Software Open Access
Stiller, Patrick;
Zhdanov, Maksim;
Rustamov, Jeyhun;
Bethke, Friedrich;
Hoffmann, Nico
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"description": "<p>Neural Solvers are neural network-based solvers for partial differential equations and inverse problems. The framework implements scalable physics-informed neural networks Physics-informed neural networks allow strong scaling by design. Therefore, we have developed a framework that uses data parallelism to accelerate the training of physics-informed neural networks significantly. To implement data parallelism, we use the Horovod framework, which provides near-ideal speedup on multi-GPU regimes.</p>",
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| All versions | This version | |
|---|---|---|
| Views | 1,397 | 1,397 |
| Downloads | 36 | 36 |
| Data volume | 56.2 MB | 56.2 MB |
| Unique views | 1,183 | 1,183 |
| Unique downloads | 35 | 35 |