Collaboration Supports Next-Generation Memory Codevelopment With NVIDIA\u2019s AI Infrastructure Roadmap and Expands Supply for the Accelerating Global AI Factory Buildout<\/p>\n
News Summary:<\/p>\n
\n\tNVIDIA and SK hynix announce multiyear technology partnership for next-generation memory aligned to NVIDIA\u2019s AI infrastructure roadmap.
\n\tThe agreement supports supply for advanced memory, addressing the extended development cycles, advanced fabrication and capital investments to sustain the global buildout of AI factories.
\n\tSK hynix will diversify into new markets NVIDIA is creating \u2014 across AI infrastructure, personal AI and physical AI \u2014 codeveloping memory for NVIDIA Vera Rubin AI supercomputers, Vera CPUs, RTX Spark-powered PCs and Jetson Thor robotic computing platforms.
\n\tThe two companies will apply AI to semiconductor chip design and manufacturing, using NVIDIA CUDA-X libraries and NVIDIA PhysicsNeMo to accelerate semiconductor simulations, TCAD workflows and in-house engineering codes.
\n\tSK hynix will advance factory digital twins by combining NVIDIA Omniverse, OpenUSD scene optimization and NVIDIA cuOpt to drive fully autonomous fab operations.
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\nNVIDIA and SK hynix today announced a multiyear technology partnership to advance next-generation memory for the global AI factory buildout and accelerate semiconductor design and manufacturing. The agreement builds on years of deep co-engineering collaboration that has powered some of the world\u2019s most advanced AI computing platforms. \u00a0<\/p>\n
\u201cAI factories are the engines of the next industrial revolution, and advanced memory is essential to their performance,\u201d said Jensen Huang, founder and CEO of NVIDIA. \u201cSK hynix has been an extraordinary partner to NVIDIA, playing a central role in delivering advanced memory technologies for NVIDIA AI computing platforms. Together, we will codevelop the next generation of memory for AI factories and support the accelerating global expansion of AI infrastructure \u2014 from frontier model training to agentic and physical AI.\u201d<\/p>\n
\u201cSK hynix and NVIDIA have been building toward this for years, and this partnership reflects the depth of that collaboration,\u201d said Chey Tae-won, Chairman of SK Group. \u201cTogether, we are codeveloping the next generation of memory for AI factories and applying AI to how we design and manufacture semiconductors \u2014 work that will shape the future of AI infrastructure.\u201d<\/p>\n
The multiyear agreement supports supply to address the extended development cycles of advanced memory. As AI factories scale globally, this strategic partnership enables memory supply to keep pace with NVIDIA\u2019s infrastructure roadmap and the sustained buildout of AI infrastructure worldwide. Through this partnership, SK hynix will diversify into new markets NVIDIA is creating \u2014 spanning AI infrastructure, personal AI and physical AI<\/a> \u2014 codeveloping memory for NVIDIA Vera Rubin AI supercomputers<\/a>, NVIDIA Vera CPUs<\/a>, NVIDIA RTX Spark\u2122-powered PCs<\/a> and NVIDIA Jetson Thor\u2122 robotic computing platforms<\/a>.<\/p>\n Accelerating Technology Computer-Aided Design and Semiconductor Simulation SK hynix is also using CUDA-X and the NVIDIA PhysicsNeMo<\/a>\u2122 framework to deliver core-workload acceleration across its in-house simulation codes and AI physics workflows.<\/p>\n By extending these tools to the semiconductor electronic design automation and simulation ecosystems, this initiative paves the way for three-way collaborations among chipmakers, NVIDIA and electronic design automation software vendors.<\/p>\n Advancing Fab Digital Twins for Autonomous Manufacturing These digital twins can also support operational optimization, including the movement of autonomous mobile robots and other fab assets, using the open source, GPU-accelerated NVIDIA cuOpt<\/a>\u2122 decision optimization engine and the NVIDIA Metropolis<\/a> platform.<\/p>\n The companies are also exploring ways to connect digital twins with existing legacy software and agentic AI workflows, enabling AI systems to reason over fab data, automate tasks and improve manufacturing decision-making.<\/p>\n","protected":false},"excerpt":{"rendered":"Collaboration Supports Next-Generation Memory Codevelopment With NVIDIA\u2019s AI Infrastructure Roadmap and Expands Supply for the Accelerating Global AI…\n","protected":false},"author":2,"featured_media":690703,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[45],"tags":[182,181,507,74],"class_list":["post-690702","post","type-post","status-publish","format-standard","has-post-thumbnail","category-artificial-intelligence","tag-ai","tag-artificial-intelligence","tag-artificialintelligence","tag-technology"],"_links":{"self":[{"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/posts\/690702","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/comments?post=690702"}],"version-history":[{"count":0,"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/posts\/690702\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/media\/690703"}],"wp:attachment":[{"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/media?parent=690702"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/categories?post=690702"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/tags?post=690702"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
\nSK hynix is using NVIDIA CUDA-X<\/a>\u2122 libraries and AI to speed semiconductor simulation, including technology computer-aided design and computational lithography workflows.<\/p>\n
\nSK hynix is developing fab digital twins<\/a> as a foundation for autonomous fab operations. Teams can use scene optimization technologies, as well as NVIDIA Omniverse\u2122<\/a> libraries and OpenUSD<\/a> pipelines, to build 3D factory scenes for visualizing, simulating and optimizing complex semiconductor manufacturing environments.<\/p>\n