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id="primary" class="content-area"> <main id="main" class="site-main" role="main"> <div class="cf-posts-with-overrides"> <article id="post-75841" class="post-with-sidebar post-75841 post type-post status-publish format-standard has-post-thumbnail hentry category-enterprise category-supercomputing tag-cuda tag-nvidia-hopper-architecture loop-item-1 for-pagenum-1" data-url="https://blogs.nvidia.com/blog/top500-supercomputers-sc24/" data-identifier="75841 https://blogs.nvidia.com/?p=75841" data-title="The Need for Speed: NVIDIA Accelerates Majority of World’s Supercomputers to Drive Advancements in Science and Technology" > <header class="entry-header"> <div class="inner3">  <h1>The Need for Speed: NVIDIA Accelerates Majority of World’s Supercomputers to Drive Advancements in Science and Technology</h1> <div class="nvb4-subtitle"> <div class="nvb4-subtitle-inner"> Latest TOP500 list reveals 384 systems run on NVIDIA technology, enabling breakthroughs in climate forecasting, drug discovery and quantum simulation. </div> </div> <div class="author_meta"> <span class="entry-date">November 20, 2024</span> <span class="meta-sep">by</span> <span class="author vcard"><a class="url fn n" href="https://blogs.nvidia.com/blog/author/dionharris/" title="View all posts by Dion Harris">Dion Harris</a></span> </div> </div>  <div class="entry-title img-bg orientation-landscape"> <div class="tile-image-wrapper"><img width="1280" height="680" src="https://blogs.nvidia.com/wp-content/uploads/2024/11/hpc-corp-blog-t500-blog-1280x680-1.jpg" class="attachment-medium_large size-medium_large" alt="" decoding="async" fetchpriority="high" srcset="https://blogs.nvidia.com/wp-content/uploads/2024/11/hpc-corp-blog-t500-blog-1280x680-1.jpg 1280w, https://blogs.nvidia.com/wp-content/uploads/2024/11/hpc-corp-blog-t500-blog-1280x680-1-960x510.jpg 960w" sizes="(max-width: 1280px) 100vw, 1280px" /></div> </div> </header>  <div class="entry-meta-social"> <div class="share-count-section"> <span class="share-text"> <span class="icon icon-share"></span> Share </span> </div> <ul class="entry-meta-social-links-list"> <li><a href="https://twitter.com/intent/tweet?text=The Need for Speed: NVIDIA Accelerates Majority of World’s Supercomputers to Drive Advancements in Science and Technology https%3A%2F%2Fblogs.nvidia.com%2Fblog%2Ftop500-supercomputers-sc24%2F" class="nvb4-social-share-link for-twitter" target="_blank"> <span class="icon icon-twitter"></span> </a></li><li><a href="https://www.facebook.com/sharer/sharer.php?u=https%3A%2F%2Fblogs.nvidia.com%2Fblog%2Ftop500-supercomputers-sc24%2F" class="nvb4-social-share-link for-facebook" target="_blank"> <span class="icon icon-facebook"></span> </a></li><li><a href="http://news.ycombinator.com/submitlink?u=https%3A%2F%2Fblogs.nvidia.com%2Fblog%2Ftop500-supercomputers-sc24%2F&t=NVIDIA+Accelerates+Majority+of+World%E2%80%99s+Supercomputers+%7C+NVIDIA+Blog" class="nvb4-social-share-link for-hacker-news" target="_blank"> <span class="icon 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id="bsf_rt_marker"></div><p>Starting with the release of CUDA in 2006, NVIDIA has driven advancements in AI and accelerated computing — and the most recent <a target="_blank" href="https://top500.org/lists/top500/2024/11/">TOP500 list</a> of the world’s most powerful supercomputers highlights the culmination of the company’s achievements in the field.</p> <p>This year, 384 systems on the TOP500 list are powered by NVIDIA technologies. Among the 53 new to the list, 87% — 46 systems — are accelerated. Of those accelerated systems, 85% use <a target="_blank" href="https://www.nvidia.com/en-us/data-center/technologies/hopper-architecture/">NVIDIA Hopper GPUs</a>, driving advancements in areas like <a href="https://blogs.nvidia.com/blog/earth-2-nim-simulations/">climate forecasting</a>, <a target="_blank" href="https://nvidianews.nvidia.com/news/nvidia-opens-bionemo-to-scale-digital-biology-for-global-biopharma-and-scientific-industry">drug discovery</a> and <a target="_blank" href="https://nvidianews.nvidia.com/news/nvidia-supercharges-google-quantum-processor-design-with-simulation-of-quantum-device-physics">quantum simulation</a>.</p> <p>Accelerated computing is much more than floating point operations per second (FLOPS). It requires full-stack, application-specific optimization. At SC24 this week, NVIDIA announced the release of <a href="https://blogs.nvidia.com/blog/cupynumeric-gpu-acceleration/">cuPyNumeric</a>, an <a target="_blank" href="https://www.nvidia.com/en-us/technologies/cuda-x/">NVIDIA CUDA-X</a> library that enables over 5 million developers to seamlessly scale to powerful computing clusters without modifying their Python code.</p> <p>At the conference, NVIDIA also revealed significant updates to the <a target="_blank" href="https://developer.nvidia.com/blog/nvidia-partners-accelerate-quantum-breakthroughs-with-ai-supercomputing/">NVIDIA CUDA-Q</a> development platform, which empowers quantum researchers to simulate quantum devices at a scale previously thought computationally impossible.</p> <h2><b>A New Era of Scientific Discovery With Mixed Precision and AI</b></h2> <p>Mixed-precision floating-point operations and AI have become the tools of choice for researchers grappling with the complexities of modern science. They offer greater speed, efficiency and adaptability than traditional methods, without compromising accuracy.</p> <p>This shift isn’t just theoretical — it’s already happening. At SC24, two Gordon Bell finalist projects revealed how using AI and mixed precision helped advance genomics and protein design.</p> <p>In his paper titled “Using Mixed Precision for Genomics,” David Keyes, a professor at King Abdullah University of Science and Technology, used 0.8 exaflops of mixed precision to explore relationships between genomes and their generalized genotypes, and then to the prevalence of diseases to which they are subject.</p> <p>Similarly, Arvind Ramanathan, a computational biologist from the Argonne National Laboratory, harnessed 3 exaflops of AI performance on the NVIDIA Grace Hopper-powered Alps system to speed up protein design.</p> <p>To further advance AI-driven drug discovery and the development of lifesaving therapies, researchers can use <a target="_blank" href="https://www.nvidia.com/en-us/clara/biopharma/">NVIDIA BioNeMo</a>, powerful tools designed specifically for pharmaceutical applications. Now in open source, the <a target="_blank" href="https://nvidianews.nvidia.com/news/nvidia-opens-bionemo-to-scale-digital-biology-for-global-biopharma-and-scientific-industry">BioNeMo Framework</a> can accelerate AI model creation, customization and deployment for drug discovery and molecular design.</p> <p>Across the TOP500, the widespread use of AI and mixed-precision floating-point operations reflects a global shift in computing priorities. A total of 249 exaflops of AI performance are now available to TOP500 systems, supercharging innovations and discoveries across industries.</p> <figure id="attachment_75842" aria-describedby="caption-attachment-75842" style="width: 960px" class="wp-caption aligncenter"><a href="https://blogs.nvidia.com/wp-content/uploads/2024/11/image1-1.png"><img decoding="async" class="size-medium wp-image-75842" src="https://blogs.nvidia.com/wp-content/uploads/2024/11/image1-1-960x644.png" alt="" width="960" height="644" srcset="https://blogs.nvidia.com/wp-content/uploads/2024/11/image1-1-960x644.png 960w, https://blogs.nvidia.com/wp-content/uploads/2024/11/image1-1.png 1226w" sizes="(max-width: 960px) 100vw, 960px" /></a><figcaption id="caption-attachment-75842" class="wp-caption-text">TOP500 total AI, FP32 and FP64 FLOPs by year.</figcaption></figure> <p>NVIDIA-accelerated TOP500 systems excel across key metrics like AI and mix-precision system performance. With over 190 exaflops of AI performance and 17 exaflops of single-precision (FP32), NVIDIA’s accelerated computing platform is the new engine of scientific computing. NVIDIA also delivers 4 exaflops of double-precision (FP64) performance for certain scientific calculations that still require it.</p> <h2><b>Accelerated Computing Is Sustainable Computing</b></h2> <p>As the demand for computational capacity grows, so does the need for sustainability.</p> <p>In the Green500 list of the world’s most energy-efficient supercomputers, systems with NVIDIA accelerated computing rank among eight of the top 10. The JEDI system at EuroHPC/FZJ, for example, achieves a staggering 72.7 gigaflops per watt, setting a benchmark for what’s possible when performance and sustainability align.</p> <p>For climate forecasting, NVIDIA announced at SC24 <a href="https://blogs.nvidia.com/blog/earth-2-nim-simulations/">two new NVIDIA NIM microservices for NVIDIA Earth-2</a>, a digital twin platform for simulating and visualizing weather and climate conditions. The CorrDiff NIM and FourCastNet NIM microservices can accelerate climate change modeling and simulation results by up to 500x.</p> <p>In a world increasingly conscious of its environmental footprint, NVIDIA’s innovations in accelerated computing balance high performance with energy efficiency to help realize a brighter, more sustainable future.</p> <p><i>Watch the replay of NVIDIA’s </i><a target="_blank" href="https://www.nvidia.com/en-us/events/supercomputing/"><i>special address</i></a><i> at SC24 and learn more about the company’s news in the </i><a target="_blank" href="https://nvidianews.nvidia.com/online-press-kit/sc24-news"><i>SC24 online press kit</i></a><i>.</i></p> <p><i>See</i> <a target="_blank" href="https://www.nvidia.com/en-us/about-nvidia/legal-info/"><i>notice</i></a><i> regarding software product information.</i></p> <div class="has-social-placeholder has-content-area" data-url="https://blogs.nvidia.com/blog/top500-supercomputers-sc24/" data-title="The Need for Speed: NVIDIA Accelerates Majority of World’s Supercomputers to Drive Advancements in Science and Technology" data-hashtags="" data-post-id="75841"></div> <footer id="post-footer" class="entry-footer "> <div class="entry-footer-categories"><span class="cat-links">Categories: <a href="https://blogs.nvidia.com/blog/category/enterprise/" rel="category tag">Data Center</a> | <a href="https://blogs.nvidia.com/blog/category/enterprise/supercomputing/" rel="category tag">Supercomputing</a></span></div><div class="entry-footer-tags"><span class="tags-links">Tags: <a href="https://blogs.nvidia.com/blog/tag/cuda/" rel="tag">CUDA</a> | <a href="https://blogs.nvidia.com/blog/tag/nvidia-hopper-architecture/" rel="tag">NVIDIA Hopper Architecture</a></span></div><div id="disqus_thread"></div> </footer> </div> <div id="secondary" class="single-latest-news-widget-area" role="complementary"> <aside id="nvb5_subscribe_widget-2" class="widget NVB5_Subscribe_Widget"> <div class="subscribe-wrapper"> <img 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