Dipl.Ing. Daniel Tameling
Former Ph.D. student
Education
02/2012  08/2016  Postgraduate student at the Aachen Institute for Advanced Study in Computational Engineering Science (AICES), RWTH Aachen University. 

10/2005  09/2011  Diplom in Mechanical Engineering (equiv. to M.Sc.), Karlsruhe Institute of Technology (KIT) 
Research
Recent Publications (link to complete list)
Journal Article
 Multilevel Summation for Dispersion: A LinearTime Algorithm for 1/r^6 PotentialsJournal 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 LinearTime Algorithm for 1/r^6 Potentials", journal = "Journal of Chemical Physics", year = 2014, volume = 140, pages = 24105, month = jan, url = "https://arxiv.org/pdf/1308.4005.pdf" }
abstractwebPDFbibtexThe multilevel summation (MLS) method was developed to evaluate longrange interactions in molecular dynamics (MD) simulations. MLS was initially introduced for Coulombic potentials; we have extended this method to dispersion interactions. While formally shortranged, for an accurate calculation of forces and energies in cases such as in interfacial systems, dispersion potentials require longrange methods. Since longrange 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 meshbased Ewald methods like the particleparticle particlemesh and particle mesh Ewald methods. Unlike meshbased 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 meshbased 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.
Technical Report
 A Note on Time Measurements in LAMMPSAachen Institute for Computational Engineering Science, RWTH Aachen, February 2016.
Technical Report AICES2016/021.@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 AICES2016/021", url = "http://arxiv.org/abs/1602.05566" }
abstractPDFbibtexWe 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.
Recent Talks (link to complete list)
 Annual ReportAICES Graduate School.
Aachen, Germany, April 2014.  Multilevel Summation for Dispersion: A LinearTime Algorithm for 1/r^6 Potentials 2013 AIChE Annual Meeting.
San Francisco, USA, November 2013.abstractPDFThe multilevel summation method (MLS) was developed to evaluate longrange 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 shortranged, longrange methods have to be used to calculate accurately dispersion forces in certain situations, such as in interfacial systems. Because longrange 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 meshbased Ewald methods like the particleparticle particlemesh and particle mesh Ewald methods. Because, unlike meshbased 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 meshbased 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 meshbased methods.  Multilevel Summation for Dispersion: A LinearTime Algorithm for 1/r^6 PotentialsInternational Conference on Scientific Computation and Differential Equations (SciCADE).
Valladolid, Spain, September 2013.abstractPDFThe multilevel summation (MLS) method was developed to evaluate longrange 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 shortranged, dispersion potentials require longrange methods for accurate calculation of forces and energies in certain situations, such as in interfacial systems. Because longrange 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 longrange solvers, e.g. the meshbased 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.
Poster Presentations

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