Nvidia (NASDAQ: NVDA) announced at SEMICON West that several semiconductor companies are adopting its CUDA-X libraries to support what the company calls "AI-defined fabs," or semiconductor factories where AI assists engineers in optimizing production processes.

Among the new tools is cuPotential, a CUDA-X library now available in early access that developers can use to build AI agents simulating atomic and molecular interactions. In early-access testing, the library accelerated already GPU-optimized workflows by an additional 2–3x, according to the company. Synopsys is among the early adopters using cuPotential.

Synopsys is also using two other CUDA-X libraries — cuEST and cuDSS — with early results showing a potential 30x speedup in QuantumATK using cuEST and a 12x speedup in S-Device benchmarks using cuDSS. Cadence is using cuDSS with its Celsius software to optimize advanced packages for heat and stress 8x faster.

Lam Research plans to integrate NanoVDB, an open-source 3D data library, into its SEMulator3D platform, with the addition expected to accelerate select wafer-etch modeling by up to 30x. That capability is targeted for release by the end of 2026.

KLA applied insights from its production kernels to a new NPP NCC kernel, achieving performance levels 50x faster than earlier CPU versions. Teradyne is using Nvidia NPP and RAPIDS cuDF to deliver approximately 85x faster probe-maintenance inference.

Applied Materials is using Nvidia Omniverse and CUDA-X libraries across materials discovery and fab optimization, enabling up to 35x faster chamber simulations. COMSOL reported up to 10x faster semiconductor multiphysics simulations using cuDSS.

FANUC and Foxconn are connecting robot models to the Mega Nvidia Omniverse Blueprint to simulate robotic operations in factory digital twins before physical deployment. Advantest has integrated Nvidia Nemotron and Nvidia Kumo-Anomaly into its ACS RTDI system, reducing response times from hours to minutes.

"The semiconductor industry made the AI revolution possible. Now, AI is transforming how chips are built," said Tim Costa, vice president and general manager of industrial and computational engineering at Nvidia.