h-Analysis and data-parallel physics-informed neural networks
Abstract We explore the data-parallel acceleration of physics-informed machine learning (PIML) schemes, with a focus on physics-informed neural networks (PINNs) for multiple graphics processing units (GPUs) architectures. In order to develop scale-robust and high-throughput PIML models for sophistic...
Main Authors: | , |
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Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2023-10-01
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Series: | Scientific Reports |
Online Access: | https://doi.org/10.1038/s41598-023-44541-5 |