Be sure to attend these sessions at GTC 2019 to learn about the latest developments and use cases for NVIDIA DGX solutions.

1. DGX SESSIONS YOU WON’T WANT TO MISS AT
GTC 2019

2. NVIDIA LED DGX SESSIONS AT GTC 2019
NVIDIA LED SESSIONS
S9483 Creating AI Workgroups Within The Enterprise: Developers Share Their Best Practices
- Markus Weber, Senior Product Manager & Michael Balint, Senior Product Manager
S9120 How to Accelerate and Scale A.I. Deployment with Proven Architecture Designs
- Charlie Boyle, Senior Director, Product Management
S9121 Deep Learning Implementers Panel: Experts Discuss The Keys to Their Success
- Tony Paikeday, Director, Product Marketing
S9653 How to Make Your Life Easier in the Age of Exascale Computing Using NVIDIA GPUDirect Technologies
- Elena Agostini, Software Engineer & David Rossetti, Software Engineer
CE9116 Connect with the Experts: Memory Management on Heterogeneous Systems
- Nikolay Sakharnykh, Sr. Developer Technology Engineer, Lars Nyland, GPU Computing Architect, Max Katz, Solutions Architect, Javier Cabezas, Sr.
System Software Engineer, Robert Crovella, Solutions Architect, & Mark Hairgrove, CUDA Driver
S9334 AI Infrastructure: Lessons Learned from NVIDIA DGX POD
- Darrin Johnson, Global Technical Marketing for Enterprise, Andrew Bull, Senior Solutions Architect, Sumit Kumar, Solutions Architect, and Jacci
Cenci, Senior Technical Marketing Engineer
S9893
KVM GPU Virtual Machines: Maximizing Performance and Utilization on DGX
- Anish Gupta, Principal Engineer
S9241
All You Need to Know about Programming NVIDIA's DGX-2
- Lars Nyland, GPU Computing Architect & Stephen Jones, Principal Software Engineer

3. DEEP LEARNING IMPLEMENTERS PANEL: EXPERTS
DISCUSS THEIR KEYS TO THEIR SUCCESS
This customer panel brings together AI implementers who
have deployed deep learning at scale. The discussion will
focus on specific technical challenges they faced, solution
design considerations, and best practices from
implementing their respective solutions.
Time: 3/19/19 2:00 - 2:50 PM
Location: Marriott Hotel Ballroom 3
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4. ALL YOU NEED TO KNOW ABOUT PROGRAMMING
NVIDIA’S DGX-2
NVIDIA's DGX-2 system offers a unique architecture
that connects 16 GPUs together via the high-speed
NVLink interface, along with NVSwitch which
enables unprecedented bandwidth between
processors. This talk will take an in-depth look at
the properties of this system along with
programming techniques to take maximum
advantage of the system architecture.
Time: 3/20/19 1:00 - 1:50 PM
Location: SJCC Room 220C
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5. CREATING AI WORKGROUPS WITHIN THE ENTERPRISE:
DEVELOPERS SHARE THEIR BEST PRACTICES
Learn from NVIDIA customers who will share their
best practices for extending AI compute power to
their teams without the need to build and manage
a data center. These organizations will describe
innovative approaches that let them turn an
NVIDIA DGX Station into a powerful solution
serving entire teams of developers from the
convenience of an office environment. Learn how
teams building powerful AI applications may not
need to own servers or depend on data center
access. The organizations will also show demos of
how to set up an AI workgroup with ease.
Time: 3/18/19 9:00 - 9:50 AM
Location: Marriott Hotel Ballroom 3
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6. HOW TO ACCELERATE AND SCALE AI DEPLOYMENT
WITH PROVEN ARCHITECTURE DESIGNS
While every enterprise is on a mission to infuse its
business with deep learning, few know how to build
the infrastructure to get there. Short-sighted
approaches to data center design can lead to long-
term consequences that make the ROI of AI elusive.
We'll talk about the insights and best practices we at
NVIDIA have gained from deep learning deployments
around the globe and provide prescriptive guidance
that every organization can leverage to shorten
deployment timeframes, improve developer
productivity, and streamline operations.
Time: 3/19/19 10:00 - 10:50 AM
Location: SJCC Room 212B
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7. AI INFRASTRUCTURE: LESSONS LEARNED FROM NVIDIA
DGX POD
Do you have a GPU cluster or air-gapped
environment that you are responsible for but don't
have an HPC background? NVIDIA DGX POD is a new
way of thinking about AI infrastructure, combining
DGX servers with networking and storage to
accelerate AI workflow deployment and time to
insight. We'll discuss lessons learned about building,
deploying, and managing AI infrastructure at scale
— from design to deployment to management and
monitoring.
Time: 3/20/19 10:00 - 11:20 AM
Location: SJCC Room 212B
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8. PARTNER LED DGX SESSIONS AT GTC 2019
CUSTOMER/PARTNER LED SESSIONS
S9292
Red Hat and the NVIDIA DGX: Tried, Tested, Trusted
- Jeremy Eder, Senior Principal Software Engineer, Red Hat & Andre Beausoleil, Senior Principal Partner Manager, Red Hat
S9164
Advanced Weather Information Recall with DGX-2
- Tomohiro Ishibashi, Director, Weather News & Shigehisa Omatsu, CEO, dAIgnosis Inc
S9325
Machine Learning in Action within a Large Regional Healthcare System (Geisinger)
- Brandon Fornwalt, Associate Professor, Geisinger & Aalpen Patel, Chairman, System Radiology, Geisinger
S9373
TPC-H Benchmark on DGX-2: A New Paradigm for OLAP and Decision Support
- Richard Heyns, CEO, Brytlyt and Piotr Kowalski, Senior Engineer, Brytlyt
S9417
Molecular Generative VAEs: Parallelization, Optimization, and Latent Space Analysis on the DGX-1
- Ellen Du, Research Scientist, The Dow Chemical Company & Joey Storer, Principal Research Scientist, The Dow Chemical Company
S9469
MATLAB and NVIDIA Docker: A Complete AI Solution, Where You Need It, in an Instant
- Jos Martin, Engineering Manager, MathWorks & Joss Knight, Developer, MathWorks
S9892
Deep Learning for Autonomous Driving at BMW
- Alexander Frickenstein, PhD Candidate, BMW Group
S9406
Hybrid Cloud for Flexible GPU Resource Planning and Orchestration
- Jeongkyu Shin, CEO and Joongi Kim, CTO, Lablup, Inc.

9. RED HAT AND THE NVIDIA DGX: TRIED, TESTED,
TRUSTED
Red Hat and NVIDIA collaborated to bring together
two of the technology industry's most popular
products: Red Hat Enterprise Linux 7 and the NVIDIA
DGX system. This talk will cover how the
combination of RHELs rock-solid stability with the
incredible DGX hardware can deliver tremendous
value to enterprise data scientists. We will also show
how to leverage NVIDIA GPU Cloud container images
with Kubernetes and RHEL to reap maximum benefits
from this incredible hardware.
Time: 3/18/19 10:00 - 10:50 AM
Location: SJCC Room 212B
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10. ADVANCED WEATHER INFORMATION RECALL WITH
DGX-2
Learn how Weather News, Inc. is applying deep learning to
weather forecasting. They are now able to provide
Japanese TV news shows with AI-generated weather
information and plan to expand elsewhere in Asia. They’ll
explain how they used TensorFlow on an NVIDIA DGX-2
machine and innovative learning model to add
measurement results and increase the accuracy of their
forecaster. You’ll also hear about how they’re creating new
learning models with TensorRT on the DGX-2.
Time: 3/19/19 9:00 - 9:50 AM
Location: Hilton Hotel Market Room
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11. DEEP LEARNING FOR AUTONOMOUS DRIVING AT BMW
This session will discuss the process of training
deep neural networks using NVIDIA DGX servers at
BMW Group. We will describe our research work in
four application areas: fine-grained vehicle
representations for autonomous driving, panoptic
segmentation, self-supervised learning of the
drivable area for autonomous vehicles and neural
network optimization. All of these projects require
high-performance compute and demand a scalable,
agile and adaptive learning infrastructure,
leveraging Kubernetes on NVIDIA DGX servers.
Time: 3/20/19 4:00 - 4:50 PM
Location: SJCC Room 220A
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12. MOLECULAR GENERATIVE VAEs: PARALLELIZATION,
OPTIMIZATION, AND LATENT SPACE ANALYSIS ON THE
DGX-1
Generative Variational Autoencoders (VAE) in
molecular discovery and new materials design has
recently gained considerable attention in academia
as well as industry (Gomez-Bombarelli, 2017). In
this talk, we will present results from a combined
Dow Chemical and NVIDIA development effort to
implement a VAE for chemical discovery.
Researchers from The Dow Chemical Company will
discuss challenges associated with applying deep
learning to chemistry and highlight recently
developed methods.
Time: 3/20/19 3:00 - 3:50 PM
Location: SJCC Room 211B
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13. OPTIMIZING FACEBOOK AI WORKLOADS FOR NVIDIA
GPUS
Hear about Facebook’s experiences and solutions for
scaling up and increasing the utilization of GPU
resources with machine learning and HPC workloads
on premises and clouds. The core of their solution is
Backend.AI, an open source platform that combines
the power of Docker and CUDA. In this session,
Facebook engineers will demonstrate Backend.AI's
scaling and sharing of GPU resources from a case of
prototyping a TensorFlow ML model with GTX 1080
on a PC combined with AWS GPU instances and the
NVIDIA DGX platform.
Time: 3/19/19 9:00 - 9:50 AM
Location: SJCC Room 210D
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14. EXPLORE THE FULL LIST
OF DGX SESSIONS AND
REGISTER TODAY FOR GTC
LEARN MORE