CERN Project Sees Orders-of-Magnitude Speedup with AI Approach

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An award-winning effort at CERN has demonstrated potential to significantly change how the physics based modeling and simulation communities view machine learning. The CERN team demonstrated that AI-based models have the potential to act as orders-of-magnitude-faster replacements for computationally expensive tasks in simulation, while maintaining a remarkable level of accuracy. Dr. Federico Carminati (Project Coordinator, CERN) points out, "This work demonstrates the potential of'black box' machine-learning models in physics-based simulations." A poster describing this work was awarded the prize for best poster in the category'programming models and systems software' at ISC'18. This recognizes the importance of the work, which was carried out by Dr. Federico Carminati, Gul Rukh Khattak, and Dr. Sofia Vallecorsa at CERN, as well as Jean-Roch Vlimant at Caltech.