This post has been republished via RSS; it originally appeared at: Azure Compute articles.
Despite being converted into a digital-only event, this year’s GTC is certain not to disappoint. The big buzz around cloud-based GPUs is the introduction of deep learning and AI capabilities complimentary to existing visualization, rendering, and gaming workflows. Having on-demand versatility by which GPUs can be consumed and transacted empowers greater productivity and efficiency with enhanced VDI/DaaS, real-time visualizations, and more immersive gaming & entertainment experiences.
This year we are sharing examples of some of the most versatile GPU-powered resources anywhere in the public cloud, with a clear understanding of maximum cost-for-performance metrics. We’re focusing on three main application use cases for GPUs:
- Visualization, including 3D design rendering, remote rendering, and desktop virtualization
- AI for machine learning, model training and inferencing
- Edge Computing for hybrid scenarios, decoupled environments, and IoT device ecosystems
Microsoft Digital Sessions at NVIDIA GTC
Microsoft will be supporting the following pre-recorded sessions at GTC Digital this year. Please note that all session content will be posted and available for consumption by Thursday March 26th, 2020.
|
SESSION |
SPEAKER(S) |
|
Microsoft open sources breakthrough optimizations for large scale BERT Models |
Emma Ning Nathan Yan |
|
Enabling Workloads Using High-End Graphics through Windows Virtual Desktop |
Manvender Rawat Denis Gundarev |
|
Deploying your Models to GPU with ONNX Runtime for Inferencing in Cloud & Edge Endpoints |
Manash Goswami Kundana Palagiri |
|
Speed Up Your Data Science Tasks by a Factor of 100+ Using AzureML & NVIDIA RAPIDS |
Daniel Schneider Cody Peterson Tom Drabas |
|
Paul DeCarlo Ian Davis |
|
|
Emma Ning Spandan Tiwari |
|
|
Accelerated Machine Learning at Scale with NVIDIA RAPIDS on Microsoft Azure |
Tom Drabas |
|
David Aronchick |
|
|
Jaliya Ekanayake |
|
|
Visual Anomaly Detection using NVIDIA DeepStream with Azure IoT |
Paul DeCarlo Emmanuel Bertrand Ian Davis |
|
Yuxiong He Samyam Rajbhandari |
|
| Edge Computing for building Machine Learning pipelines using Azure Stack
|
Kirtana Venkatraman Mahesh Yadav Garvita Rai |
NVIDIA DLI Training Powered by Azure
Microsoft is proud to host the NVIDIA DLI instructor-led online training covering AI, accelerated computing, and accelerated data science all powered on Microsoft Azure.
This year’s GTC event is shaping up to mark a major leap forward in how GPUs are utilized for modern application & service development workflows.