As businesses and technology change rapidly, the complexity of the workloads has dramatically increased, leading to an ever-increasing need for more power. Many of these workloads require the ability to both scale up and scale out their infrastructure to meet more complex needs and ambiguity. To solve your most complex and innovative workloads, Azure has the infrastructure you need with the power of the world’s largest supercomputer, the versatility of the cloud, and the security you expect.
This year’s Spring NVIDIA GTC event is virtual, and we have pulled out all the stops. With 21 Microsoft sessions hitting across 11 topics and 8 key industries, you’re bound to find the topic you’ve been waiting for.
Attend sessions to get a chance to win a Jetson Nano
Two of our sessions give you the chance to win a SWAG box, complete with an HPC T-shirt and Jetson Nano. Didn’t win? We’re also giving out special SWAG boxes until supplies run out. So, what are you waiting for? Attend these sessions and don’t forget to look for the special link to enter.
Supercomputer Performance, Meet Cloud Versatility
Nidhi Chappell Head of product, Azure HPC/AI Microsoft John Montgomery Corporate Vice President Program Management, Azure AI- Microsoft
The Azure platform enables a new era of innovative applications and services that leverage the versatility of the cloud with the power of supercomputing performance. The convergence of HPC and AI is a revolution, bringing dramatic acceleration to every kind of simulation, and advancing fields across science and industry. Whether you need to scale to 80K+ cores for your MPI-based workloads, or you are looking for AI supercomputing capabilities Azure can support your needs with all of the versatility of the cloud.
In this session we will provide an overview of the Azure HPC + AI, Confidential Computing, and AI platforms, reviewing recent accomplishments and cover in detail how these portfolios can support your accelerator workload needs ranging from AI inferencing to machine learning and more.
Unlocking new possibilities for privacy-preserving data analytics with Azure confidential computing
Mark Russinovich Azure CTO and Technical Fellow Microsoft; Ian Buck, Vice President and General Manager of Accelerated Computing, NVIDIA
In this session, Microsoft Azure CTO and Technical Fellow Mark Russinovich and NVIDIA Data Center VP Ian Buck discuss how Microsoft and Nvidia are partnering together to integrate latest GPU technology with Azure confidential computing to help customers process large data workloads such as AI/ML, multi-party analytics, and 3D rendering, while keeping data private and secure. Currently, there is no comparable offering in the marketplace, and Azure is driving first to market with this game changing technology in our quest to be the most secure cloud.
We’ll meet you at GTC
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Session ID |
Session Title |
Speakers |
Primary Topic |
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Azure AI Supercomputing VMs: AI at any scale |
Vijay Kanchanahalli, Principal Program Manager, Microsoft; Sherry Wang, Sr. Program Manager, Azure HPC and AI Microsoft |
AI Strategy for Business Leaders |
|
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Train and deploy a Kaggle-winning transformer model for less than $50 with PyTorch on Azure |
Alon Bochman, Principal Program Manager, Microsoft |
Data Center / Cloud Infrastructure – Technical |
|
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Bringing DevOps principles to the ML workflow to facilitate bringing ML to production |
Osarumwense Omorogbe, Program Manager II, Microsoft |
HPC – Supercomputing |
|
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Transforming AI and ML at the Edge with Microsoft and NVIDIA |
Christa St Pierre Group Manager, Azure Edge, Microsoft |
IoT / 5G / Edge |
|
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Accelerated compute on all of your PCs with Azure IoT Edge for Linux on Windows |
Jason Farmer, Principal Program Manager, Microsoft |
IoT / 5G / Edge |
|
|
S42529 |
Breaking down the power of confidential GPUs |
Antoine Delignat-Lavaud, Principal Researcher Microsoft Research; Kapil Vaswani, Principal Researcher, Microsoft Research; Vikas Bhatia, Head of Product for Azure Confidential Computing (ACC), Microsoft |
Data Center / Cloud Infrastructure – Technical |
|
Largest models are not always expensive: Large Scale Mixture of Expert models with efficient inference empowers Microsoft Translator with best models |
Young Jin Kim, Principal Researcher, Microsoft; Rawn Henry, Senior AI Developer Technology Engineer, NVIDIA |
Conversational AI / NLP |
|
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Using NVIDIA GPU accelerated Spark with Rapids on Azure Synapse |
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Setting HPC and Deep-learning Records in the Cloud with Azure |
Jon Shelley, HPC/AI Benchmarking Team, Principal PM Manager, Azure Compute Microsoft; Edwin Weill, Solutions Architect and Data Scientist, NVIDIA |
Data Center / Cloud Infrastructure - Technical |
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CAD in the Cloud: Engineering and Simulation Software on Microsoft Azure |
Gauhar Junnarkar, Senior Program Manager, Microsoft |
Product Development - Design, Engineering and Manufacturing |
|
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Accelerate Autonomous Vehicle Development with NVIDIA DRIVE on Microsoft Azure |
Adithya Ranga, Senior Program Manager, Microsoft Corporation |
Autonomous Vehicles |
