Extended Software Development Workshop: Mesoscopic simulation models and High-Performance Computing

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If you are interested in attending this event, please visit the CECAM website here.

Workshop Description

In Discrete Element Methods the equation of motion of large number of particles is numerically integrated to obtain the trajectory of each particle [1]. The collective movement of the particles very often provides the system with unpredictable complex dynamics inaccessible via any mean field approach. Such phenomenology is present for instance in a seemingly simple systems such as the hopper/silo, where intermittent flow accompanied with random clogging occurs [2]. With the development of computing power alongside that of the numerical algorithms it has become possible to simulate such scenarios involving the trajectories of millions of spherical particles for a limited simulation time. Incorporating more complex particle shapes [3] or the influence of the interstitial medium [4] rapidly decrease the accessible range of the number of particles.

Another class of computer simulations having a huge popularity among the science and engineering community is the Computational Fluid Dynamics (CFD). A tractable method for performing such simulations is the family of Lattice Boltzmann Methods (LBMs) [5]. There, instead of directly solving the strongly non-linear Navier-Stokes equations, the discrete Boltzmann equation is solved to simulate the flow of Newtonian or non-Newtonian fluids with the appropriate collision models [6,7]. The method resembles a lot the DEMs as it simulates the the streaming and collision processes across a limited number of intrinsic particles, which evince viscous flow applicable across the greater mass.

As both of the methods have gained popularity in solving engineering problems, and scientists have become more aware of finite size effects, the size and time requirements to simulate practically relevant systems using these methods have escaped beyond the capabilities of even the most modern CPUs [8,9]. Massive parallelization is thus becoming a necessity. This is naturally offered by graphics processing units (GPUs) making them an attractive alternative for running these simulations, which consist of a large number of relatively simple mathematical operations readily implemented in a GPU [8,9].

 

References

[1] P.A. Cundall and O.D.L. Strack, Geotechnique 29, 47–65 (1979).
[2] H. G. Sheldon and D. J. Durian, Granular Matter 6, 579-585 (2010).
[3] A. Khazeni, Z. Mansourpour Powder Tech. 332, 265-278 (2018).
[4] J. Koivisto, M. Korhonen, M. J. Alava, C. P. Ortiz, D. J. Durian, A. Puisto, Soft Matter 13 7657-7664 (2017).
[5] S. Succi,The lattice Boltzmann equation: for fluid dynamics and beyond. Oxford university press, (2001).
[6] L. S. Luo, W. Liao, X. Chen, Y. Peng, W. Zhang, Phys. Rev. E, 83, 056710 (2011).
[7] S. Gabbanelli, G.Drazer, J. Koplik, Phys. Rev. E, 72, 046312 (2005).
[8] N Govender, R. K. Rajamani, S. Kok, D. N. Wilke, Minerals Engin. 79, 152-168 (2015).
[9] P.R. Rinaldi, E. A. Dari, M. J. Vénere, A. Clausse, Simulation Modelling Practice and Theory, 25, 163-171 (2012).

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A Conversation on The Fourth Industrial Revolution: Opportunities & Trends for Particle Based Simulation

 

Abstract

In the margins of a recent multiscale simulation workshop a discussion began between a prominent  pharmaceutical industry scientist, and E-CAM and EMMC regarding the unfolding Fourth Industrial Revolution and the role of particle based simulation and statistical methods there.  The impact of simulation  is predicted to become very significant.  This discussion is intended to create awareness of the general public, of how industry 4.0 is initiating in companies, and  how academic research will support that transformation.

Authors: Prof. Pietro Asinari (EMMC and Politecnico di Torino, denoted below as PA) and Dr. Donal MacKernan (E-CAM and University College Dublin, denoted below as  DM) , and a prominent  pharmaceutical industry scientist (name withheld at author’s request as  the view expressed is a personal one, denoted below as  IS)

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Multi-GPU version of DL_MESO_DPD

This module implements the first version of the DL_MESO_DPD Mesoscale Simulation Package, with multiple NVidia Graphical Processing Units (GPUs).

In this module the main framework of a multi-GPU version of the DL_MESO_DPD code has been developed. The exchange of data between GPUs overlaps with the computation of the forces for the internal cells of each partition (a domain decomposition approach based on the MPI parallel version of DL_MESO_DPD has been followed). The current implementation is a proof of concept and relies on slow transfers of data from the GPU to the host and vice-versa. Faster implementations will be explored in future modules.

Future plans include benchmarking of the code with different data transfer implementations other than the current (trivial) GPU-host-GPU transfer mechanism. These are: of Peer To Peer communication within a node, CUDA-aware MPI, and CUDA-aware MPI with Direct Remote Memory Access (DRMA).

Practical application and exploitation of the code

Dissipative Particle Dynamics (DPD) is routinely used in an industrial context to find out the static and dynamic behaviour of soft-matter systems. Examples include colloidal dispersions, emulsions and other amphiphilic systems, polymer solutions, etc. Such materials are being produced or processed in industries like cosmetics, food, pharmaceutics, biomedicine, etc. Porting the method to GPUs is thus inherently useful in order to provide cheaper calculations.

See more information in the industry success story recently reported by E-CAM.

Software documentation and link to the source code can be found in our E-CAM software Library here.

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E-CAM State of the Art Workshop: CHALLENGES IN MULTIPHASE FLOWS

We would like to draw your attention to a school cum workshop on

CHALLENGES IN MULTIPHASE FLOWS

that will run on Dec 9-12, 2019, at the Monash University Prato Center,
see http://monash.it/, in Tuscany. The event is an E-CAM state-of-the-art
workshop, and its aim is to focus on computer
simulation methods for multiphase systems and their dynamics, and
their strengths and shortcomings. This is a topic that is relevant in
physics, mathematics, chemistry, and engineering, and we are trying to
bring these communities together for a fruitful exchange. At the same
time, a set of advanced lectures at the school is intended to provide
a solid foundation of background knowledge. For more information (in
particular, the list of Invited Speakers), see the

Main web site for the event

Registration is now open. Regular participants need to pay a fee of
500 Australian Dollars (roughly 300 Euros) for meals etc.; however the
first 25 students (with proven status) who register may attend for free.

DEADLINE for registration and abstract submission is September 22.

Please do not hesitate to contact the organisers (contact information on the main website for the event) if you feel you need more information beyond what is provided on the web.

The Organisers

Burkhard Duenweg, Mainz
Ravi Prakash Jagadeeshan, Melbourne
Ignacio Pagonabarraga, Lausanne

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Extension of the ParaDiS code to include precipitate interactions, and code optimisation to run on HPC environment


Here present two featured software modules of the month:

  1. ParaDiS with precipitates
  2. ParaDiS with precipitates optimized to HPC environment

that provide extensions to the ParaDIS Discrete dislocation dynamics (DDD) code (LLNL, http://paradis.stanford.edu/) where dislocation/precipitate interactions are included. Module 2 was built to run the code on an HPC environment, by optimizing the original code for the Cray XC40 cluster at CSC in Finland. Software was developed by E-CAM partners at CSC and Aalto University (Finland).

Practical application and exploitation of the codes

The ParaDiS code is a free large scale dislocation dynamics (DD) simulation code to study the fundamental mechanisms of plasticity. However, DDD simulations don’t always take into account scenarios of impurities interacting with the dislocations and their motion. The consequences of the impurities are multiple: the yield stress is changed, and in general the plastic deformation process is greatly affected. Simulating these by DDD allows to look at a large number of issues from materials design to controlling the yield stress and may be done in a multiscale manner by computing the dislocation-precipitate interactions from microscopic simulations or by coarse-graining the DDD results for the stress-strain curves on the mesoscopic scale to more macroscopic Finite Element Method.

Modules 1 and 2 provide therefore an extension of the ParaDIS code by including dislocation/precipitate interactions. The possibility to run the code on HPC environments is also provided.

Software documentation and link to the source code can be found in our E-CAM software Library here.

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Upcoming event: Extended Software Development Workshop in Mesoscopic simulation models and HPC


E-CAM partners at Aalto University (CECAM Finish Node) in collaboration with the HPC training experts from the CSC Supercomputing Centre, are organizing a joint Extended Software Development Workshop from 15-19 October 2019 , aimed at people interested in particle based methods, such as the Discrete Element and Lattice Boltzmann Methods, and on their massive parallelization using GPU architectures. The workshop will mix three different ingredients: (1) workshop on state-of-the-art challenges in computational science and software, (2) CSC -run school, and (3) coding sessions with the aid of CSC facilities and expertise.

How to Apply

Follow the instruction at the CECAM website for the event: https://www.cecam.org/workshop1752/

Organizers

  • Mikko Alava
    Aalto University, Finland
  • Brian Tighe
    TU Delft, The Netherlands
  • Jan Astrom
    CSC It center for science, Finland
  • Antti Puisto
    Aalto University, Finland

Location

CECAM-FI Node, Aalto University, Finland

Dates

October 15 – 19, 2019

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Mesoscale simulation of billion atom complex systems using thousands of GPGPU’s, an industry success story


Dr. Jony Castagna, Science and Technology Facilities Council, United Kingdom


Abstract

Jony Castagna recounts his transition from industry scientist to research software developer at the STFC, his E-CAM rewrite of  DL_MESO allowing the simulation of billion atom systems on thousands of GPGPUs, and his latest role as Nvidia ambassador focused on machine learning.

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Abrupt GC-AdResS: A new and more general implementation of the Grand Canonical Adaptive Resolution Scheme (GC-AdResS)

The Grand Canonical Adaptive resolution scheme (GC-AdResS) gives a methodological description to partition a simulation box into different regions with different degrees of accuracy. For more details on the theory see Refs. [1,2,3].

In the context of an E-CAM pilot project focused on the development of the GC-AdResS scheme, an updated version of GC-AdResS was built and implemented in GROMACS, as reported in https://aip.scitation.org/doi/10.1063/1.5031206 (open access version: https://arxiv.org/abs/1806.09870). The main goal of the project is to develop a library or recipe with which GC-AdResS can be implemented in any Classical MD Code.

The current implementation of GC- AdResS in GROMACS has several performance problems. We know that the main performance loss of AdResS simulations in GROMACS is in the neighbouring list search and the generic serial force calculation linking the atomistic (AT) and coarse grained (CG) forces together via a smooth weighting function. Thus, to remove the bottleneck with respect to performance and a hindrance regarding the easy/general implementation into other codes and eliminate the non optimized force calculation, we had to change the neighbourlist search. This lead to a considerable speed up of the code. Furthermore it decouples the method directly from the core of any MD code, which does not hinder the performance and makes the scheme hardware independent[4].

This module presents a very straight forward way to implement a new partitioning scheme in GROMACS . And this solves two problems which affect the performance, the neighborlist search and the generic force kernel.

Information about module purpose, background information, software installation, testing and a link to the source code, can be found in our E-CAM software Library here.

E-CAM Deliverables D4.3[5] and D4.4[6] present more modules developed in the context of this pilot project.

References

[1] L. Delle Site and M. Praprotnik, “Molecular Systems with Open Boundaries: Theory and Simulation,” Phys. Rep., vol. 693, pp. 1–56, 2017

[2] H.Wang, C. Schütte, and L.Delle Site, “Adaptive Resolution Simulation (AdResS): A Smooth Thermodynamic and Structural Transition fromAtomistic to Coarse Grained Resolution and Vice Versa in a Grand Canonical Fashion,” J. Chem. Theory Comput., vol. 8, pp. 2878–2887, 2012

[3] H. Wang, C. Hartmann, C. Schütte, and L. Delle Site, “Grand-Canonical-Like Molecular-Dynamics Simulations by Using an Adaptive-Resolution Technique,” Phys. Rev. X, vol. 3, p. 011018, 2013

[4] C. Krekeler, A. Agarwal, C. Junghans, M. Prapotnik and L. Delle Site, “Adaptive resolution molecular dynamics technique: Down to the essential”, J. Chem. Phys. 149, 024104

[5] B. Duenweg, J. Castagna, S. Chiacchera, H. Kobayashi, and C. Krekeler, “D4.3: Meso– and multi–scale modelling E-CAM modules II”, March 2018 . [Online]. Available: https://doi.org/10.5281/zenodo.1210075

[6] B. Duenweg, J. Castagna, S. Chiacchera, and C. Krekeler, “D4.4: Meso– and multi–scale modelling E-CAM modules III”, Jan 2019 . [Online]. Available: https://doi.org/10.5281/zenodo.2555012

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E-CAM related work labeled as “Excellent Science” by the EC Innovation Radar Initiative

The Innovation Radar aims to identify high-potential innovations and innovators. It is an important source of actionable intelligence on innovations emerging from research and innovation projects funded through European Union programmes.

E-CAM is associated to the following Innovations (Innovation topic: excellence science):

    1. Improved Simulation Software Packages for Molecular Dynamics (see link)
    2. Improved software modules for Meso– and multi–scale modelling (see link)

Related to the work of our E-CAM funded Postdoctoral researchers supervised by scientists in the team, working on:

  • Development of the OpenPathSampling package to study rare events  (Universiteit van Amsterdam). Link1
  • Implementation of GPU version of DL_MESO_DPD (Hartree Centre (STFC)). Link
  • Development of polarizable mesoscale model for DL_MESO_DPD (Hartree Centre (STFC)). Link
  • Development of the GC-AdResS scheme (Freie Universitaet Berlin). Link

  • Implementation of hierarchical strategy on ESPResSO++ (Max Plank Institute for Polymer Research, Mainz). Link
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New E-CAM publication is out: “Molecular Dynamics of Open Systems: Construction of a Mean‐Field Particle Reservoir”



New publication from E-CAM partners working at the Institute of Mathematics of the Freie Universität Berlin:

Molecular Dynamics of Open Systems: Construction of a Mean‐Field Particle Reservoir

Authors: Luigi Delle Site, Christian Krekeler, John Whittaker, Animesh Agarwal, Rupert Klein, and Felix Höfling

Adv. Theory Simul. 2019, 1900014, DOI: 10.1002/adts.201900014 (Open access)

Synopsis

A procedure for the construction of a particle and energy reservoir for the simulation of open molecular systems is presented. The reservoir is made of non‐interacting particles (tracers), embedded in a mean‐field. The tracer molecules acquire atomistic resolution upon entering the atomistic region, while atomistic molecules become tracers after crossing the atomistic boundary.

Abstract

The simulation of open molecular systems requires explicit or implicit reservoirs of energy and particles. Whereas full atomistic resolution is desired in the region of interest, there is some freedom in the implementation of the reservoirs. Here, a combined, explicit reservoir is constructed by interfacing the atomistic region with regions of point-like, non-interacting particles (tracers) embedded in a thermodynamic mean field. The tracer molecules acquire atomistic resolution upon entering the atomistic region and equilibrate with this environment, while atomistic molecules become tracers governed by an effective mean-field potential after crossing the atomistic boundary. The approach is extensively tested on thermodynamic, structural, and dynamic properties of liquid water. Conceptual and numerical advantages of the procedure as well as new perspectives are highlighted and discussed.

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