AWS and NVIDIA collaborate to launch 65 ExaFLOP AI supercomputer and innovative solutions.

Amazon Web Services (AWS) and nVidia have announced an expanded collaboration to provide advanced infrastructure, software, and services for generative artificial intelligence (AI) innovations. The partnership will combine NVIDIA’s latest multi-node systems with AWS technologies such as the Nitro System, Elastic Fabric Adapter (EFA) interconnect, and UltraCluster scalability. These technologies are ideal for training foundation models and building generative AI applications.

As part of the collaboration, AWS will be the first cloud provider to offer NVIDIA GH200 Grace Hopper Superchips with new multi-node NVLink technology on its Amazon Elastic Compute Cloud (Amazon EC2) instances. This platform, supported by advanced virtualization and powerful networking capabilities, will allow joint customers to scale their generative AI workloads to thousands of GH200 Superchips.

Furthermore, NVIDIA and AWS will collaborate to host NVIDIA DGX Cloud, an AI-training-as-a-service platform, on AWS. This will be the first DGX Cloud featuring GH200 NVL32, providing developers with access to the largest shared memory in a single instance. The platform will accelerate the training of generative AI and large language models.

The two companies are also partnering on Project Ceiba to design the world’s fastest GPU-powered AI supercomputer. This supercomputer, featuring 16,384 NVIDIA GH200 Superchips and capable of processing 65 exaflops of AI, will be hosted by AWS for NVIDIA’s research and development team.

In addition to these initiatives, AWS will introduce three new Amazon EC2 instances powered by NVIDIA GPUs. The P5e instances, powered by NVIDIA H200 Tensor Core GPUs, are designed for large-scale generative AI and high-performance computing workloads. The G6 and G6e instances, powered by NVIDIA L4 and L40S GPUs respectively, are suitable for a wide range of applications including AI fine-tuning, inference, graphics, and video workloads.

Overall, this expanded collaboration between AWS and NVIDIA aims to supercharge generative AI across industries by combining the best technologies from both companies. With these advancements, developers will have access to powerful infrastructure and software to drive the next wave of AI innovation.

Background Information

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About nVidia:

NVIDIA has firmly established itself as a leader in the realm of client computing, continuously pushing the boundaries of innovation in graphics and AI technologies. With a deep commitment to enhancing user experiences, NVIDIA's client computing business focuses on delivering solutions that power everything from gaming and creative workloads to enterprise applications. for its GeForce graphics cards, the company has redefined high-performance gaming, setting industry standards for realistic visuals, fluid frame rates, and immersive experiences. Complementing its gaming expertise, NVIDIA's Quadro and NVIDIA RTX graphics cards cater to professionals in design, content creation, and scientific fields, enabling real-time ray tracing and AI-driven workflows that elevate productivity and creativity to unprecedented heights. By seamlessly integrating graphics, AI, and software, NVIDIA continues to shape the landscape of client computing, fostering innovation and immersive interactions in a rapidly evolving digital world.

  

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Technology Explained

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AWS: Amazon Web Services (AWS) is a cloud platform powered by Amazon that enables users to access cloud computing services, such as storage, data analytics, and distributed computing. It offers users the ability to utilize both on-demand and pay-as-you-go computing services, making it a great option for the computer industry. It offers a wide range of services with great flexibility for a variety of uses. It can help companies build powerful web and mobile applications, run large-scale analytics, quickly provision servers and other services, design sophisticated architectures for data storage, and more. AWS provides access to a wide range of services such as virtualization, storage, database, monitoring, analytics, and other services that can help organizations increase agility, manage complexity, and remain on the cutting edge of technology. Many big and famous organizations use AWS services to give them a competitive edge, and more and more companies are turning to this service for their computer needs.

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EC2: Amazon EC2 (Elastic Compute Cloud) is a cloud service provided by Amazon Web Services (AWS). It is a virtual computing environment that allows users to rent or lease an online server, compute power, storage, and other computing resources. EC2 is a highly reliable, cost-effective, easily scalable, and quickly available cloud computing service that allows users to deploy and configure their own computing resources. It has helped businesses around the world to quickly and securely scale their operations, while minimizing IT costs, enabling them to spin up virtual servers in minutes without having to worry about provisioning, maintaining, or managing hardware. Its ease of use and reliable performance has made it an attractive choice for businesses that require a fast, seamless computing solution. EC2 can be used for a wide range of applications, from big data analysis, precise medical imaging, machine learning, or web and mobile app development to 3D rendering, simulation, and gaming.

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GPU: GPU stands for Graphics Processing Unit and is a specialized type of processor designed to handle graphics-intensive tasks. It is used in the computer industry to render images, videos, and 3D graphics. GPUs are used in gaming consoles, PCs, and mobile devices to provide a smooth and immersive gaming experience. They are also used in the medical field to create 3D models of organs and tissues, and in the automotive industry to create virtual prototypes of cars. GPUs are also used in the field of artificial intelligence to process large amounts of data and create complex models. GPUs are becoming increasingly important in the computer industry as they are able to process large amounts of data quickly and efficiently.

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