Mistral and NVIDIA announce collaboration on AI for industrial engineering, including physics AI benchmarks and agentic AI evaluations
NVIDIA cuDSS Library Goes GA; Mistral Partnership Targets Industrial AI
GPU-accelerated sparse solvers can reduce simulation time and expand the number of designs teams can test. The Mistral-NVIDIA partnership targets open benchmarks for physics AI and agentic AI evaluations in industrial CAE and EDA workflows.
The full picture
NVIDIA has released cuDSS, a CUDA-X library that accelerates sparse linear system solving by offloading the computation to GPUs. Sparse system solving is a repeated bottleneck in engineering and scientific simulations. Applied Materials reported up to 10x speedup in its Ginestra semiconductor simulation platform, ZEISS SMT reported a 4x speedup in an EUV lithography plasma simulation using COMSOL Multiphysics, and Dassault Systèmes reported 8-10x speedup in Abaqus electromagnetic solvers. cuDSS supports C, C++, Python, and Fortran interfaces and scales from workstations to large computing clusters. Separately, Mistral and NVIDIA announced a collaboration to bring AI to industrial engineering workflows, including faster simulation capabilities, open benchmarks and datasets for physics AI, and evaluations for agentic AI in computer-aided engineering and electronic design automation.
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