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Home » Uncategorized » Team 211: Deep Learning for Fluid Flow Prediction in the Advania Data Centers Cloud

Team 211: Deep Learning for Fluid Flow Prediction in the Advania Data Centers Cloud

Team 211The goal of this UberCloud Case Study 211 was to apply Artificial Neural Networks to solve fluid flow problems and significantly decrease time-to-solution while preserving much of the accuracy of a traditional CFD solver. Creating a large number of simulation samples is paramount to let the neural network learn the dependencies between simulated design and flow field around it. This project between Renumics and UberCloud was therefore established to explore the benefits of additional cloud computing resources that can be used to create a large amount of simulation samples (in fact 100,000 !) in a fraction of the time a desktop computer would need to create them. In this project, we wanted to explore whether the overall accuracy of the neural network can be improved when more samples are being created in UberCloud’s OpenFOAM container on Advania Data Centers HPCFLOW Cloud and then used during the training of the neural network. This project has been sponsored by HPE and Intel.

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