NVIDIA introduces Eos, a powerful data-center-scale supercomputer with 18.4 exaflops of FP8 AI performance, equipped with 4,608 H100 Tensor Core GPUs and optimized for ultra-low-latency and high-throughput interconnectivity, showcasing their commitment to advancing AI technology and providing a crucial resource for enterprises and developers seeking to harness the power of AI.
- NVIDIA's latest data-center-scale supercomputer, Eos, boasts an impressive 18.4 exaflops of FP8 AI performance.
- Eos is equipped with 4,608 NVIDIA H100 Tensor Core GPUs, making it capable of handling even the most demanding AI workloads.
- Eos's architecture is specifically optimized for AI workloads, making it an ideal solution for enterprises looking to scale their AI capabilities.
nVidia, the tech giant known for its advancements in artificial intelligence (AI), has launched its latest data-center-scale supercomputer, Eos. In a newly released video, NVIDIA provides a glimpse into the architecture that powers advanced AI factories.
Eos, an impressive NVIDIA DGX SuperPOD, serves as a hub for NVIDIA developers to create AI innovations using accelerated computing infrastructure and optimized software. With its 576 NVIDIA DGX H100 systems and NVIDIA Quantum-2 InfiniBand networking and software, Eos boasts a remarkable 18.4 exaflops of FP8 AI performance. The supercomputer was first revealed at the Supercomputing 2023 trade show and was aptly named after the Greek goddess who opens the gates of dawn each day—an homage to NVIDIA’s commitment to advancing AI technology.
Each DGX H100 system within Eos is equipped with eight NVIDIA H100 Tensor Core GPUs, resulting in a total of 4,608 H100 GPUs. This immense computational power allows Eos to handle even the most demanding AI workloads, from training large language models to running quantum simulations. Eos serves as a testament to the capabilities of NVIDIA’s technologies when operating at scale.
The timing of Eos’s arrival couldn’t be more perfect. Generative AI has become a driving force behind transformative advancements across various fields, including drug discovery, chatbots, and autonomous machines. However, achieving these breakthroughs requires more than just AI expertise and development skills. What’s needed is an AI factory—an AI engine purpose-built to provide constant availability and support for building AI models at scale. Eos fulfills this need.
Eos has already made its mark on the world stage, ranking an impressive No. 9 in the TOP 500 list of the world’s fastest supercomputers. By pushing the boundaries of AI technology and infrastructure, Eos showcases NVIDIA’s commitment to driving the field forward. The supercomputer incorporates advanced accelerated computing and networking technologies, complemented by sophisticated software products like NVIDIA Base Command and NVIDIA AI Enterprise.
Eos’s architecture is specifically optimized for AI workloads that demand ultra-low-Latency and high-throughput interconnectivity across a large cluster of accelerated computing nodes. This makes it an ideal solution for enterprises looking to scale their AI capabilities. Powered by NVIDIA Quantum-2 InfiniBand with In-Network Computing technology, Eos’s network architecture enables data transfer speeds of up to 400 Gb/s, facilitating the rapid movement of large datasets crucial for training complex AI models.
At the core of Eos lies the DGX SuperPOD architecture, fueled by NVIDIA’s DGX H100 systems. This architecture provides the AI and computing fields with fully integrated full-stack systems capable of computing at an enormous scale. As enterprises and developers worldwide seek to harness the power of AI, Eos stands as a pivotal resource, promising to accelerate the journey towards AI-infused applications that drive innovation in every organization.
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Background Information
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.Latest Articles about nVidia
Technology Explained
Exaplops: Exaflops is a unit of measurement used to describe the computational power of a supercomputer or a high-performance computing system. It represents the ability to perform one quintillion (10^18) floating-point operations per second, which is an enormous amount of computational throughput. Achieving exaflops-level performance is a significant milestone in the field of computing and enables scientists, researchers, and engineers to tackle complex problems and simulations at unprecedented scales and speeds.
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Latency: Technology latency is the time it takes for a computer system to respond to a request. It is an important factor in the performance of computer systems, as it affects the speed and efficiency of data processing. In the computer industry, latency is a major factor in the performance of computer networks, storage systems, and other computer systems. Low latency is essential for applications that require fast response times, such as online gaming, streaming media, and real-time data processing. High latency can cause delays in data processing, resulting in slow response times and poor performance. To reduce latency, computer systems use various techniques such as caching, load balancing, and parallel processing. By reducing latency, computer systems can provide faster response times and improved performance.
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Petaflops: Petaflops is a measure of computing speed, specifically one quadrillion floating-point operations per second. This technology is used to measure the performance of supercomputers, which are extremely powerful computers used for complex calculations and simulations. Petaflops technology has revolutionized the computer industry by allowing for faster and more efficient processing of large amounts of data. This has enabled advancements in fields such as weather forecasting, climate modeling, and drug discovery. Petaflops technology has also been utilized in artificial intelligence and machine learning, allowing for more accurate and sophisticated algorithms. In simpler terms, Petaflops is like a race car for computers, allowing them to process information at lightning-fast speeds and tackle complex problems that were previously impossible to solve.
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Tensor Cores: Tensor Cores are a type of specialized hardware designed to accelerate deep learning and AI applications. They are used in the computer industry to speed up the training of deep learning models and to enable faster inference. Tensor Cores are capable of performing matrix operations at a much faster rate than traditional CPUs, allowing for faster training and inference of deep learning models. This technology is used in a variety of applications, including image recognition, natural language processing, and autonomous driving. Tensor Cores are also used in the gaming industry to improve the performance of games and to enable more realistic graphics.
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Teraflops: Teraflops, or trillion floating point operations per second, is a measure of computing speed and power. It is used to describe the performance of supercomputers and high-end computer processors. To put it simply, a teraflop is equivalent to one trillion calculations per second. This incredible speed allows for complex and data-intensive tasks to be completed in a fraction of the time it would take a regular computer. In the computer industry, teraflops are used for a variety of applications such as weather forecasting, scientific research, and artificial intelligence. They also play a crucial role in the development of advanced video games and virtual reality experiences. With the continuous advancement of technology, the use of teraflops is expected to increase, leading to even faster and more efficient computing capabilities.
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