AER offering Data Innovation Lab Project on the Acceleration of CFD-accelerating Machine Learning Kernels for the first time (Deadline 31.01)

For the first time the AER is participating in the [TUM Data Innovation Lab]( of the [Munich Data Science Institute]( with its own project on the software-level acceleration of neural network kernels used in the acceleration of traditional computational fluid dynamics simulations.

The students will work on the acceleration of research-level neural networks, specifically a generative adversarial network (GAN), and a graph neural network (GNN) for the acceleration of smoothed-particle hydrodynamics. For this we will begin by introducing the Microsoft DeepSpeed concepts at the beginning of the project, and the successively building on the gained knowledge by first accelerating a classical GAN, the research-level GAN, to finally accelerate the kernels used in the graph neural network acceleration.

For more information please have a look at the [project page](, and feel free to approach Ludger Paehler ( if you need more information.