DL_MESO_DPD, is the Dissipative Particle Dynamics (DPD) code from the mesoscopic simulation package DL_MESO , developed by Dr. Michael Seaton at Daresbury Laboratory (UK). This open source code is available from Science and Technology Facilities Council (STFC) under both academic (free) and commercial (paid) licenses. E-CAM’s Work-package 4 (WP4), Meso and Multi-scale Modelling, makes use of the DL_MESO_DPD code. See this article on our news feed, for more information on how it is used within E-CAM.
In order to accelerate the DL_MESO_DPD code on the latest and future exascale hardware, a first version for NVidia GPUs has been developed. This is only a starting point, it does not yet cover all the possible cases and it does not yet support multiple GPUs. However, it represents an HPC milestone for the application, complementing the already present parallel versions developed for shared and distributed memory (MPI/OpenMP).
DL_MESO_DPD, is the Dissipative Particle Dynamics (DPD) code from the mesoscopic simulation package DL_MESO, developed by Dr. Michael Seaton at Daresbury Laboratory (UK). This open source code is available from Science and Technology Facilities Council (STFC) under both academic (free) and commercial (paid) licenses.
In the last few years, modelling of rare events has made tremendous progress and several computational methods have been put forward to study these events. Despite this effort, new approaches have not yet been included, with adequate efficiency and scalability, in common simulation packages. One objective of the Classical Dynamics Work Package of the project E-CAM is to close this gap. The present text is an easy-to-read article on the use of path sampling methods to study rare events, and the role of the OpenPathSampling package to performing these simulations. Practical applications of rare events sampling and scalabilities opportunities in OpenPathSampling are also discussed.
The library LibOMM solves the Kohn-Sham equation as a generalized eigenvalue problem for a fixed Hamiltonian. It implements the orbital minimization method (OMM), which works within a density matrix formalism. The basic strategy of the OMM is to find the set of Wannier functions (WFs) describing the occupied subspace by direct unconstrained minimization of an appropriately-constructed functional. The density matrix can then be calculated from the WFs. The solver is usually employed within an outer self-consistency (SCF) cycle. Therefore, the WFs resulting from one SCF iteration can be saved and then re-used as the initial guess for the next iteration.
More information on the module’s documentation can be found here, and the source code is available from the E-CAM Gitlab here. The algorithms and implementation of the library are described in https://arxiv.org/abs/1312.1549v1.
This module is an effort from the Electronic Structure Library Project (ESL), and it was initiated during an E-CAM Extended Software Development Workshop in Zaragoza in June 2016. This and other codes revolved around the broad theme of solvers, were recently reported in Deliverable D2.1.: Electronic structure E-CAM modules I, available for download and consultation here.
Practical application and exploitation of the module
libOMM is one of the libraries supported and enhanced by the Electronic Structure Infrastructure ELSI , which in turn is interfaced with the DGDFT, FHI-aims, NWChem, and SIESTA codes.
 The electronic structure infrastructure ELSI provides and enhances scalable, open-source software library solutions for electronic structure calculations in materials science, condensed matter physics, chemistry, molecular biochemistry, and many other fields [https://arxiv.org/abs/1705.11191v1].
The development of a new methodology, known as Accurate NeurAl networK engINe for Molecular Energies (ANAKIN-ME, or ANI for short), is able, it is claimed, to describe the forces in molecules as accurately as density functional theory (DFT), but hundreds of thousands of times faster. This combination of speed and accuracy could allow researchers to tackle problems that were previously impossible, leading to breakthroughs in the arenas of drug discovery and materials science. Details of the method by J. S. Smith O. Isayev and A. E. Roitberg built on earlier work of Michele Parrinello are available in a 2017 publication entitled “ANI-1: an extensible neural network potential with DFT accuracy at force field computational cost” arXiv:1610.08935v4 .
The methodology has been ported to NVIDIA, and will be the subject of a webinar hosted by NVIDIA, University of Florida, University of North Carolina, on 20 September 2017 from 10am-11am PST . Sign up for the webinar here.
E-CAM strongly recommends software developers interested in HPC to attend the webinar series on Best Practices for HPC organized by the IDEAS project in collaboration with the DOE/ASCR computing facilities (ALCF, NERSC, and OLCF), and the Exascale Computing Project (ECP).
Information on the webinars programme available here.
The present module, gen_dipole.f90, is a generalization of the dipole.f90 post-processing utility of DL_MESO_DPD, the Dissipative Particle Dynamics (DPD) code from the DL_MESO package. It processes the trajectory (HISTORY) files to obtain the charge dipole moments of all the (neutral) molecules in the system. It produces files dipole_* containing the time evolution of relevant quantities (see module documentation for more information). In the case of a single molecular species, it also prints to the standard output the Kirkwood number and the relative electric permittivity for this species, together with an estimate for their errors (standard error).
The module can be applied to systems including molecules with a generic charge structure, as long as each molecule is neutral (otherwise the charge dipole moment would be frame-dependent).
gen_dipole.f9 is available under BSD license, and is a post-processing utilities to be used with DL_MESO in its last released version, version 2.6 (dating November 2015). They have been developed in the context of the pilot project 1 of WP 4, which concerns the derivation of a realistic polarizable model of water to be used in DPD simulations. This project involves a collaboration between computational scientists (STFC Daresbury), academia (University of Manchester), and industry (Unilever). This and other modules based on DL_MESO_DPD have recently been reported in deliverable D4.2: Meso- and multi-scale modelling E-CAM modules I, available for consultation here.
SQARE (solvers for quantum atomic radial equations) is a library of utilities intended for dealing with functions discretized on radial meshes, wave-equations with spherical symmetry and their corresponding quantum states. The utilities are segregated into three levels: radial grids and functions, ODE solvers, and states.
An event to bring together the quantum information and HPC communities to discuss their specific expertise and outline the bridges that will eventually identify: (1) the future role of quantum technologies in scientific fields where HPC is currently dominant; (2) the use of existing HPC platforms to demonstrate the potentialities of future quantum technologies to simulate materials and biological systems.
E-CAM WP leader Sara Bonella and the industrial partner from IBM, Ivano Tavernelli, are co-organizers of this event.
For more information on this workshops that will take place in ETH Zurich 22-24 August 2017 see here.
The ETP4HPC initiative is inviting the industrial HPC users to a attend a workshop in June 22, Frankfurt, to discuss their needs and expectations regarding the potential use of Extreme Scale Demonstrators’ (EsDs).