Accelerated computing is supercharging AI and data processing workloads, helping enterprises across industries achieve greater efficiency with reduced time and costs.
For over a decade, NVIDIA has worked with Amazon Web Services (AWS) to bring accelerated computing to businesses and developers around the world.
At AWS re:Invent 2024, taking place Dec. 2-6 in Las Vegas, NVIDIA’s full-stack offerings will be on display. Attendees can take a deep dive into the broad range of NVIDIA hardware and software platforms available on AWS and learn how partners and customers use them to accelerate their most compute-intensive workloads.
Highlights from the session catalog include:
- “NVIDIA Accelerated Computing Platform on AWS” with Dave Salvator, director of accelerated computing products at NVIDIA (AIM110-S)
- “Build, Customize and Deploy Generative AI With NVIDIA on AWS” with Abhishek Sawarkar, product manager at NVIDIA, and Charlie Huang, senior product marketing at NVIDIA (AIM241-S)
- “Advancing Physical AI: NVIDIA Isaac Lab and AWS for Next-Gen Robotics” with Rishabh Chadha, technical marketing engineer at NVIDIA; Abhishek Srivastav, senior solutions architect at AWS; and Shaun Kirby, principal enterprise architect at AWS (AIM113-S)
- “NVIDIA AI Startups: Innovations in Action” with Jen Hoskins, global head of Inception cloud partnerships and go-to-market at NVIDIA, and speakers from Inception startups, including Bria, Contextual AI, Hippocratic AI, Mendel AI, Twelve Labs and Writer (AIM121-S)
- “AI-Driven Value: Capital One’s Path to Better Customer Experience” with Joey Conway, senior director of product management for large language model software at NVIDIA, and Prem Natarajan, chief scientist and head of enterprise AI at Capital One (AIM130-S)
- “Accelerate Apache Spark Up to 5 Times on AWS With RAPIDS” with Sameer Raheja, senior director of engineering at NVIDIA (ANT208-S)
For a more hands-on experience, join an AWS Jam session and workshops:
- AWS Jam: Building a RAG Chat Agent With NVIDIA NIM (GHJ305)
- Robotic Simulation With NVIDIA Isaac Lab on AWS Batch (MFG319)
- Unleash Edge Computing With AWS IoT Greengrass on NVIDIA Jetson (IOT316)
- Building Scalable Drug Discovery Applications With NVIDIA BioNeMo (HLS205)
- Creating Immersive 3D Digital Twins From Photos, Videos and LiDAR With NVIDIA Omniverse (CMP315)
NVIDIA booth 1620 will feature a variety of demos, including a full NVIDIA GB200 NVL72 rack, coming soon to Amazon Elastic Compute Cloud (Amazon EC2) and NVIDIA DGX Cloud, as well as Spot, an agile mobile robot from Boston Dynamics.
Other demos showcasing the NVIDIA platform on AWS include:
- Powering Digital Twins and Physical AI With NVIDIA Omniverse
- Deploying Generative AI Faster With NVIDIA NIM
- Speed Deployment of AI With NVIDIA AI Blueprints, Including Generative Virtual Screening for Accelerated Drug Discovery
- The NVIDIA Accelerated Computing Platform on AWS, Hardware Show-and-Tell
- Fraud Prevention Reference Architecture on RAPIDS With AWS
NVIDIA will also feature demos from select partners and customers, including startups Balbix, Bria, Mendel AI, Standard Bots, Union and Writer.
Attendees can learn more about NVIDIA’s full-stack accelerated computing platform on AWS, including three new Amazon EC2 instance types released this year: Amazon EC2 P5e instances (NVIDIA H200 Tensor Core GPUs) for large-scale AI training and inference, G6e instances (NVIDIA L40S GPUs) for AI and graphics, and G6 instances (NVIDIA L4 Tensor Core GPUs) for small model deployments.
Plus, discover how NVIDIA’s GPU-optimized software stack delivers high performance across AWS services, making it easy for developers to accelerate their applications in the cloud. Some examples include:
- Generative AI: NVIDIA NeMo and NIM microservices, part of the NVIDIA AI Enterprise software platform and available in AWS Marketplace, for building, customizing and deploying generative AI on Amazon EC2, Amazon SageMaker and Amazon Elastic Kubernetes Service (EKS).
- Digital Twins and Physical AI: NVIDIA Earth-2 weather simulation on AWS and NVIDIA Isaac Sim and Isaac Lab for robot simulation and learning using AWS Batch.
- Healthcare: NVIDIA BioNeMo for drug discovery applications, including an NVIDIA AI Blueprint for virtual screening and NIM microservices for protein prediction and small molecule generation, supported on AWS Healthomics.
- Data Processing: RAPIDS Accelerator for Apache Spark for accelerating analytic and machine learning workloads, available on Amazon EMR, Amazon EC2 and Amazon EMR on EKS.
- Edge AI: NVIDIA Jetson with AWS IoT Greengrass for streamlined experiences to deploy generative AI models and manage fleets of connected edge devices and robots.
Members of the NVIDIA Inception program for cutting-edge startups are already testing, developing and deploying their most challenging workloads using the NVIDIA platform on AWS:
- Twelve Labs achieved up to a 7x inference improvement in requests served per second when upgrading to NVIDIA H100 Tensor Core GPUs. Its Marengo and Pegasus models, soon available as NIM microservices, power video Al solutions that enable semantic search on embedded enterprise video archives.
- Wiz doubled inference throughput speed for DSPM data classification using NIM microservices over alternatives.
- Writer achieved 3x faster model iteration cycles using SageMaker HyperPod with NVIDIA H100 GPUs. With NVIDIA accelerated computing and AWS, Writer optimized the training and inference of its Palmyra models, significantly reducing time to market for its customers.
Inception helps startups evolve faster by offering the latest NVIDIA technologies, opportunities to connect with venture capitalists, and access to technical resources and experts.
Register for AWS re:Invent to see how businesses can speed up their generative AI and data processing workloads with NVIDIA accelerated computing on AWS.
Send an email to schedule a meeting with NVIDIA experts at the show.