Martin Bernreuther

ms2: A molecular simulation tool for thermodynamic properties, new version release

Abstract A new version release (2.0) of the molecular simulation tool ms2 [S. Deublein et al., Comput. Phys. Commun. 182 (2011) 2350] is presented. Version 2.0 of ms2 features a hybrid parallelization based on MPI and OpenMP for molecular dynamics simulation to achieve higher scalability. Furthermore, the formalism by Lustig [R. Lustig, Mol. Phys. 110 (2012) 3041] is implemented, allowing for a systematic sampling of Massieu potential derivatives in a single simulation run. Moreover, the Green–Kubo formalism is extended for the sampling of the electric conductivity and the residence time. To remove the restriction of the preceding version to electro-neutral molecules, Ewald summation is implemented to consider ionic long range interactions. Finally, the sampling of the radial distribution function is added. Program summary Program title: m s 2 Catalogue identifier: AEJF_v2_0 Program summary URL: http://cpc.cs.qub.ac.uk/summaries/AEJF_v2_0.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 50375 No. of bytes in distributed program, including test data, etc.: 345786 Distribution format: tar.gz Programming language: Fortran90. Computer: The simulation program m s 2 is usable on a wide variety of platforms, from single processor machines to modern supercomputers. Operating system: Unix/Linux. Has the code been vectorized or parallelized?: Yes: Message Passing Interface (MPI) protocol and OpenMP Scalability is up to 2000 cores. RAM: m s 2 runs on single cores with 512 MB RAM. The memory demand rises with increasing number of cores used per node and increasing number of molecules. Classification: 7.7, 7.9, 12. External routines: Message Passing Interface (MPI) Catalogue identifier of previous version: AEJF_v1_0 Journal reference of previous version: Comput. Phys. Comm. 182 (2011) 2350 Does the new version supersede the previous version?: Yes. Nature of problem: Calculation of application oriented thermodynamic properties for fluids consisting of rigid molecules: vapor–liquid equilibria of pure fluids and multi-component mixtures, thermal and caloric data as well as transport properties. Solution method: Molecular dynamics, Monte Carlo, various classical ensembles, grand equilibrium method, Green–Kubo formalism, Lustig formalism Reasons for new version: The source code was extended to introduce new features. Summary of revisions: The new features of Version 2.0 include: Hybrid parallelization based on MPI and OpenMP for molecular dynamics simulation; Ewald summation for long range interactions; sampling of Massieu potential derivatives; extended Green–Kubo formalism for the sampling of the electric conductivity and the residence time; radial distribution function. Restrictions: None. The system size is user-defined. Typical problems addressed by m s 2 can be solved by simulating systems containing typically 1000–4000 molecules. Unusual features: Auxiliary feature tools are available for creating input files, analyzing simulation results and visualizing molecular trajectories. Additional comments: Sample makefiles for multiple operation platforms are provided. Documentation is provided with the installation package and is available at http://www.ms-2.de . Running time: The running time of m s 2 depends on the specified problem, the system size and the number of processes used in the simulation. E.g. running four processes on a “Nehalem” processor, simulations calculating vapor–liquid equilibrium data take between two and 12 hours, calculating transport properties between six and 24 hours. Note that the examples given above stand for the total running time as there is no post-processing of any kind involved in property calculations.

ls1 mardyn: The Massively Parallel Molecular Dynamics Code for Large Systems

The molecular dynamics simulation code ls1 mardyn is presented. It is a highly scalable code, optimized for massively parallel execution on supercomputing architectures and currently holds the world record for the largest molecular simulation with over four trillion particles. It enables the application of pair potentials to length and time scales that were previously out of scope for molecular dynamics simulation. With an efficient dynamic load balancing scheme, it delivers high scalability even for challenging heterogeneous configurations. Presently, multicenter rigid potential models based on Lennard-Jones sites, point charges, and higher-order polarities are supported. Due to its modular design, ls1 mardyn can be extended to new physical models, methods, and algorithms, allowing future users to tailor it to suit their respective needs. Possible applications include scenarios with complex geometries, such as fluids at interfaces, as well as nonequilibrium molecular dynamics simulation of heat and mass transfer.

591 TFLOPS Multi-trillion Particles Simulation on SuperMUC

Anticipating large-scale molecular dynamics simulations (MD) in nano-fluidics, we conduct performance and scalability studies of an optimized version of the code ls1 mardyn. We present our implementation requiring only 32 Bytes per molecule, which allows us to run the, to our knowledge, largest MD simulation to date. Our optimizations tailored to the Intel Sandy Bridge processor are explained, including vectorization as well as shared-memory parallelization to make use of Hyperthreading. Finally we present results for weak and strong scaling experiments on up to 146016 Cores of SuperMUC at the Leibniz Supercomputing Centre, achieving a speed-up of 133k times which corresponds to an absolute performance of 591.2 TFLOPS.

Homogeneous nucleation in supersaturated vapors of methane, ethane, and carbon dioxide predicted by brute force molecular dynamics

Molecular dynamics (MD) simulation is applied to the condensation process of supersaturated vapors of methane, ethane, and carbon dioxide. Simulations of systems with up to a 10(6) particles were conducted with a massively parallel MD program. This leads to reliable statistics and makes nucleation rates down to the order of 10(30) m(-3) s(-1) accessible to the direct simulation approach. Simulation results are compared to the classical nucleation theory (CNT) as well as the modification of Laaksonen, Ford, and Kulmala (LFK) which introduces a size dependence of the specific surface energy. CNT describes the nucleation of ethane and carbon dioxide excellently over the entire studied temperature range, whereas LFK provides a better approach to methane at low temperatures.

Teaching high-performance computing on a high-performance cluster

The university education in parallel and high-performance computing often suffers from a significant gap between the effects and potential performance taught in the lectures on the one hand and those practically experienced in exercises or lab courses on the other hand. With a small number of processors, the results obtained are often hardly convincing; however, supercomputers are rarely accessible to students doing their first steps in parallel programming. In this contribution, we present our experiences of how a state-of-the-art mid-size Linux cluster, bought and operated on a department level primarily for education and algorithm development purposes, can be used for teaching a large variety of HPC aspects. Special focus is put on the effects of such an approach on the intensity and sustainability of learning.

Molecular Simulation of Fluids with Short Range Potentials

Molecular modeling and simulation of thermophysical properties using short-range potentials covers a large variety of real simple fluids and mixtures. To study nucleation phenomena within a research project, a molecular dynamics simulation package is developed. The target platform for this software are Clusters of Workstations (CoW), like the Linux cluster Mozart with 64 dual nodes, which is available at the Institute of Parallel and Distributed Systems, or the HLRS cluster cacau, which is part of the Teraflop Workbench. The used algorithms and data structures are discussed as well as first simulation results.

First experiences with group projects in CSE education

In an effort to improve the way in which computational science and engineering is taught, the authors worked on two project-based software-focused modules in two different studyprograms at two German universities. This article describes both their expectations andoutcomes and addresses the question of whether-and how-software engineering practices should be taught in CSE courses.

Static and Dynamic Properties of Curved Vapour-Liquid Interfaces by Massively Parallel Molecular Dynamics Simulation

Curved fluid interfaces are investigated on the nanometre length scale by molecular dynamics simulation. Thereby, droplets surrounded by a metastable vapour phase are stabilized in the canonical ensemble. Analogous simulations are conducted for cylindrical menisci separating vapour and liquid phases under confinement in planar nanopores. Regarding the emergence of nanodroplets during nucleation, a non-equilibrium phenomenon, both the non-steady dynamics of condensation processes and stationary quantities related to supersaturated vapours are considered. Results for the truncated and shifted Lennard-Jones fluid and for mixtures of quadrupolar fluids confirm the applicability of the capillarity approximation and the classical nucleation theory.

Learning by doing: software projects in CSE education

Software development is one of the main routine activities in Computational Science and Engineering (CSE). Nevertheless, there is a huge gap between software engineering techniques available and established today in most fields where mainstream software is developed on the one hand and the typical extent of their application in a CSE context on the other hand. CSE curricula often reflect this tendency by not including software engineering topics adequately. This contribution reports experiences with a new course format called “student project” in the CSE masters program at TU Munchen. There, for about half a year, a group of 4-8 students cooperate on a software development project – this time dealing with molecular dynamics. Although it is one objective to get a well performing code, the projects focus is on the consequent application of software engineering and project management practices.

Molecular Modeling of Hydrogen Bonding Fluids: Phase Behavior of Industrial Fluids

Six new rigid models for Hydrogen chloride, Phosgene, Toluene, Benzene, Chlorobenzene and Ortho-Dichlorobenzene, that are based on quantum chemical calculations, are presented. Only the parameters of the dispersive and repulsive interactions are fitted to macroscopic thermodynamic properties to achieve an optimal agreement with experimental vapor-liquid equilibrium data.