NVIDIA and SK hynix Partner on Next-Generation Memory for AI Infrastructure
NVIDIA and SK hynix announced a multiyear technology partnership on June 7 to develop advanced memory systems aligned with NVIDIA's AI infrastructure roadmap. The agreement addresses supply constraints as companies worldwide scale AI factory buildouts.
The partnership codevelops memory for NVIDIA's Vera Rubin AI supercomputers, Vera CPUs, RTX Spark-powered PCs, and Jetson Thor robotic computing platforms. SK hynix will expand into markets NVIDIA is creating across AI infrastructure, personal AI, and physical AI applications.
Using AI to Speed Chip Design and Manufacturing
Both companies will apply AI to their own semiconductor design and manufacturing processes. SK hynix is using NVIDIA's CUDA-X libraries and PhysicsNeMo framework to accelerate technology computer-aided design (TCAD) workflows and computational lithography simulations.
The approach extends to SK hynix's in-house simulation codes and physics workflows. This work could establish a model for three-way collaborations among chipmakers, NVIDIA, and electronic design automation software vendors.
Building Digital Twins for Factory Automation
SK hynix is developing digital twins of its manufacturing facilities to support autonomous fab operations. The company is using NVIDIA Omniverse libraries and OpenUSD standards to build 3D models of semiconductor manufacturing environments.
SK hynix will apply NVIDIA's cuOpt decision optimization engine and Metropolis platform to optimize operations like autonomous mobile robot movement and asset allocation. The companies are also exploring connections between digital twins and AI systems that can reason over fab data and automate manufacturing decisions.
Why This Matters for Development Teams
For IT professionals and software engineers, this partnership signals how AI tools are moving upstream into infrastructure design itself. Teams working with AI for IT & Development need to understand frameworks like CUDA-X and physics simulation tools that are becoming standard in hardware-software co-design.
Engineers working on AI infrastructure projects should familiarize themselves with the tools mentioned here. The AI Learning Path for Software Engineers covers relevant foundational concepts for this type of work.
SK hynix and NVIDIA have been collaborating for years on memory technologies. This formal partnership formalizes work that has already powered some of the world's most advanced AI computing systems.
Your membership also unlocks:
