Adaptation of AI-accelerated CFD Simulations to the IPU platform
Intelligence Processing Units (IPU) have proven useful for many AI applications. In this paper, we evaluate them within the emerging field of \emph{AI for simulation}, where traditional numerical simulations are supported by artificial intelligence approaches. We focus specifically on a program for training machine learning models supporting a \emph{computational fluid dynamics} application. We use custom TensorFlow provided by the Poplar SDK to adapt the program for the IPU-POD16 platform and investigate its ease of use and performance scalability. Training a model on data from OpenFOAM simulations allows us to get accurate simulation state predictions in test time. We show how to utiliz...
| Authors | P. Rosciszewski, A. Krzywaniak, S. Iserte et al. |
|---|---|
| Primary category | cs.DC |
| Published | 1 May 2026 |
| Last updated at source | 1 May 2026 |
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