NAMD is a parallel molecular dynamics code designed for high-performance simulation of large biomolecular systems. NAMD scales to hundreds of processors on high-end parallel platforms, as well as tens of processors on low-cost commodity clusters, and also runs on individual desktop and laptop computers. NAMD works with AMBER and CHARMM potential functions, parameters, and file formats. This article, directed to novices as well as experts, first introduces concepts and methods used in the NAMD program, describing the classical molecular dynamics force field, equations of motion, and integration methods along with the efficient electrostatics evaluation algorithms employed and temperature and pressure controls used. Features for steering the simulation across barriers and for calculating both alchemical and conformational free energy differences are presented. The motivations for and a roadmap to the internal design of NAMD, implemented in C++ and based on Charm++ parallel objects, are outlined. The factors affecting the serial and parallel performance of a simulation are discussed. Finally, typical NAMD use is illustrated with representative applications to a small, a medium, and a large biomolecular system, highlighting particular features of NAMD, for example, the Tcl scripting language. The article also provides a list of the key features of NAMD and discusses the benefits of combining NAMD with the molecular graphics/sequence analysis software VMD and the grid computing/collaboratory software BioCoRE. NAMD is distributed free of charge with source code at www.ks.uiuc.edu.

/pdf/scalable-molecular-dynamics-with-namd-51o1z7rwp8.pdf

Scalable molecular dynamics with NAMD

/pdf/scalable-molecular-dynamics-with-namd-3j7xyc70g4.pdf

Scalable Molecular Dynamics with NAMD

Fluid dynamic turbulence is one of the most challenging computational physics problems because of the extremely wide range of time and space scales involved, the strong nonlinearity of the governing equations, and the many practical and important applications. While most linear fluid instabilities are well understood, the nonlinear interactions among them makes even the relatively simple limit of homogeneous isotropic turbulence difficult to treat physically, mathematically, and computationally. Turbulence is modeled computationally by a two-stage bootstrap process. The first stage, direct numerical simulation, attempts to resolve the relevant physical time and space scales but its application is limited to diffusive flows with a relatively small Reynolds number (Re). Using direct numerical simulation to provide a database, in turn, allows calibration of phenomenological turbulence models for engineering applications. Large eddy simulation incorporates a form of turbulence modeling applicable when the large-scale flows of interest are intrinsically time dependent, thus throwing common statistical models into question. A promising approach to large eddy simulation involves the use of high-resolution monotone computational fluid dynamics algorithms such as flux-corrected transport or the piecewise parabolic method which have intrinsic subgrid turbulence models coupled naturally to the resolved scales in the computed flow. The physical considerations underlying and evidence supporting this monotone integrated large eddy simulation approach are discussed.

New insights into large eddy simulation

We present the latest version of the Groningen Molecular Simulation program package, GROMOS05. It has been developed for the dynamical modelling of (bio)molecules using the methods of molecular dynamics, stochastic dynamics, and energy minimization. An overview of GROMOS05 is given, highlighting features not present in the last major release, GROMOS96. The organization of the program package is outlined and the included analysis package GROMOS++ is described. Finally, some applications illustrating the various available functionalities are presented.

/pdf/the-gromos-software-for-biomolecular-simulation-gromos05-4ga1gu8edn.pdf

The GROMOS software for biomolecular simulation: GROMOS05

In this article we consider finite element methods for approximating the solution of partial differential equations on surfaces. We focus on surface finite elements on triangulated surfaces, implicit surface methods using level set descriptions of the surface, unfitted finite element methods and diffuse interface methods. In order to formulate the methods we present the necessary geometric analysis and, in the context of evolving surfaces, the necessary transport formulae. A wide variety of equations and applications are covered. Some ideas of the numerical analysis are presented along with illustrative numerical examples.

/pdf/finite-element-methods-for-surface-pdes-1w1k25wxnx.pdf

Finite element methods for surface PDEs

PPM: a highly efficient parallel particle-mesh library for the simulation of continuum systems

https://www.zora.uzh.ch/id/eprint/39538/1/sdarticle.pdf

A hybrid model for three-dimensional simulations of sprouting angiogenesis.

Billion vortex particle direct numerical simulations of aircraft wakes

https://www-ljk.imag.fr/membres/Georges-Henri.Cottet/ref38.pdf

GPU accelerated simulations of bluff body flows using vortex particle methods

This paper presents a novel, multiresolution Lagrangian particle method with enhanced, wavelet‐based adaptivity. The method is formulated for transport problems and combines the efficiency of wavelet collocation with the inherent numerical stability of particle methods. The accuracy and efficiency of the present method is assessed on a number of benchmark problems pertaining to interface capturing and transport. The method is compared with existing techniques demonstrating its advantages and limitations. The present approach leads to a new generation of particle methods with multiresolution capabilities.

Michael Bergdorf

Papers

PPM: a highly efficient parallel particle-mesh library for the simulation of continuum systems

A hybrid model for three-dimensional simulations of sprouting angiogenesis.

Billion vortex particle direct numerical simulations of aircraft wakes

GPU accelerated simulations of bluff body flows using vortex particle methods

A Lagrangian Particle‐Wavelet Method