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Vinci executive Dinesh Panneerselvam introduced Vinci's approach to bringing simulation into chip design using physical AI. According to SiliconANGLE, Vinci4D showcased its physical AI solution at SEMICON West, combining physics foundation models with GPU-native physics kernels, called Continuous Physics Reasoning, enabling engineers to obtain both accuracy and fast physical simulation at design speed. The model is trained on Vinci's own data, deployed within customers' firewalls, and can directly read existing design files. Its $250 million Series B funding will support expansion into electromagnetics, fluid dynamics, and the automotive and aerospace sectors. There are currently no subsequent development facts.
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Vinci Uses Physical AI to Accelerate Chip DesignDevelopments
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- Source:SiliconANGLE
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Oct 17
SiliconANGLE
Vinci Uses Physical AI to Accelerate Chip Design
Vinci4D showcased its physical AI solution at SEMICON West, combining physics foundation models with GPU-native physics kernels in what it calls Continuous Physics Reasoning, enabling engineers to obtain both accuracy and fast physics simulation at design speed. The model is trained on Vinci's proprietary data, deployed within customers' firewalls, and can directly read existing design files. Its $250 million Series B funding will support expansion into electromagnetics, fluid dynamics, and the automotive and aerospace sectors.