Dipl.-Ing. Daniel Tameling

Former Ph.D. student

Education

Research

• Parallel Algorithms for Molecular Simulations

Recent Publications (link to complete list)

Journal Article

1. Multilevel Summation for Dispersion: A Linear-Time Algorithm for 1/r^6 Potentials
   Daniel Tameling, Paul Springer, Paolo Bientinesi and Ahmed E. Ismail
   Journal of Chemical Physics, Volume 140, pp. 024105, January 2014.

   @article{Tameling2014:590,
       author  = "Daniel Tameling and Paul Springer and Paolo Bientinesi and {Ahmed E.} Ismail",
       title   = "Multilevel Summation for Dispersion: A Linear-Time Algorithm for 1/r^6 Potentials",
       journal = "Journal of Chemical Physics",
       year    = 2014,
       volume  = 140,
       pages   = 24105,
       month   = jan,
       doi     = "10.1063/1.4857735",
       url     = "https://arxiv.org/pdf/1308.4005.pdf"
   }

   The multilevel summation (MLS) method was developed to evaluate long-range interactions in molecular dynamics (MD) simulations. MLS was initially introduced for Coulombic potentials; we have extended this method to dispersion interactions. While formally short-ranged, for an accurate calculation of forces and energies in cases such as in interfacial systems, dispersion potentials require long-range methods. Since long-range solvers tend to dominate the time needed to perform MD calculations, increasing their performance is of vital importance. The MLS method offers some significant advantages when compared to mesh-based Ewald methods like the particle-particle particle-mesh and particle mesh Ewald methods. Unlike mesh-based Ewald methods, MLS does not use fast Fourier transforms and is thus not limited by communication and bandwidth concerns. In addition, it scales linearly in the number of particles, as compared to the O(N log N) complexity of the mesh-based Ewald methods. While the structure of the MLS method is invariant for different potentials, every algorithmic step had to be adapted to accommodate the 1/r^6 form of the dispersion interactions. In addition, we have derived error bounds, similar to those obtained by Hardy for the electrostatic MLS. Using a prototype implementation, we can already demonstrate the linear scaling of the MLS method for dispersion, and present results establishing the accuracy and efficiency of the method.

   abstractwebPDFbibtexhide

Technical Report

1. A Note on Time Measurements in LAMMPS
   Daniel Tameling, Paolo Bientinesi and Ahmed E. Ismail
   Aachen Institute for Computational Engineering Science, RWTH Aachen, February 2016.
   Technical Report AICES-2016/02-1.

   @techreport{Tameling2016:140,
       author      = "Daniel Tameling and Paolo Bientinesi and {Ahmed E.} Ismail",
       title       = "A Note on Time Measurements in LAMMPS",
       institution = "Aachen Institute for Computational Engineering Science, RWTH Aachen",
       year        = 2016,
       month       = feb,
       note        = "Technical Report AICES-2016/02-1",
       url         = "http://arxiv.org/abs/1602.05566"
   }

   We examine the issue of assessing the efficiency of components of a parallel program at the example of the MD package LAMMPS. In particular, we look at how LAMMPS deals with the issue and explain why the approach adopted might lead to inaccurate conclusions. The misleading nature of this approach is subsequently verified experimentally with a case study. Afterwards, we demonstrate how one should correctly determine the efficiency of the components and show what changes to the code base of LAMMPS are necessary in order to get the correct behavior.

   abstractPDFbibtexhide

Recent Talks (link to complete list)

1. Annual Report
   Daniel Tameling
   AICES Graduate School.
   Aachen, Germany, April 2014.
   PDFhide
2. Multilevel Summation for Dispersion: A Linear-Time Algorithm for 1/r^6 Potentials
   Daniel Tameling
   2013 AIChE Annual Meeting.
   San Francisco, USA, November 2013.
   The multilevel summation method (MLS) was developed to evaluate long-range interactions in molecular dynamics (MD) simulations. Previously MLS was investigated in detail for the electrostatic potential by Hardy et al., and we have applied this new method to dispersion interactions. While dispersion interactions are formally short-ranged, long-range methods have to be used to calculate accurately dispersion forces in certain situations, such as in interfacial systems. Because long-range solvers tend to dominate the time needed to perform a step in MD calculations, increasing their performance is of vital importance. The multilevel summation method offers some significant advantages when compared to mesh-based Ewald methods like the particle-particle particle-mesh and particle mesh Ewald methods. Because, unlike mesh-based Ewald methods, the multilevel summation method does not use fast Fourier transforms, they are not limited by communication and bandwidth concerns. In addition, it scales linearly in the number of particles, as compared to the O(N log N) complexity of the mesh-based methods. While the structure of the Multilevel Summation is invariant for different potentials, every algorithmic step had to be adapted to accommodate the 1/r^6 form of the dispersion interactions. In addition, we have derived strict error bounds, similar to those obtained by Hardy for the electrostatic multilevel summation method. Using an unoptimized implementation in C++, we can already demonstrate the linear scaling of the multilevel summation method for dispersion, and present results that suggest it will be competitive in terms of accuracy and performance with mesh-based methods.

   abstractPDFhide
3. Multilevel Summation for Dispersion: A Linear-Time Algorithm for 1/r^6 Potentials
   Daniel Tameling
   International Conference on Scientific Computation and Differential Equations (SciCADE).
   Valladolid, Spain, September 2013.
   The multilevel summation (MLS) method was developed to evaluate long-range interactions in molecular dynamics (MD) simulations. In MD the MLS was initially introduced for Coulombic potentials by Skeel et al., based on the multilevel matrix summation; we have extended the MLS to dispersion interactions. While formally short-ranged, dispersion potentials require long-range methods for accurate calculation of forces and energies in certain situations, such as in interfacial systems. Because long-range solvers tend to dominate the time needed to perform a step in MD calculations, increasing their performance is of vital importance. Because of its properties, the MLS is particularly attractive compared to other long-range solvers, e.g. the mesh-based Ewald and the fast Multipole methods. While the structure of the MLS is invariant for different potentials, every algorithmic step had to be adapted to accommodate the 1/r^6 form of the dispersion interactions.

   abstractPDFhide

Poster Presentations

1. Multilevel Summation for Dispersion: A Linear-Time Algorithm for 1/r^6 Potentials
   Daniel Tameling
   European Symposium on Applied Thermodynamics.
   Eindhoven, Netherlands, July 2014
   PDF
2. Multilevel Summation for Dispersion: A Linear-Time Algorithm for 1/r^6 Potentials
   Daniel Tameling
   Fast Methods for Long Range Interactions in Complex Particle Systems.
   Jülich, Germany, Sep. 2013
   PDF