Advancing Semiconductor Innovation Across Materials Engineering and Manufacturing

Summary

Increasing artificial intelligence workloads and slowing geometric scaling require rapid semiconductor innovation across materials engineering and manufacturing. Applied Materials collaborated with NVIDIA to build an end-to-end digital development pipeline that accelerates atomic-scale modeling, process development, and factory optimization. The Ginestra defect-centric simulation platform integrates NVIDIA cuDSS sparse solvers to achieve up to a 10x speedup, while NVIDIA cuEST accelerates density functional theory calculations on B200 systems by approximately 55x compared to 64 CPU cores. In process engineering, the ACE+ multiphysics platform pairs with NVIDIA PhysicsNeMo to run topography simulations up to 35x faster, and NVIDIA Omniverse generates fab digital twins to optimize material flows. This unified digital workflow enables engineers to perform virtual experiments rapidly, mitigate production bottlenecks, and shorten transitions to high-volume manufacturing.

Takeaways

1. 1

   NVIDIA cuEST accelerated density functional theory simulations on an NVIDIA B200 GPU by approximately 55x compared to 64 CPU cores, cutting runtime from five days to roughly two hours.

2. 2

   Integrating NVIDIA cuDSS into the Ginestra platform accelerated sparse linear algebra simulations up to 10x over CPU-only approaches without sacrificing simulation accuracy.

3. 3

   Applied Materials ACE+ coupled with NVIDIA PhysicsNeMo achieved up to 35x faster topography simulations, shifting multiphysics chamber workflows from days to same-day results.