Austin Benchmark Suite for Computational Bioelectromagnetics

References

  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. J. W. Massey, C. Liu, and A. E. Yilmaz, Benchmarking to close the credibility gap: A computational BioEM benchmark suite, in Proc. URSI EMTS, Aug. 2016.
  3. P. C. Boutros, A. A. Margolin, J. M. Stuart, A. Califano, and G. Stolovitzky, Toward better benchmarking: challenge-based methods assessment in cancer genomics, Genome Biol. vol. 15, no. 9, p. 462, Sep. 2014.
  4. D. L. Donoho, A. Maleki, I. U. Rahman, M. Shahram, and V. Stodden Reproducible research in computational harmonic analysis, Comput. Sci. Eng., vol. 11, no. 1, pp. 8-18, Jan.-Feb. 2009.
  5. IEEE recommended practice for determining the peak spatial-average specific absorption rate (SAR) in the human head from wireless communications devices: measurement techniques, IEEE Std 1528C-2013 (Revision IEEE Std 1528-2003), 2013.
  6. S. Gabriel, R. W. Lau, and C. Gabriel, The dielectric properties of biological tissues: III. Parametric models for the dielectric spectrum of tissues, Phys. Med. Biol., vol. 41, no. 11, pp. 2271–93, Nov. 1996.
  7. Human exposure to radio frequency fields from hand-held and body mounted wireless communication devices - Human models, instrumentation, and procedures - Part 2, IEC 62209-2:2010, 2010.
  8. J. W. Massey et al., AustinMan electromagnetic voxels: An open source model constructed from the Visible Human dataset, 2016.
  9. F. Wei, J. W. Massey, C. S. Geyik, and A. E. Yilmaz, Error measures for comparing bioelectromagnetic simulators, in Proc. IEEE Int. Symp. Antennas Propag., 2012, no. 3, pp. 1–2.
  10. M. F. Wu, G. Kaur, and A. E. Yilmaz, A multiple-grid adaptive integral method for multi-scale problems, IEEE Trans. Antennas Propag., vol. 58, no. 5, pp. 1601-1613, May 2010.
  11. L. Pastor and J. L. Bosque Orero, An efficiency and scalability model for heterogeneous clusters, in Proc. IEEE Int. Conf. Cluster Comp., Oct. 2001, pp. 427-434.
  12. J. W. Massey, A. Menshov, and A. E. Yilmaz, An empirical methodology for judging the performance of parallel algorithms on heterogeneous clusters, in Proc. 13th Int. Workshop FEM Microw. Eng., pp. 151-152, May 2016.
  13. M. J. Miranda, T. Ozdemir, and R. J. Burkholder, Hardware acceleration of an FMM-FFT solver using consumer-grade GPUs, in Proc. URSI NRSM Meet., Jan. 2016.
  14. 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.
  15. C. Drummond, Replicability is not reproducibility: Nor is it good science, in Proc. of the Evaluation Methods for Machine Learning Workshop at the 26th ICML, Montreal, Canada, 2009.
  16. D. G. Feitelson, From repeatability to reproducibility and corroboration, SIGOPS Operating Systems Rev., vol. 49, no. 1, pp. 3-11, Jan. 2015.
  17. G. Kaur, COMPASS-EM: Comprehensive program for analytical scattering solutions for electromagnetics.
  18. C. Liu, G. Kaur, and A. E. Yilmaz, Analytical solution of radiation by a Hertzian dipole near an electrically large layered spheroid, in Proc. IEEE Antennas Propagat. Soc. Int. Symp., July 2015, pp. 1688–1689.