA)
Location: 1E15

While every enterprise is on a mission to infuse its business with deep learning, few know how to build the infrastructure to get them there. Shortsighted approaches to data center design can lead to long-term consequences that make the ROI of AI elusive. Darrin Johnson shares insights and best practices learned from NVIDIA’s deep learning deployments around the globe that you can leverage to shorten deployment timeframes, improve developer productivity, and streamline operations.

Learn more about NVIDIA DGX Systems.

 2:05pm - 2:45pm

Michael Balint

Kubernetes on GPUs
Michael Balint
(NVIDIA)
Location: 1E15

Building an AI application can be a challenging, iterative, and time-consuming endeavor – and empowering an entire team to build and deploy multiple AI applications simultaneously can be quite daunting. It doesn’t have to be that way! Leveraging the right infrastructure can make the entire process a joy. Learn how NVIDIA employs its own distribution of Kubernetes,in conjunction with DGX Systems, to make the most efficient use of GPU resources and scale its efforts across a cluster, allowing multiple users to run experiments and push their finished work to production.

Learn more about Kubernetes on GPUs.

4:35pm - 5:15pm

Jim McHugh
Tim Delisle
Alen Capalik
SriSatish Ambati

GPU-Accelerated Analytics and Machine Learning Ecosystems (Analytics Partners Showcase sponsored by NVIDIA)
Jim McHugh (NVIDIA)
Tim Delisle
(Datalogue)
Alen Capalik (Fasdat.io)
SriSatish Ambati
(H20.ai)

Location: 1E15

Join in to learn how GPU-accelerated deep learning data prep solution Datalogue can cut down 50 days of workflow to 5 days for better customer insights and greater data ROI; how GPU-native data processing solution FASTDATA.io can process a terabyte of data on a single GPU cloud in 35 seconds, instead of nine hours on Apache Spark; and how GPU-accelerated machine learning platform H2O.ai provides algorithms up to 30x faster than traditional algorithms, along with recipes for automatic feature engineering for faster and more scalable inferencing.

Datalogue

Datalogue is a NVIDIA GPU AI-augmented data operations platform. It enables automated ingestion of every data source, every data type across your entire network. Data scientists and data operators can now spend 5% or less time preparing and 95% doing data science.

FastData

Exploiting the massive parallel processing power of the GPU, FASTDATA.io has created the fastest stream processing engine in the world today. Plasma Engine™ is the first GPU-native software to fully leverage NVIDIA GPUs and Apache Arrow for real-time processing of infinite data in motion. By porting Apache Spark to Plasma Engine, we empower you to process your existing Spark workloads faster than ever on GPUs without the hassle of changing your code.


H20.ai

H2O.ai provides open source GPU-accelerated machine learning algorithms and Driverless AI platform for accurate and interpretable model building. H2O.ai brings machine learning solutions to financial services, insurance, and healthcare industries.

Learn more about Analytics partners.

5:25pm - 6:05pm

Renee Yao

Accelerate AI with Synthetic Data Using Generative Adversarial Networks (GAN)
Renee Yao
(NVIDIA)
Location: 1E15

Synthetic data will drive the next wave of deployment and application of deep learning in the real world across a variety of problems involving speech recognition, image classification, object recognition and language. All industries, and companies will benefit, as synthetic data can create conditions through simulation, instead of authentic situations (virtual worlds enable you to avoid cost of damages, spare human injuries, and other factors that come into play); unparalleled ability to test products, and interactions with them in any environment.

Join us for this introductory session to learn more about how Generative Adversarial Networks (GAN) are successfully used to improve data generation. We will cover specific real world examples where customers have deployed GAN to solve challenges in healthcare, space, transportation, and retail industries

Learn more about the Inception Program.

5:25pm - 6:05pm

Joshua Patterson
Omar Yilmaz

Accelerating Financial Data Science Workflows on GPUs
Joshua Patterson
(NVIDIA)
Omar Yilmaz (NVIDIA)
Location: 1A 15/16

Joshua Patterson and Onur Yilmaz will discuss several GPU accelerated data science tools and libraries that can be used to process financial data more efficiently. They will talk about the evolution of the GPU data science ecosystem and discuss the motivation behind and value of the GPU Open Analytics Initiative (GoAi)—a collection of libraries, frameworks, and APIs built on Apache Arrow, designed to simplify and accelerate development and performance. Finally, they will show machine learning and deep learning approaches to various financial services use cases.

Learn more about the GPU Open Analytics.

Add all of these sessions to your personal schedule

NVIDIA AT ECOSYSTEM PARTNER's BOOTHS

NVIDIA AT ECOSYSTEM PARTNER's BOOTHS

Join us to learn how NVIDIA is leading the discussion in AI innovation.

Join us to learn how NVIDIA is leading the discussion in AI innovation.

Wednesday September 12th

12:30pm

Rima Alameddine

NVIDIA & CISCO: Powering Change with AI
Rima Alameddine
(NVIDIA)
Location: Cisco booth #1007

See you on the showfloor among our ecosystems partners for more purpose-driven use cases.

Learn more about GPU-Accelerated Analytics

STRATA PARTY

Have a chance to chat with experts from NVIDIA, Anaconda, Cisco, Kinetica, MapD, and Pure Storage at our party Wednesday evening. Register now to secure your spot!

Events Strata Hadoop Party

NVIDIA'S PARTNER ECOSYSTEM AT STRATA

Anaconda
Datalogue
FastData
H2O
IBM Cloud
MapD
NetApp
Pure Storage
SAP

Keep up on the latest in AI and analytics