NVIDIA and SK hynix will co-develop next-generation memory for AI factory infrastructure and use AI-based tools to accelerate semiconductor design and manufacturing workflows. The partnership builds on co-engineering work for advanced AI computing platforms.
“AI factories are the engines of the next industrial revolution, and advanced memory is essential to their performance,” said Jensen Huang, founder and CEO of NVIDIA. “SK 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 – from frontier model training to agentic and physical AI.”
“SK hynix and NVIDIA have been building toward this for years, and this partnership reflects the depth of that collaboration,” said Chey Tae-won, chairman of SK Group. “Together, we are codeveloping the next generation of memory for AI factories and applying AI to how we design and manufacture semiconductors – work that will shape the future of AI infrastructure.”
The agreement supports memory supply over the extended development cycles required for advanced memory. As AI factories expand globally, the companies aim to align memory supply with NVIDIA’s infrastructure roadmap and the buildout of AI infrastructure. SK hynix will also work with NVIDIA in markets including AI infrastructure, personal AI and physical AI, while codeveloping memory for NVIDIA Vera Rubin AI supercomputers, NVIDIA Vera CPUs, NVIDIA RTX Spark-powered PCs and NVIDIA Jetson Thor robotic computing platforms.
Accelerating Semiconductor Design Simulation
SK hynix is using NVIDIA CUDA-X libraries and AI to accelerate semiconductor simulation, including technology CAD and computational lithography workflows.
SK hynix is also using CUDA-X and the NVIDIA PhysicsNeMo framework to accelerate core workloads across its in-house simulation codes and AI physics workflows.
The companies plan to extend these tools into semiconductor electronic design automation and simulation ecosystems, creating a basis for collaboration among chipmakers, NVIDIA and electronic design automation software vendors.
Building Autonomous Fab Digital Twins
SK hynix is developing fab digital twins to support autonomous fab operations. Teams can use scene optimization technologies, NVIDIA Omniverse libraries and OpenUSD pipelines to build 3D factory scenes for visualizing, simulating and optimizing semiconductor manufacturing environments.
The digital twins can also support operational optimization, including the movement of mobile robots and other assets, using the open-source, GPU-accelerated NVIDIA cuOpt decision optimization engine and the NVIDIA Metropolis platform.
The companies are also exploring ways to connect digital twins with legacy software and agentic AI workflows so AI systems can reason over fab data, automate tasks and improve manufacturing decision-making.
Source: NVIDIA
About SK Hynix
SK Hynix is a South Korean semiconductor company based in Icheon, South Korea. Founded in 1983, it makes memory and storage products for computing, mobile devices, consumer electronics, vehicles, industrial systems and data centers. Its products include DRAM, NAND flash memory, solid-state drives and CMOS image sensors. SK Hynix supplies components to device makers, cloud providers, data center operators and other technology companies worldwide. The company runs production sites in South Korea and China and maintains research, sales and support operations in several countries. Its products are used in servers, personal computers, smartphones, AI systems and storage devices. SK Hynix employed about 32,000 people globally.
About NVIDIA
NVIDIA, founded in 1993 and headquartered in Santa Clara, CA, designs and manufactures graphics processing units, systems on chips, networking hardware, and AI intelligence software such as CUDA. Its products serve industries including gaming, data centers, autonomous vehicles, professional visualization, robotics, health care, and energy. The company introduced the GPU in 1999 and later expanded into accelerated computing and AI infrastructure. In gaming, its GPUs support high-performance rendering, while in AI and high-performance computing, its systems provide the infrastructure for training and deploying large-scale models. NVIDIA also develops tools for robotics and autonomous driving.