A Fast Finite-Difference Method for Micromagnetics Using the Magnetic Scalar Potential

Abert, Claas; Selke, Gunnar; Krüger, Benjamin; Drews, André

doi:10.1109/tmag.2011.2172806

Cited by 34 publications

(53 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…On the other hand, the Heisenberg model cannot be efficiently used to simulate systems larger than a few nanometers due to the computational time increasing faster than linearly with the number of atoms. 6,7 In the presented approach ( Fig. 2), the entire system is simulated using the micromagnetic model while one or more regions of it containing large gradient structures (e.g.…”

Section: Introductionmentioning

confidence: 99%

Multiscale model approach for magnetization dynamics simulations

et al. 2016

View full text Add to dashboard Cite

Simulations of magnetization dynamics in a multiscale environment enable rapid evaluation of the Landau-Lifshitz-Gilbert equation in a mesoscopic sample with nanoscopic accuracy in areas where such accuracy is required. We have developed a multiscale magnetization dynamics simulation approach that can be applied to large systems with spin structures that vary locally on small length scales. To implement this, the conventional micromagnetic simulation framework has been expanded to include a multiscale solving routine. The software selectively simulates different regions of a ferromagnetic sample according to the spin structures located within in order to employ a suitable discretization and use either a micromagnetic or an atomistic model. To demonstrate the validity of the multiscale approach, we simulate the spin wave transmission across the regions simulated with the two different models and different discretizations. We find that the interface between the regions is fully transparent for spin waves with frequency lower than a certain threshold set by the coarse scale micromagnetic model with no noticeable attenuation due to the interface between the models. As a comparison to exact analytical theory, we show that in a system with Dzyaloshinskii-Moriya interaction leading to spin spiral, the simulated multiscale result is in good quantitative agreement with the analytical calculation.

show abstract

Section: Introductionmentioning

confidence: 99%

Multiscale model approach for magnetization dynamics simulations

et al. 2016

View full text Add to dashboard Cite

show abstract

“…The current trend for micromagnetic code is shifting the computationally intensive parts to GPUs. In micromagnetic simulations the magnetostatic field computation is the most time and memory consuming part . The magnetostatic field at a given point is calculated by taking considerations from the complete magnetization vector field.…”

Section: Introductionmentioning

confidence: 99%

“…36 -simulations the magnetostatic field computation is the most time and memory consuming part. 20,21 The magnetostatic field at a given point is calculated by taking considerations from the complete magnetization vector field. This results in an asymptotic complexity of O(n 2 ) where n is the number of field points.…”

mentioning

confidence: 99%

An optimized magnetostatic field solver on GPU using open computing language

Khan

Montrucchio

Jan

et al. 2016

Concurrency and Computation

View full text Add to dashboard Cite

Summary Recent graphic processing units (GPUs) have remarkable raw computing power, which can be used for very computationally challenging problems. Like in micromagnetic simulations, where the magnetostatic field computation to analyze the magnetic behavior at very small time and space scale demands a huge computation time. This paper presents a multidimensional FFT‐based parallel implementation of a magnetostatic field computation on GPUs. We have developed a specialized 3D FFT library for magnetostatic field calculation on GPUs. This made it possible to fully exploit the symmetries inherent in the field calculation and other optimizations specific to the GPUs architecture. We have compared our results with the widely used CPU‐based parallel OOMMF program and with an equivalent serial implementation on CPU. The results have shown a speedup of up to 95x and 8.7x for single and 66x and 4.6x for double precision floating point accuracy against equivalent serial implementation and OOMMF, respectively.

show abstract

“…There have been steady improvements in computational micromagnetics in recent years, both in techniques as well as in the use of graphical processing units (GPUs) [1]- [4]. These are complemented by efforts to compute the magnetization dynamics in various kinds of magnonic crystals and waveguides, of different geometries and made of different materials [5]- [7].…”

Section: Introductionmentioning

confidence: 99%

Proposal for a Standard Micromagnetic Problem: Spin Wave Dispersion in a Magnonic Waveguide

et al. 2013

View full text Add to dashboard Cite

Abstract-We propose a standard micromagnetic problem, of a nanostripe of permalloy. We study the magnetization dynamics and describe methods of extracting features from simulations. Spin wave dispersion curves, relating frequency and wave vector, are obtained for wave propagation in different directions relative to the axis of the waveguide and the external applied field. Simulation results using both finite element (Nmag) and finite difference (OOMMF) methods are compared against analytic results, for different ranges of the wave vector.

show abstract

A Fast Finite-Difference Method for Micromagnetics Using the Magnetic Scalar Potential

Cited by 34 publications

References 20 publications

Multiscale model approach for magnetization dynamics simulations

Multiscale model approach for magnetization dynamics simulations

An optimized magnetostatic field solver on GPU using open computing language

Proposal for a Standard Micromagnetic Problem: Spin Wave Dispersion in a Magnonic Waveguide

Contact Info

Product

Resources

About