NVIDIA and Semiconductor Leaders Advance AI Across Chip Design and Manufacturing for AI-Defined Fabs
Key Highlights
- ➤NVIDIA cuPotential accelerates GPU-optimized atomic-interaction workflows an additional 2-3x in early-access testing
- ➤Synopsys QuantumATK shows potential 30x speedup using NVIDIA cuEST
- ➤Lam Research targets up to 30x faster select wafer-etch modeling with NanoVDB
- ➤KLA’s new NPP NCC kernel runs 50x faster than earlier CPU versions
- ➤Teradyne achieves approximately 85x faster probe-maintenance inference using NVIDIA technologies
Expert Statements
Tim Costa, Vice president and general manager of industrial and computational engineering at NVIDIA
“The semiconductor industry made the AI revolution possible. Now, AI is transforming how chips are built.”
Tim Costa, Vice president and general manager of industrial and computational engineering at NVIDIA
“As fabs race to meet demand for advanced chips, NVIDIA CUDA-X and Omniverse libraries give AI agents accelerated simulation and inspection tools to help engineers manage complexity, improve yield and advance AI-defined fabs.”
News Summary: * NVIDIA introduces cuPotential, a new NVIDIA CUDA-X library developers can use to build AI agents that simulate how atoms and molecules interact, accelerating already GPU-optimized workflows by an additional 2-3x in early-access testing. * NanoVDB, an open source library for working with 3D data, accelerates chipmaking simulation for AI-defined fabs, helping Lam Research achieve 30x faster simulation. * NVIDIA NPP, a library for processing images on GPUs, accelerates chipmaking inspection for AI-defined fabs, helping KLA accelerate inspection. * Applied Materials, Cadence, KLA, Lam Research, Siemens, Synopsys and other semiconductor leaders are using NVIDIA’s accelerated computing and AI stack across chip design, manufacturing and testing, helping drive faster development, better yield and greater production capacity. SAN FRANCISCO, Oct. 14, 2026 (GLOBE NEWSWIRE) -- SEMICON West -- NVIDIA today announced semiconductor leaders are adopting NVIDIA CUDA-X™ libraries — including the new NVIDIA cuPotential library, which developers can use to build AI agents that simulate how atoms and molecules interact — to advance AI-defined fabs.
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