As AI workloads increase, explosive compute demand is pushing the semiconductor industry to meet unprecedented performance targets. Even small delays can have outsized financial impact in fast-moving AI hardware cycles. Simultaneously, the shift from chip-level optimization to system-level engineering is compounding thermal and power challenges.

Meeting these demands requires breakthroughs in materials deep within the device stack. This calls for advanced modeling and simulation beyond what conventional approaches can deliver.

This post explores how Applied Materials and NVIDIA are tackling this challenge with an end-to-end digital development model that combines Applied Materials leadership in materials engineering and semiconductor manufacturing with NVIDIA CUDA-X libraries .…