{"id":4353,"date":"2025-11-17T23:39:44","date_gmt":"2025-11-17T23:39:44","guid":{"rendered":"https:\/\/salarydistribution.com\/machine-learning\/2025\/11\/17\/nvidia-accelerates-ai-for-over-80-new-science-systems-worldwide\/"},"modified":"2025-11-17T23:39:44","modified_gmt":"2025-11-17T23:39:44","slug":"nvidia-accelerates-ai-for-over-80-new-science-systems-worldwide","status":"publish","type":"post","link":"https:\/\/salarydistribution.com\/machine-learning\/2025\/11\/17\/nvidia-accelerates-ai-for-over-80-new-science-systems-worldwide\/","title":{"rendered":"NVIDIA Accelerates AI for Over 80 New Science Systems Worldwide"},"content":{"rendered":"<div>\n\t\t<span class=\"bsf-rt-reading-time\"><span class=\"bsf-rt-display-label\"><\/span> <span class=\"bsf-rt-display-time\"><\/span> <span class=\"bsf-rt-display-postfix\"><\/span><\/span><\/p>\n<p>Across quantum physics, digital biology and climate research, the world\u2019s researchers are harnessing a universal scientific instrument to chart new frontiers of discovery: accelerated computing.<\/p>\n<p>At this week\u2019s <a target=\"_blank\" href=\"https:\/\/sc25.supercomputing.org\/\" rel=\"noopener\">SC25<\/a> conference in St. Louis, Missouri, NVIDIA announced that over 80 new scientific systems powered by the NVIDIA accelerated computing platform have been unveiled around the globe in the last year, contributing to a combined total of 4,500 exaflops of AI performance.<\/p>\n<p>Newest among them is America\u2019s largest academic supercomputer: the 300-petaflop Horizon system at the Texas Advanced Computing Center (TACC).<\/p>\n<p>Slated to be powered by NVIDIA GB200 NVL4 and NVIDIA Vera CPU servers, interconnected with NVIDIA Quantum-X800 InfiniBand networking, Horizon is set to accelerate breakthroughs in science and engineering when it comes online in 2026, offering the nation\u2019s research community unprecedented computing capabilities for discovery and innovation.<\/p>\n<p>It\u2019s the latest in a new wave of NVIDIA-accelerated supercomputers fueling global research by nations and private companies in areas such as healthcare, weather and climate modeling, robotics, manufacturing, quantum computing research and materials science.<\/p>\n<p>NVIDIA\u2019s full-stack accelerated computing platform \u2014 spanning GPUs, CPUs, DPUs, NICs, scale-out switches, as well as CUDA-X libraries and NVIDIA AI Enterprise software \u2014 provides the unified architecture, scale and efficiency these systems need to advance science sustainably and at unprecedented speed.<\/p>\n<h2><b>Scientific Innovation on the Horizon for TACC<\/b><\/h2>\n<p>With 4,000 NVIDIA Blackwell GPUs, the Horizon supercomputer can deliver up to 80 exaflops of AI compute at FP4 precision. It was designed to support a specific set of scientific modeling and simulation applications, including:\u00a0<b><\/b><\/p>\n<ul>\n<li><b>Simulating the mechanics of disease: <\/b>Researchers plan to use molecular dynamics software and AI-enhanced simulations to study viruses.<\/li>\n<li><b>Modeling stars and galaxies across the universe: <\/b>Astrophysicists plan to explore how stars and galaxies form \u2014 and simulate distant galaxies uncovered by recent discoveries from the James Webb Space Telescope.<\/li>\n<li><b>Investigating novel materials at atomic scale: <\/b>Scientists plan to study turbulence, solids with complex crystal structures and the conductivity of quantum materials.<\/li>\n<li><b>Mapping seismic waves to prepare for earthquakes: <\/b>Researchers plan to improve seismic hazard maps and simulate how faults rupture during earthquakes.<\/li>\n<\/ul>\n<p>\u201cHorizon will enable our scientists to pursue ambitious scientific research at unprecedented scale,\u201d said John Cazes, director of high-performance computing at TACC. \u201cThis new system will transform how the research community can pursue AI-driven initiatives to decipher the molecular dynamics of viral infections, explore data from distant galaxies and simulate seismic activity decades into the future.\u201d<\/p>\n<\/p>\n<h2><b>Argonne,<\/b> <b>Los Alamos National Laboratories <\/b><b>to House New AI Supercomputers<\/b><\/h2>\n<p>The U.S. Department of Energy (DOE) recently announced a partnership with NVIDIA to build seven new AI supercomputers at Argonne National Laboratory (ANL) in Illinois and Los Alamos National Laboratory (LANL) in New Mexico.<\/p>\n<p>At ANL, two <a target=\"_blank\" href=\"https:\/\/nvidianews.nvidia.com\/news\/nvidia-oracle-us-department-of-energy-ai-supercomputer-scientific-discovery\" rel=\"noopener\">AI supercomputing systems featuring NVIDIA Blackwell GPUs<\/a> and NVIDIA networking will connect with the DOE\u2019s network of scientific instruments and data assets, enabling researchers to develop powerful AI models for science and energy applications.<\/p>\n<p>The largest system in the lab complex, Solstice, will feature 100,000 NVIDIA Blackwell GPUs. A system of that scale featuring NVIDIA GB200 NVL72 systems can reach a staggering 1,000 exaflops of AI training compute for training. That\u2019s over 50% higher than the sum of AI training compute across the entire TOP500 list from June 2025, at around 650 exaflops.<\/p>\n<p>Another ANL system, called Equinox, will be powered by 10,000 NVIDIA Blackwell GPUs. Three more NVIDIA-accelerated systems at the lab \u2014 Minerva, Janus and Tara \u2014 will support AI inference and workforce development.<\/p>\n<p>At LANL, the <a target=\"_blank\" href=\"https:\/\/www.energy.gov\/nnsa\/articles\/nnsa-announces-two-new-supercomputers-los-alamos-national-laboratory-propelling\" rel=\"noopener\">Mission and Vision systems<\/a> \u2014 to be built and delivered by HPE \u2014 will be powered by the NVIDIA Vera Rubin platform and the NVIDIA Quantum-X800 InfiniBand networking platform. Mission will run classified applications for the National Nuclear Security Administration, while Vision will power open science research, including foundation models and agentic AI.<\/p>\n<p>Both are expected to be operational in 2027.<\/p>\n<p>These seven DOE systems follow this year\u2019s announcement with Lawrence Berkeley National Laboratory about <a href=\"https:\/\/blogs.nvidia.com\/blog\/dell-nvidia-berkeley-doudna\/\">Doudna<\/a> \u2014 a supercomputer for scientific discovery set to launch in 2026. Doudna will be powered by the NVIDIA Vera Rubin architecture and NVIDIA Quantum-X800 InfiniBand, and is poised to support the work of over 11,000 researchers across fusion energy, materials science, drug discovery and astronomy.<\/p>\n<h2><b>Europe\u2019s J\u00fclich Supercomputer Breaks Exaflop Barrier on Linpack Benchmark<\/b><\/h2>\n<p>Across the Atlantic, NVIDIA-accelerated supercomputers in Europe \u2014 including systems at the Swiss National Supercomputing Centre and Italy\u2019s CINECA supercomputing center \u2014 are fueling scientific research throughout the continent.<\/p>\n<p>In Germany, the J\u00fclich Supercomputing Centre\u2019s JUPITER system has achieved <a href=\"https:\/\/blogs.nvidia.com\/blog\/what-is-an-exaflop\/\">exaflop<\/a> performance \u2014 calculating 1 quintillion floating point operations per second \u2014 on the HPL benchmark, which measures computing performance on double precision (FP64) math.<\/p>\n<figure id=\"attachment_84476\" aria-describedby=\"caption-attachment-84476\" class=\"wp-caption aligncenter\"><img decoding=\"async\" loading=\"lazy\" class=\"size-full wp-image-84476\" src=\"https:\/\/blogs.nvidia.com\/wp-content\/uploads\/2025\/09\/jupiter-featured-still-1280x680-1.jpg\" alt=\"\" width=\"1280\" height=\"680\"><figcaption id=\"caption-attachment-84476\" class=\"wp-caption-text\">View into a JUPITER rack with compute blades. Image courtesy of Forschungszentrum J\u00fclich \/ Sascha Kreklau.<\/figcaption><\/figure>\n<p><a href=\"https:\/\/blogs.nvidia.com\/blog\/jupiter-exascale-supercomputer-live\/\">JUPITER, inaugurated in September<\/a>, is Europe\u2019s first exascale computer, featuring 24,000 NVIDIA GH200 Grace Hopper Superchips interconnected with NVIDIA Quantum-2 InfiniBand. It\u2019s already in use for applications including high-resolution global climate simulation.<\/p>\n<p>\u201cWith over 1 exaflop of computing power on JUPITER, our researchers can now run global simulations at kilometer-scale resolution,\u201d said Thomas Lippert, director of the J\u00fclich Supercomputing Centre. \u201cThis leap in compute capacity enables European researchers to run AI models and simulations across scientific disciplines at new levels of complexity, size and scale.\u201d<\/p>\n<p><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter size-full wp-image-81884\" src=\"https:\/\/blogs.nvidia.com\/wp-content\/uploads\/2025\/06\/hpc-corp-blog-isc-blue-lion-supercomputer-1280x680-1.jpg\" alt=\"An image of the Blue Lion supercomputer floating against a blue field.\" width=\"1280\" height=\"680\"><\/p>\n<p>Other major European supercomputers unveiled in the past year include:<\/p>\n<ul>\n<li><a href=\"https:\/\/blogs.nvidia.com\/blog\/blue-lion-vera-rubin\/\">Blue Lion<\/a> \u2014\u00a0 Slated to go online in early 2027, this system at Germany\u2019s Leibniz Supercomputing Centre, LRZ, will be powered by the NVIDIA Vera Rubin platform to support researchers working on climate, turbulence, physics and machine learning.<\/li>\n<li><a href=\"https:\/\/blogs.nvidia.com\/blog\/denmark-sovereign-ai-supercomputer\/\">Gefion<\/a> \u2014 Denmark\u2019s first AI supercomputer, operated by DCAI, is an<a target=\"_blank\" href=\"https:\/\/www.nvidia.com\/en-us\/data-center\/dgx-superpod\/\" rel=\"noopener\"> NVIDIA DGX SuperPOD<\/a> providing sovereign AI capacity for the country\u2019s innovators to advance research in areas including quantum computing, clean energy and biotechnology.<\/li>\n<li><a href=\"https:\/\/blogs.nvidia.com\/blog\/isambard-ai\/\">Isambard-AI<\/a> \u2014 The U.K.\u2019s most powerful AI supercomputer, housed at the University of Bristol, is being used for projects including Nightingale AI, a multimodal foundation model trained on National Health Service data, and <a href=\"https:\/\/blogs.nvidia.com\/blog\/uk-llm-nemotron\/\">UK-LLM<\/a>, an initiative to enable high-quality AI reasoning for Welsh and other U.K. languages.<\/li>\n<\/ul>\n<figure id=\"attachment_82024\" aria-describedby=\"caption-attachment-82024\" class=\"wp-caption aligncenter\"><img decoding=\"async\" loading=\"lazy\" class=\"size-full wp-image-82024\" src=\"https:\/\/blogs.nvidia.com\/wp-content\/uploads\/2025\/06\/quantum-computing-corp-blog-ansys-gefion-1280x680-1.png\" alt=\"\" width=\"1280\" height=\"680\"><figcaption id=\"caption-attachment-82024\" class=\"wp-caption-text\">Gefion is Denmark\u2019s first AI supercomputer, consisting of an NVIDIA DGX SuperPOD interconnected with NVIDIA Quantum-2 InfiniBand networking. Image courtesy of DCAI.<\/figcaption><\/figure>\n<h2><b>Supercomputers in Japan, South Korea and Taiwan Fuel Research Across Industries<\/b><\/h2>\n<p>Through <a href=\"https:\/\/blogs.nvidia.com\/blog\/what-is-sovereign-ai\/\">sovereign AI<\/a> investments and private-sector initiatives, NVIDIA-accelerated AI infrastructure is also supporting scientific research in Japan, South Korea and Taiwan.<\/p>\n<p>RIKEN, Japan\u2019s top research institute, announced at SC25 that it is integrating NVIDIA GB200 NVL4 systems in two new supercomputers \u2014 a 1600-GPU system for AI for science and a 540-GPU system for quantum computing.<\/p>\n<figure id=\"attachment_87463\" aria-describedby=\"caption-attachment-87463\" class=\"wp-caption aligncenter\"><img decoding=\"async\" loading=\"lazy\" class=\"wp-image-87463 size-full\" src=\"https:\/\/blogs.nvidia.com\/wp-content\/uploads\/2025\/11\/hpc-corp-blog-sc25-riken-pr-1280x680-2.jpg\" alt=\"\" width=\"1280\" height=\"680\"><figcaption id=\"caption-attachment-87463\" class=\"wp-caption-text\">RIKEN is integrating NVIDIA Blackwell with two new supercomputers in Japan \u2014 one built for AI for science and the other for quantum computing.<\/figcaption><\/figure>\n<p>RIKEN is also working with Fujitsu and NVIDIA to codesign <a href=\"https:\/\/blogs.nvidia.com\/blog\/fugakunext\/\">FugakuNEXT<\/a> (development code name), a supercomputer that will power earth systems modeling, drug discovery research and advanced manufacturing applications. It\u2019ll feature FUJITSU-MONAKA-X CPUs, which can be paired with NVIDIA technologies using <a target=\"_blank\" href=\"https:\/\/nvidianews.nvidia.com\/news\/nvidia-nvlink-fusion-semi-custom-ai-infrastructure-partner-ecosystem\" rel=\"noopener\">NVLink Fusion<\/a>.<\/p>\n<p>Tokyo University of Technology has built an AI supercomputer with <a target=\"_blank\" href=\"https:\/\/www.nvidia.com\/en-us\/data-center\/dgx-b200\/\" rel=\"noopener\">NVIDIA DGX B200<\/a> systems capable of achieving 2 exaflops of FP4 theoretical computing performance with under 100 GPUs. The system will be used to develop large language models and build digital twins to serve as core infrastructure for fostering the next generation of AI talent.<\/p>\n<p>Japan\u2019s National Institute of Advanced Industrial Science and Technology recently launched <a target=\"_blank\" href=\"https:\/\/nvidianews.nvidia.com\/news\/nvidia-powers-worlds-largest-quantum-research-supercomputer\" rel=\"noopener\">ABCI-Q<\/a>, the world\u2019s largest research supercomputer dedicated to quantum computing, featuring over 2,000 NVIDIA H100 GPUs.<\/p>\n<figure id=\"attachment_87458\" aria-describedby=\"caption-attachment-87458\" class=\"wp-caption aligncenter\"><img decoding=\"async\" loading=\"lazy\" class=\"wp-image-87458 size-large\" src=\"https:\/\/blogs.nvidia.com\/wp-content\/uploads\/2025\/11\/aist-quantum-research-supercomputer-1680x1120.jpg\" alt=\"\" width=\"1680\" height=\"1120\"><figcaption id=\"caption-attachment-87458\" class=\"wp-caption-text\">NVIDIA powers ABCI-Q, the world\u2019s largest research supercomputer dedicated to quantum computing. Image courtesy of AIST G-QuAT.<\/figcaption><\/figure>\n<p>The South Korean government plans to deploy <a target=\"_blank\" href=\"https:\/\/nvidianews.nvidia.com\/news\/south-korea-ai-infrastructure\" rel=\"noopener\">over 50,000 NVIDIA GPUs across sovereign clouds and AI factories<\/a>. Industry leaders <a target=\"_blank\" href=\"https:\/\/nvidianews.nvidia.com\/news\/samsung-ai-factory\" rel=\"noopener\">Samsung<\/a>, <a target=\"_blank\" href=\"https:\/\/nvidianews.nvidia.com\/news\/sk-group-ai-factory\" rel=\"noopener\">SK Group<\/a> and <a target=\"_blank\" href=\"https:\/\/nvidianews.nvidia.com\/news\/hyundai-motor-group-ai-factory\" rel=\"noopener\">Hyundai Motor Group<\/a> are also building AI factories with NVIDIA Blackwell GPUs to accelerate research and manufacturing.<\/p>\n<p>And in Taiwan, NVIDIA is working with <a target=\"_blank\" href=\"https:\/\/nvidianews.nvidia.com\/news\/foxconn-ai-factory-tsmc-taiwan-nvidia\" rel=\"noopener\">Foxconn Hon Hai Technology group<\/a> to build an AI factory supercomputer with 10,000 NVIDIA Blackwell GPUs to fuel innovation across researchers, startups and industries.<\/p>\n<p><i>Read more about <\/i><a target=\"_blank\" href=\"https:\/\/www.nvidia.com\/en-us\/high-performance-computing\/\" rel=\"noopener\"><i>NVIDIA-accelerated supercomputing<\/i><\/a><i> and watch the <\/i><a target=\"_blank\" href=\"https:\/\/nvevents.nvidia.com\/sc25fireside\" rel=\"noopener\"><i>SC25 fireside chat by Ian Buck<\/i><\/a><i>, vice president of hyperscale and high-performance computing at NVIDIA.<\/i><\/p>\n<\/p><\/div>\n","protected":false},"excerpt":{"rendered":"<p>https:\/\/blogs.nvidia.com\/blog\/sc25-new-science-systems-worldwide\/<\/p>\n","protected":false},"author":0,"featured_media":4354,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[3],"tags":[],"_links":{"self":[{"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/posts\/4353"}],"collection":[{"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/types\/post"}],"replies":[{"embeddable":true,"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/comments?post=4353"}],"version-history":[{"count":0,"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/posts\/4353\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/media\/4354"}],"wp:attachment":[{"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/media?parent=4353"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/categories?post=4353"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/tags?post=4353"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}