FastMag: Fast micromagnetic simulator for complex magnetic structures
Center for Magnetic Recording Research and Department of Electrical and Computer Engineering, University of California, San Diego, California 92093, USA
Journal of Applied Physics, 2011
@article{chang2011fastmag,
title={FastMag: Fast micromagnetic simulator for complex magnetic structures},
author={Chang, R. and Li, S. and Lubarda, MV and Livshitz, B. and Lomakin, V.},
journal={Journal of Applied Physics},
volume={109},
number={7},
pages={07D358–07D358},
year={2011},
publisher={AIP}
}
A fast micromagnetic simulator (FastMag) for general problems is presented. FastMag solves the Landau-Lifshitz-Gilbert equation and can handle multiscale problems with a high computational efficiency. The simulator derives its high performance from efficient methods for evaluating the effective field and from implementations on massively parallel graphics processing unit (GPU) architectures. FastMag discretizes the computational domain into tetrahedral elements and therefore is highly flexible for general problems. The magnetostatic field is computed via the superposition principle for both volume and surface parts of the computational domain. This is accomplished by implementing efficient quadrature rules and analytical integration for overlapping elements in which the integral kernel is singular. Thus, discretized superposition integrals are computed using a nonuniform grid interpolation method, which evaluates the field from N sources at N collocated observers in O(N) operations. This approach allows handling objects of arbitrary shape, allows easily calculating of the field outside the magnetized domains, does not require solving a linear system of equations, and requires little memory. FastMag is implemented on GPUs with GPU-central processing unit speed-ups of 2 orders of magnitude. Simulations are shown of a large array of magnetic dots and a recording head fully discretized down to the exchange length, with over a hundred million tetrahedral elements on an inexpensive desktop computer.
August 31, 2011 by hgpu