Austin Benchmark Suite for Computational Bioelectromagnetics

Benchmarked Methods

Method 1

  • Name: AIM-Tetra
  • Class: FFT-accelerated iterative frequency-domain integral-equation solver
  • Algorithm: Iterative method of moments solution of volume electric field integral equation using tetrahedral elements with SWG basis/testing functions accelerated by the adaptive integral method [1]–[3].
  • Software implementation: The computational electromagnetics group at The University of Texas at Austin
  • Hardware: Lonestar5 at the Texas Advanced Computing Center
  • Submission date: October 1, 2016

Method 2

  • Name: AIM-Voxel
  • Class: FFT-accelerated iterative frequency-domain integral-equation solver
  • Algorithm: Iterative method of moments solution of volume electric field integral equation using voxel elements with volumetric rooftop basis/testing functions accelerated by the adaptive integral method [1]–[3].
  • Software implementation: The computational electromagnetics group at The University of Texas at Austin
  • Hardware: Lonestar5 at the Texas Advanced Computing Center
  • Submission date: October 1, 2016

Method 3

  • Name: FDTD
  • Class: Time-domain differential-equation solver
  • Algorithm: Explicit finite-difference time-domain method using the Yee grid with frequency-independent material properties, a split-field polynomial conductivity profile PML truncation, and a sinusoidally-modulated ramp waveform [1], [4].
  • Software implementation: The computational electromagnetics group at The University of Texas at Austin
  • Hardware: Lonestar5 at the Texas Advanced Computing Center
  • Submission date: October 1, 2016

References for Benchmarked Methods

  1. J. W. Massey, A comprehensive comparison of FFT-accelerated integral equation methods vs. FDTD for bioelectromagnetics, M.S. thesis, Dept. Electrical and Computer Engineering, The University of Texas at Austin, Austin, TX, 2015.
  2. F. Wei and A. E. Yilmaz, A more scalable and efficient parallelization of the adaptive integral method—Part I: Algorithm, IEEE Trans. Antennas Propag., vol. 62, no. 2, pp. 714–726, Feb. 2014.
  3. F. Wei and A. E. Yilmaz, A more scalable and efficient parallelization of the adaptive integral method—Part II: BIOEM application, IEEE Trans. Antennas Propag., vol. 62, no. 2, pp. 727–738, Feb. 2014.
  4. C. S. Geyik, Accuracy-efficiency comparison of finite-difference time-domain and adaptive integral method based simulators for bioelectromagnetics, M.S. thesis, Dept. Electrical and Computer Engineering, The University of Texas at Austin, Austin, TX, 2013.