Cickovski T, Chatterjee S, Wenger J, Sweet CR, and Izaguirre JA
Journal of computational chemistry [J Comput Chem] 2010 May; Vol. 31 (7), pp. 1345-56.
Molecular dynamics (MD) simulation involves solving Newton's equations of motion for a system of atoms, by calculating forces and updating atomic positions and velocities over a timestep Deltat. Despite the large amount of computing power currently available, the timescale of MD simulations is limited by both the small timestep required for propagation, and the expensive algorithm for computing pairwise forces. These issues are currently addressed through the development of efficient simulation methods, some of which make acceptable approximations and as a result can afford larger timesteps. We present MDLab, a development environment for MD simulations built with Python which facilitates prototyping, testing, and debugging of these methods. MDLab provides constructs which allow the development of propagators, force calculators, and high level sampling protocols that run several instances of molecular dynamics. For computationally demanding sampling protocols which require testing on large biomolecules, MDL includes an interface to the OpenMM libraries of Friedrichs et al. which execute on graphical processing units (GPUs) and achieve considerable speedup over execution on the CPU. As an example of an interesting high level method developed in MDLab, we present a parallel implementation of the On-The-Fly string method of Maragliano and Vanden-Eijnden. MDLab is available at http://mdlab.sourceforge.net. (Copyright 2009 Wiley Periodicals, Inc.)
Journal of Computational Chemistry. March 2013, Vol. 34 Issue 6, p492, 13 p.
Quantum theory -- Analysis
Keywords: interactive quantum chemistry; reduced basis; adaptive; divide-and-conquer; ASED-MO Abstract We present a novel Block-Adaptive Quantum Mechanics (BAQM) approach to interactive quantum chemistry. Although quantum chemistry models are known to be computationally demanding, we achieve interactive rates by focusing computational resources on the most active parts of the system. BAQM is based on a divide-and-conquer technique and constrains some nucleus positions and some electronic degrees of freedom on the fly to simplify the simulation. As a result, each time step may be performed significantly faster, which in turn may accelerate attraction to the neighboring local minima. By applying our approach to the nonself-consistent Atom Superposition and Electron Delocalization Molecular Orbital theory, we demonstrate interactive rates and efficient virtual prototyping for systems containing more than a thousand of atoms on a standard desktop computer. A[c] 2012 Wiley Periodicals, Inc. Author Affiliation: NANO-D-INRIA Grenoble-Rhone-Alpes/CNRS Laboratoire Jean Kuntzmann, Rhone-Alpes 655, Avenue de l'Europe, Saint Ismier Cedex 38335, France NANO-D, INRIA Grenoble, Rhone-Alpes 655, Avenue de l'Europe, Saint-Ismier Cedex 38335, France Supporting information: Additional Supporting Information may be found in the online version of this article Additional Supporting Information may be found in the online version of this article.