Simulator Training

Simulator Training

Users can leverage our Infrastructure-as-a-Service feature, Environments, part of the (opens in a new tab) platform. With a single click, you can begin training AI-based physics simulators on servers equipped with one or multiple GPUs. Our software can manage server nodes with hundreds of GPUs.

Simulator training in the cloud with Model Engineer

Figure 1.: Simulator training in the cloud on GPU-based servers, deployed through our Environments.

Training a simulator created in the model engineer is straightforward with a few simple steps on the platform:

  1. Navigate to "Train Simulator" on the left panel.
  2. Click on "Create Environment", fill out the specifications, or select from the existing environment list.
  3. Choose the simulator you want to train, deploy the server or start it, then click on "Train".
  4. The simulator is trained using the Simulator Inference Training Environment (SITE), which is optimized for NVIDIA GPUs and uses the NVIDIA Modulus framework for model creation and training.
  5. Monitor the training process. We offer comprehensive monitoring for hardware utilization, infrastructure usage, and training progress.
Latest activity

Figure 2.: Latest activity displayed in the Overview page.

  1. Finally, the trained models can be used in Simulation Studio, a 3D interface for high-fidelity, interactive visualizations of running numerical simulations. More on this is discussed in the nect section.