Enabled by the integration of nTop's geometry iteration, Luminary's scalable engineering simulation, and NVIDIA PhysicsNeMo model training.
Luminary Cloud and nTop announced a new integration with NVIDIA PhysicsNeMo that accelerates physics-based AI design optimization, reducing processing time from weeks to hours. By integrating nTop’s parametric geometry generation, Luminary’s GPU-native simulation platform, and NVIDIA PhysicsNeMo via NIM microservices, engineers can generate and evaluate multiple design variations within a day, a process that previously required weeks of manual effort across separate systems.
From months to hours: physics AI breakthroughs transforms product design
Physics AI has made significant progress with the integration of Luminary Cloud and nTop, reducing challenges to broader adoption. This advancement enables the first automated pipeline for physics AI-driven engineering design optimization.
Engineering teams have long used computational simulation to validate designs before physical prototyping. However, fully refining products requires exploring thousands of design variations, a process that traditionally required significant time and resources.
The new integrated solution combines three critical technologies: nTop’s parametric geometry engine generates complex design variations in seconds; then Luminary Cloud’s GPU-native platform runs hundreds of high-fidelity simulations quickly and in parallel; finally NVIDIA PhysicsNeMo, AI physics framework, uses the data to create predictive models. The result is a seamless workflow that compresses what once took weeks into hours.
Engineers can now define design parameters, automatically generate and simulate multiple variations, and use AI to analyze and suggest configurations within a streamlined workflow that reduces manual file transfers and the need for specialized expertise. The system may improve performance across aerospace, automotive, and consumer product applications. In their first joint demonstration, nTop and Luminary analyzed lift and drag characteristics of flying wing configurations.
Unlocking real-time design optimization opportunities
This collaboration marks Luminary’s first native, API-based integration with a geometry engine to ingest and simulate many design iterations and represents a fundamental shift in the development of AI models for design optimization, democratizing both access to Physics AI for engineering teams of all sizes and the way simulation-based design is conducted.
Now anyone can adopt Physics AI on their own
Key benefits of an automated Physics AI pipeline for engineers:
- Easy setup. The robust and flexible APIs from nTop, Luminary, and NVIDIA allow for bi-directional connections between geometry iteration, engineering simulation, and Physics AI model training within a single workflow.
- Scale design exploration. NVIDIA CUDA software platform for high performance computing enables nTop’s geometry iteration speed and Luminary’s simulation scale which are foundational to scale up the design space.
- Rapidly optimize performance. Using NVIDIA PhysicsNeMo AI, coupled with NVIDIA Omniverse technologies, end users can visualize and interact with a physically-based digital twin to identify an optimal solution within minutes or hours.
For more information, visit luminarycloud.com.
