Abstract
Amorphous solids, like metallic glasses, exhibit an excess of low frequency vibrational states reflecting the break-up of sound due to the strong structural disorder inherent to these materials. Referred to as the boson peak regime of frequencies, how the corresponding eigenmodes relate to the underlying atomic-scale disorder remains an active research topic. In this paper we investigate the use of a polynomial filtered eigensolver for the computation and study of low frequency eigenmodes of a Hessian matrix located in a specific interval close to the boson peak regime. A distributed-memory parallel implementation of a polynomial filtered eigensolver is presented. Our implementation, based on the Trilinos framework, is then applied to a Hessian matrix of an atomistic bulk metallic glass structure derived from a molecular dynamics simulation for the computation of eigenmodes close to the boson peak. In addition, we study the parallel scalability of our implementation on multicore nodes. Our resulting calculations successfully concur with previous atomistic results, and additionally demonstrate a broad cross-over of boson peak frequencies within which sound is seen to break-up.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Accaputo, G.: Solving large scale eigenvalue problems in amorphous materials. Master’s thesis, ETH Zurich, Computer Science Department (2017). https://doi.org/10.3929/ethz-b-000221499
Accaputo, G., Derlet, P.M., Arbenz, P.: Solving large-scale interior eigenvalue problems to investigate the vibrational properties of the boson peak regime in amorphous materials. Print Archive: arXiv:1902.07041 [physics.comp-ph] (2019)
Aktulga, H.M., Buluç, A., Williams, S., Yang, C.: Optimizing sparse matrix-multiple vectors multiplication for nuclear configuration interaction calculations. In: International Parallel and Distributed Processing Symposium (IPDPS), pp. 1213–1222 (2014)
Arbenz, P., Hetmaniuk, U.L., Lehoucq, R.B., Tuminaro, R.: A comparison of eigensolvers for large-scale 3D modal analysis using AMG-preconditioned iterative methods. Int. J. Numer. Methods Eng. 64, 204–236 (2005)
Avron, H., Toledo, S.: Randomized algorithms for estimating the trace of an implicit symmetric positive semi-definite matrix. J. ACM 58, 8:1–8:34 (2011)
Baker, C.G., Hetmaniuk, U.L., Lehoucq, R.B., Thornquist, H.K.: Anasazi software for the numerical solution of large-scale eigenvalue problems. ACM Trans. Math. Softw. 36, 1–23 (2009)
van Barel, M.: Designing rational filter functions for solving eigenvalue problems by contour integration. Linear Algebra Appl. 502, 346–365 (2016)
Barrett, R., et al.: Templates for the Solution of Linear Systems: Building Blocks for Iterative Methods. SIAM, Philadelphia (1994)
Bekas, C., Kokiopoulou, E., Saad, Y.: Polynomial filtered Lanczos iterations with applications in density functional theory. SIAM J. Matrix Anal. Appl. 30, 397–418 (2008)
Bell, R.J., Dean, P.: Atomic vibrations in vitreous silica. Discuss. Faraday Soc. 50, 55–61 (1970)
Berthier, L., Charbonneau, P., Jin, Y., Parisi, G., Seoane, B., Zamponi, F.: Growing timescales and lengthscales characterizing vibrations of amorphous solids. Proc. Nat. Acad. Sci. 113, 8397–8401 (2016)
Derlet, P.M., Maaß, R.: Thermal processing and enthalpy storage of a binary amorphous solid: a molecular dynamics study. J. Mater. Res. 32, 2668–2679 (2017)
Derlet, P.M., Maaß, R.: Local volume as a robust structural measure and its connection to icosahedral content in a model binary amorphous system. Materialia 3, 97–106 (2018)
Derlet, P.M., Maaß, R.: Thermally-activated stress relaxation in a model amorphous solid and the formation of a system-spanning shear event. Acta Mater. 143, 205–213 (2018)
Derlet, P.M., Maaß, R., Löffler, J.F.: The Boson peak of model glass systems and its relation to atomic structure. Eur. Phys. J. B 85, 1–20 (2012)
Fang, H.R., Saad, Y.: A filtered Lanczos procedure for extreme and interior eigenvalue problems. SIAM J. Sci. Comput. 34, A2220–A2246 (2012)
FUJITSU Server Performance Report PRIMERGY RX2540 M4. White paper, version 1.3. Fujitsu Corporation, 17 November 2018 (2018)
Galgon, M., et al.: Improved coefficients for polynomial filtering in ESSEX. In: Sakurai, T., Zhang, S.-L., Imamura, T., Yamamoto, Y., Kuramashi, Y., Hoshi, T. (eds.) EPASA 2015. LNCSE, vol. 117, pp. 63–79. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-62426-6_5
Hutchinson, M.F.: A stochastic estimator of the trace of the influence matrix for Laplacian smoothing splines. Commun. Stat. Simulat. Comput. 19, 433–450 (1990)
Jay, L.O., Kim, H., Saad, Y., Chelikowsky, J.R.: Electronic structure calculations for plane-wave codes without diagonalization. Comput. Phys. Commun. 118, 21–30 (1999)
Krämer, L., Di Napoli, E., Galgon, M., Lang, B., Bientinesi, P.: Dissecting the FEAST algorithm for generalized eigenproblems. J. Comput. Appl. Math. 244, 1–9 (2013)
Kreutzer, M., Pieper, A., Hager, G., Wellein, G., Alvermann, A., Fehske, H.: Performance engineering of the kernel polynomial method on large-scale CPU-GPU systems. In: International Parallel and Distributed Processing Symposium (IPDPS), pp. 417–426 (2015)
Leonforte, F., Boissière, R., Tanguy, A., Wittmer, J.P., Barrat, J.L.: Continuum limit of amorphous elastic bodies. III. Three-dimensional systems. Phys. Rev. B 72, 224206 (2005)
Li, R., Xi, Y., Vecharynski, E., Yang, C., Saad, Y.: A thick-restart Lanczos algorithm with polynomial filtering for Hermitian eigenvalue problems. SIAM J. Sci. Comput. 38, A2512–A2534 (2016)
Liang, Z., Keblinski, P.: Sound attenuation in amorphous silica at frequencies near the boson peak. Phys. Rev. B 93, 054205 (2016)
Lin, L., Saad, Y., Yang, C.: Approximating spectral densities of large matrices. SIAM Rev. 58, 34–65 (2016)
Marruzzo, A., Schirmacher, W., Fratalocchi, A., Ruocco, G.: Heterogeneous shear elasticity of glasses: the origin of the boson peak. Sci. Rep. 3, 1407 (2013)
Monaco, G., Mossa, S.: Anomalous properties of the acoustic excitations in glasses on the mesoscopic length scale. Proc. Nat. Acad. Sci. 106, 16907–16912 (2009)
di Napoli, E., Polizzi, E., Saad, Y.: Efficient estimation of eigenvalue counts in an interval. Numer. Linear Algebra Appl. 23, 674–692 (2016)
Parlett, B.N.: The Symmetric Eigenvalue Problem. Prentice Hall, Upper Saddle River (1980)
Pieper, A., et al.: High-performance implementation of Chebyshev filter diagonalization for interior eigenvalue computations. J. Comput. Phys. 325, 226–243 (2016)
Rivlin, T.J.: An Introduction to the Approximation of Functions. Dover, New York (1981)
Saad, Y.: Numerical Methods for Large Eigenvalue Problems, 2nd edn. SIAM, Philadelphia (2011)
Schaffner, S.: Using Trilinos to solve large scale eigenvalue problems in amorphous materials. Master’s thesis, ETH Zurich, Computer Science Department (2015)
Schirmacher, W.: The boson peak. Phys. Status Solidi B 250, 937–943 (2013)
Schirmacher, W., Ruocco, G., Scopigno, T.: Acoustic attenuation in glasses and its relation with the boson peak. Phys. Rev. Lett. 98, 025501 (2007)
Schirmacher, W., Scopigno, T., Ruocco, G.: Theory of vibrational anomalies in glasses. J. Non-Cryst. Solids 407, 133–140 (2015)
Schofield, G., Chelikowsky, J.R., Saad, Y.: A spectrum slicing method for the Kohn–Sham problem. Comput. Phys. Commun. 183, 497–505 (2012)
Shintani, H., Tanaka, H.: Universal link between the boson peak and transverse phonons in glass. Nat. Mater. 7, 870–877 (2008)
Silver, R.N., Röder, H.: Calculation of densities of states and spectral functions by Chebyshev recursion and maximum entropy. Phys. Rev. E 56, 4822–4829 (1997)
Silver, R.N., Röder, H., Voter, A.F., Kress, J.D.: Kernel polynomial approximations for densities of states and spectral functions. J. Comput. Phys. 124, 115–130 (1996)
Sleijpen, G.L.G., van den Eshof, J.: On the use of harmonic Ritz pairs in approximating internal eigenpairs. Linear Algebra Appl. 358, 115–137 (2003)
Sleijpen, G.L.G., van der Vorst, H.A.: A Jacobi–Davidson iteration method for linear eigenvalue problems. SIAM J. Matrix Anal. Appl. 17, 401–425 (1996)
Trefethen, L.N.: Approximation Theory and Approximation Practice. SIAM, Philadelphia (2013)
The Trilinos Project Home Page. https://trilinos.github.io
Wahnström, G.: Molecular-dynamics study of a supercooled 2-component Lennard–Jones system. Phys. Rev. A 44, 3752–3764 (1991)
Weiße, A., Wellein, G., Alvermann, A., Fehske, H.: The kernel polynomial method. Rev. Mod. Phys. 78, 275–306 (2006)
Wu, K., Simon, H.D.: Thick-restart Lanczos method for large symmetric eigenvalue problems. SIAM J. Matrix Anal. Appl. 22, 602–616 (2000)
Xu, N., Wyart, M., Liu, A.J., Nagel, S.R.: Excess vibrational modes and the Boson peak in model glasses. Phys. Rev. Lett. 98, 175502 (2007)
Yamazaki, I., Tadano, H., Sakurai, T., Ikegami, T.: Performance comparison of parallel eigensolvers based on a contour integral method and a Lanczos method. Parallel Comput. 39, 280–290 (2013)
Zhou, Y., Saad, Y., Tiago, M.L., Chelikowsky, J.R.: Self-consistent field calculations using Chebyshev-filtered subspace iteration. J. Comput. Phys. 219, 172–184 (2006)
Acknowledgments
The computations have been executed on the Euler compute cluster at ETH Zurich at the expense of a grant of the Seminar for Applied Mathematics. We acknowledge the assistance of the Euler Cluster Support Team.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Switzerland AG
About this paper
Cite this paper
Accaputo, G., Derlet, P.M., Arbenz, P. (2021). Solving Large-Scale Interior Eigenvalue Problems to Investigate the Vibrational Properties of the Boson Peak Regime in Amorphous Materials. In: Kozubek, T., Arbenz, P., Jaroš, J., Říha, L., Šístek, J., Tichý, P. (eds) High Performance Computing in Science and Engineering. HPCSE 2019. Lecture Notes in Computer Science(), vol 12456. Springer, Cham. https://doi.org/10.1007/978-3-030-67077-1_5
Download citation
DOI: https://doi.org/10.1007/978-3-030-67077-1_5
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-67076-4
Online ISBN: 978-3-030-67077-1
eBook Packages: Computer ScienceComputer Science (R0)