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DGX Sessions You Won't Want to Miss at GTC 2019

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

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DGX Sessions You Won't Want to Miss at GTC 2019

  2. 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. 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 ADD TO MY SCHEDULE
  4. 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 ADD TO MY SCHEDULE
  5. 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 ADD TO MY SCHEDULE
  6. 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 ADD TO MY SCHEDULE
  7. 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 ADD TO MY SCHEDULE
  8. 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. 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 ADD TO MY SCHEDULE
  10. 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 ADD TO MY SCHEDULE
  11. 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 ADD TO MY SCHEDULE
  12. 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 ADD TO MY SCHEDULE
  13. 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 ADD TO MY SCHEDULE