AWS Machine Learning Blog
Save the date: Join AWS at NVIDIA GTC, September 19–22
Register free for NVIDIA GTC to learn from experts on how AI and the evolution of the 3D internet are profoundly impacting industries—and society as a whole. We have prepared several AWS sessions to give you guidance on how to use AWS services powered by NVIDIA technology to meet your goals. Amazon Elastic Compute Cloud (Amazon EC2) instances powered by NVIDIA GPUs deliver the scalable performance needed for fast machine learning (ML) training, cost-effective ML inference, flexible remote virtual workstations, and powerful HPC computations.
AWS is a Global Diamond Sponsor of the conference.
Scaling Deep Learning Training on Amazon EC2 using PyTorch (Presented by Amazon Web Services) [A41454]
As deep learning models grow in size and complexity, they need to be trained using distributed architectures. In this session, we review the details of the PyTorch fully sharded data parallel (FSDP) algorithm, which enables you to train deep learning models at scale.
- Tuesday, September 20, at 2:00 PM – 2:50 PM PDT
- Speakers: Shubha Kumbadakone, Senior GTM Specialist, AWS ML, AWS; and Less Wright, Partner Engineer, Meta
A Developer’s Guide to Choosing the Right GPUs for Deep Learning (Presented by Amazon Web Services) [A41463]
As a deep learning developer or data scientist, choosing the right GPU for deep learning can be challenging. On AWS, you can choose from multiple NVIDIA GPU-based EC2 compute instances depending on your training and deployment requirements. We dive into how to choose the right instance for your needs in this session.
- Available on demand
- Speaker: Shashank Prasanna, Senior Developer Advocate, AI/ML, AWS
Real-time Design in the Cloud with NVIDIA Omniverse on Amazon EC2 (Presented by Amazon Web Services) [A4631]
In this session, we discuss how, by deploying NVIDIA Omniverse Nucleus—the Universal Scene Description (USD) collaboration engine—on EC2 On-Demand compute instances, Omniverse is able to scale to meet the demands of global teams.
- Available on demand
- Speaker: Kellan Cartledge, Spatial Computing Solutions Architect, AWS
5G Killer App: Making Augmented and Virtual Reality a Reality [A41234]
Extended reality (XR), which comprises augmented, virtual, and mixed realities, is consistently envisioned as one of the key killer apps for 5G, because XR requires ultra-low latency and large bandwidths to deliver wired-equivalent experiences for users. In this session, we share how Verizon, AWS, and Ericsson are collaborating to combine 5G and XR technology with NVIDIA GPUs, RTX vWS, and CloudXR to build the infrastructure for commercial XR services across a variety of industries.
- Tuesday, September 20, at 1:00 PM – 1:50 PM PDT
- Speakers: David Randle, Global Head of GTM for Spatial Computing, AWS; Veronica Yip, Product Manager and Product Marketing Manager, NVIDIA; Balaji Raghavachari, Executive Director, Tech Strategy, Verizon; and Peter Linder, Head of 5G Marketing, North America, Ericsson
Accelerate and Scale GNNs with Deep Graph Library and GPUs [A41386]
Graphs play important roles in many applications, including drug discovery, recommender systems, fraud detection, and cybersecurity. Graph neural networks (GNNs) are the current state-of-the-art method for computing graph embeddings in these applications. This session discusses the recent improvements of the Deep Graph Library on NVIDIA GPUs in the DGL 0.9 release cycle.
- Wednesday, September 21, at 2:00 PM – 2:50 PM PDT
- Speaker: Da Zheng, Senior Applied Scientist, AWS
|Register for free for access to this content, and be sure to visit our sponsor page to learn more about AWS solutions powered by NVIDIA. See you there!|
About the author
Jeremy Singh is a Partner Marketing Manager for storage partners within the AWS Partner Network. In his spare time, he enjoys traveling, going to the beach, and spending time with his dog Bolin.