magnum.np. a PyTorch based GPU enhanced finite difference micromagnetic simulation framework for high level development and inverse design
- Author(s)
- Florian Bruckner, Sabri Koraltan, Claas Abert, Dieter Suess
- Abstract
magnum.np is a micromagnetic finite-difference library completely based on the tensor library PyTorch. The use of such a high level library leads to a highly maintainable and extensible code base which is the ideal candidate for the investigation of novel algorithms and modeling approaches. On the other hand magnum.np benefits from the device abstraction and optimizations of PyTorch enabling the efficient execution of micromagnetic simulations on a number of computational platforms including graphics processing units and potentially Tensor processing unit systems. We demonstrate a competitive performance to state-of-the-art micromagnetic codes such as mumax3 and show how our code enables the rapid implementation of new functionality. Furthermore, handling inverse problems becomes possible by using PyTorch’s autograd feature.
- Organisation(s)
- Computational and Soft Matter Physics, Physics of Functional Materials
- Journal
- Scientific Reports
- Volume
- 13
- No. of pages
- 13
- ISSN
- 2045-2322
- DOI
- https://doi.org/10.48550/arXiv.2302.08843
- Publication date
- 07-2023
- Peer reviewed
- Yes
- Austrian Fields of Science 2012
- 103043 Computational physics
- ASJC Scopus subject areas
- General
- Portal url
- https://ucris.univie.ac.at/portal/en/publications/magnumnp-a-pytorch-based-gpu-enhanced-finite-difference-micromagnetic-simulation-framework-for-high-level-development-and-inverse-design(4e7959e7-3b34-460e-97ea-dbfe40047ef4).html