Pub Date : 2024-06-28DOI: 10.1016/j.cpc.2024.109293
Vasileios Angelidakis , Katia Boschi , Karol Brzeziński , Robert A. Caulk , Bruno Chareyre , Carlos Andrés del Valle , Jérôme Duriez , Anton Gladky , Dingeman L.H. van der Haven , Janek Kozicki , Gerald Pekmezi , Luc Scholtès , Klaus Thoeni
This contribution presents the key elements of YADE, an extensible open-source framework for dynamic simulations. During the past 19 years, YADE has evolved from “Yet Another Dynamic Engine” to a versatile multiscale and multiphysics solver, counting a large, active, and growing community of users and developers. The computationally intense parts of the source code are written in C++, using flexible object models that allow for easy implementation of new features. The source code is wrapped in Python, equipping the software with an interactive kernel used for rapid and concise scene construction, simulation control, post-processing, and debugging. The project, including documentation and examples, is hosted on https://yade-dem.org, while the source code is freely available on GitLab. Over the last decade, YADE has expanded in terms of capabilities thanks to the contribution of many developers from different fields of expertise, including soil and rock mechanics, chemical engineering, physics, bulk material handling, and mineral processing. The rapid growth of YADE can be attributed to (1) the careful and robust design of the framework core, (2) a continuous integration pipeline with fully embedded thorough tests which are executed upon each merge request, ensuring stable compilation for various operating systems, and (3) user-friendliness, facilitated by the Python interface, detailed documentation, and rigorous user support. In this paper, we review the main features of YADE, highlighting its versatility in terms of applications, its flexibility in terms of code development, as well as recent improvements in terms of computational efficiency.
Program summary
Program Title: YADE - Yet Another Dynamic Engine
CPC Library link to program files:https://doi.org/10.17632/n4f5fw97rd.1
Licensing provisions: GNU General Public License 2
Programming language: C++, Python
Nature of problem: Numerical simulation of many-particle systems requires accurate models for particle-to-particle interactions, efficient contact detection between objects of various shapes, and robust time integration. In addition, the flow of fluids, thermal effects, as well as other coupled problems in the presence of particles are found in many fundamental and practical applications and they need dedicated computational tools. YADE provides a computational framework to perform such simulations using the discrete element method and multiple extensions of it.
Solution method:YADE simulates particulate systems using the Discrete Element Method (DEM) in a flexible platform combining C++ and Python
{"title":"YADE - An extensible framework for the interactive simulation of multiscale, multiphase, and multiphysics particulate systems","authors":"Vasileios Angelidakis , Katia Boschi , Karol Brzeziński , Robert A. Caulk , Bruno Chareyre , Carlos Andrés del Valle , Jérôme Duriez , Anton Gladky , Dingeman L.H. van der Haven , Janek Kozicki , Gerald Pekmezi , Luc Scholtès , Klaus Thoeni","doi":"10.1016/j.cpc.2024.109293","DOIUrl":"https://doi.org/10.1016/j.cpc.2024.109293","url":null,"abstract":"<div><p>This contribution presents the key elements of <span>YADE</span>, an extensible open-source framework for dynamic simulations. During the past 19 years, <span>YADE</span> has evolved from “Yet Another Dynamic Engine” to a versatile multiscale and multiphysics solver, counting a large, active, and growing community of users and developers. The computationally intense parts of the source code are written in C++, using flexible object models that allow for easy implementation of new features. The source code is wrapped in Python, equipping the software with an interactive kernel used for rapid and concise scene construction, simulation control, post-processing, and debugging. The project, including documentation and examples, is hosted on <span>https://yade-dem.org</span><svg><path></path></svg>, while the source code is freely available on GitLab. Over the last decade, <span>YADE</span> has expanded in terms of capabilities thanks to the contribution of many developers from different fields of expertise, including soil and rock mechanics, chemical engineering, physics, bulk material handling, and mineral processing. The rapid growth of <span>YADE</span> can be attributed to (1) the careful and robust design of the framework core, (2) a continuous integration pipeline with fully embedded thorough tests which are executed upon each merge request, ensuring stable compilation for various operating systems, and (3) user-friendliness, facilitated by the Python interface, detailed documentation, and rigorous user support. In this paper, we review the main features of <span>YADE</span>, highlighting its versatility in terms of applications, its flexibility in terms of code development, as well as recent improvements in terms of computational efficiency.</p></div><div><h3>Program summary</h3><p><em>Program Title:</em> YADE - Yet Another Dynamic Engine</p><p><em>CPC Library link to program files:</em> <span>https://doi.org/10.17632/n4f5fw97rd.1</span><svg><path></path></svg></p><p><em>Developer's repository link:</em> <span>https://gitlab.com/yade-dev/trunk</span><svg><path></path></svg></p><p><em>Licensing provisions:</em> GNU General Public License 2</p><p><em>Programming language:</em> C++, Python</p><p><em>Nature of problem:</em> Numerical simulation of many-particle systems requires accurate models for particle-to-particle interactions, efficient contact detection between objects of various shapes, and robust time integration. In addition, the flow of fluids, thermal effects, as well as other coupled problems in the presence of particles are found in many fundamental and practical applications and they need dedicated computational tools. <span>YADE</span> provides a computational framework to perform such simulations using the discrete element method and multiple extensions of it.</p><p><em>Solution method:</em> <span>YADE</span> simulates particulate systems using the Discrete Element Method (DEM) in a flexible platform combining C++ and Python","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":null,"pages":null},"PeriodicalIF":7.2,"publicationDate":"2024-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0010465524002169/pdfft?md5=adceaced53a861b5179b33ae68901234&pid=1-s2.0-S0010465524002169-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141539375","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-27DOI: 10.1016/j.cpc.2024.109291
We propose a Fast Fourier Transform based Periodic Interpolation Method (FFT-PIM), a flexible and computationally efficient approach for computing the scalar potential given by a superposition sum in a unit cell of an infinitely periodic array. Under the same umbrella, FFT-PIM allows computing the potential for 1D, 2D, and 3D periodicities for dynamic problems involving the Helmholtz potential and static problems involving Coulomb potential, including problems with and without a periodic phase shift. The computational complexity of the FFT-PIM is of for N spatially coinciding sources and observer points. The FFT-PIM uses rapidly converging series representations of the Green's function serving as a kernel in the superposition sum. Based on these representations, the FFT-PIM splits the potential into its near-zone component, which includes a small number of images surrounding the unit cell of interest, and far-zone component, which includes the rest of an infinite number of images. The far-zone component is evaluated by projecting the non-uniform sources onto a sparse uniform grid, performing superposition sums on this sparse grid, and interpolating the potential from the uniform grid to the non-uniform observation points. The near-zone component is evaluated using an FFT-based method, which is adapted to efficiently handle non-uniform source-observer distributions within the periodic unit cell. The FFT-PIM can be used for a broad range of applications, such as periodic problems involving integral equations for wave propagation in electromagnetics and acoustics, micromagnetic solvers, and density functional theory solvers.
{"title":"Fast Fourier Transform periodic interpolation method for superposition sums in a periodic unit cell","authors":"","doi":"10.1016/j.cpc.2024.109291","DOIUrl":"10.1016/j.cpc.2024.109291","url":null,"abstract":"<div><p>We propose a Fast Fourier Transform based Periodic Interpolation Method (FFT-PIM), a flexible and computationally efficient approach for computing the scalar potential given by a superposition sum in a unit cell of an infinitely periodic array. Under the same umbrella, FFT-PIM allows computing the potential for 1D, 2D, and 3D periodicities for dynamic problems involving the Helmholtz potential and static problems involving Coulomb potential, including problems with and without a periodic phase shift. The computational complexity of the FFT-PIM is of <span><math><mi>O</mi><mo>(</mo><mi>N</mi><mi>log</mi><mo></mo><mi>N</mi><mo>)</mo></math></span> for <em>N</em> spatially coinciding sources and observer points. The FFT-PIM uses rapidly converging series representations of the Green's function serving as a kernel in the superposition sum. Based on these representations, the FFT-PIM splits the potential into its near-zone component, which includes a small number of images surrounding the unit cell of interest, and far-zone component, which includes the rest of an infinite number of images. The far-zone component is evaluated by projecting the non-uniform sources onto a sparse uniform grid, performing superposition sums on this sparse grid, and interpolating the potential from the uniform grid to the non-uniform observation points. The near-zone component is evaluated using an FFT-based method, which is adapted to efficiently handle non-uniform source-observer distributions within the periodic unit cell. The FFT-PIM can be used for a broad range of applications, such as periodic problems involving integral equations for wave propagation in electromagnetics and acoustics, micromagnetic solvers, and density functional theory solvers.</p></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":null,"pages":null},"PeriodicalIF":7.2,"publicationDate":"2024-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0010465524002145/pdfft?md5=23d356ca2f300c3da1f4f8e8b1608506&pid=1-s2.0-S0010465524002145-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141729599","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-26DOI: 10.1016/j.cpc.2024.109289
Michael Penwarden
{"title":"Comment on “Trans-Net: A transferable pretrained neural networks based on temporal domain decomposition for solving partial differential equations” by D. Zhang, Y. Li, and S. Ying","authors":"Michael Penwarden","doi":"10.1016/j.cpc.2024.109289","DOIUrl":"https://doi.org/10.1016/j.cpc.2024.109289","url":null,"abstract":"","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":null,"pages":null},"PeriodicalIF":7.2,"publicationDate":"2024-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141480501","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-26DOI: 10.1016/j.cpc.2024.109292
Ronaldo Rodrigues Pela , Claudia Draxl
Currently, many ab initio codes are being prepared for exascale computing. A first and important step is to significantly improve the efficiency of existing implementations by devising algorithms that perform better also on a single-core level. This manuscript addresses this challenge for real-time time-dependent density functional theory in the full-potential all-electron code exciting, with a focus on systems with reduced dimensionality. Following the strategy described here, calculations can run orders of magnitude faster than before. We demonstrate this with the molecules H2 and CO, achieving speedups between 98 to over 50,000. We also present an example where conventional calculations would be particularly costly, namely the inorganic/organic heterostructure of pyridine physisorbed on monolayer MoS2.
{"title":"Speeding up all-electron real-time TDDFT demonstrated by the exciting package","authors":"Ronaldo Rodrigues Pela , Claudia Draxl","doi":"10.1016/j.cpc.2024.109292","DOIUrl":"https://doi.org/10.1016/j.cpc.2024.109292","url":null,"abstract":"<div><p>Currently, many <em>ab initio</em> codes are being prepared for exascale computing. A first and important step is to significantly improve the efficiency of existing implementations by devising algorithms that perform better also on a single-core level. This manuscript addresses this challenge for real-time time-dependent density functional theory in the full-potential all-electron code <span>exciting</span>, with a focus on systems with reduced dimensionality. Following the strategy described here, calculations can run orders of magnitude faster than before. We demonstrate this with the molecules H<sub>2</sub> and CO, achieving speedups between 98 to over 50,000. We also present an example where conventional calculations would be particularly costly, namely the inorganic/organic heterostructure of pyridine physisorbed on monolayer MoS<sub>2</sub>.</p></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":null,"pages":null},"PeriodicalIF":7.2,"publicationDate":"2024-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141539393","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-26DOI: 10.1016/j.cpc.2024.109290
Mohammad Imaran , James Young , Rosario Capozza , Kevin Stratford , Kevin J. Hanley
Particle shape plays a major role in the behaviour of most granular systems. This has led to increasing interest in the representation of arbitrarily shaped particles in discrete element method (DEM) simulations. In this paper, we present a simulation approach based on the representation of particle shapes using spherical harmonics where their radii can be calculated in spherical coordinates. An energy-conserving contact model is adopted which is based on the volume of overlap between interacting particles. Contact detection makes use of the bounding spheres of the interacting particles, simplifying its incorporation within a conventional sphere-based DEM code. The volume of overlap and other required quantities are calculated using Gaussian quadrature integration of the spherical cap formed by the bounding spheres. Both the accuracy and the computational cost increase with the number of quadrature points. The algorithm has been implemented as a LAMMPS user package, and verified by means of energy conservation. The performance and parallel scaling of the approach are illustrated, and an observed scaling limitation owing to load imbalance arising from the evaluation of the overlap volume is discussed.
Program summary
Program Title: SH-DEM LAMMPS package
CPC Library link to program files:https://doi.org/10.17632/vk6fj6yjtf.1
Nature of problem: Particles are often highly non-spherical. Spherical harmonics provide a natural way to represent complex particle shapes within a discrete element method (DEM) simulation. However, there is no publicly available DEM code which allows particle shapes to be represented using spherical harmonics.
Solution method: The SH-DEM package extends the capabilities of LAMMPS so that irregularly shaped particles can be represented using spherical harmonics. The package includes the definition of a new ‘shdem’ atom style for spherical harmonic particles, a time integration scheme for these particles based on the Velocity Verlet algorithm, algorithms for detecting and evaluating contacts between spherical harmonic particles, evaluation of the contact forces between these particles and rigid walls, and two energy computes for groups of spherical harmonic particles.
Additional comments including restrictions and unusual features: The SH-DEM package is applicable only to 3D simulations. In order for a particle to be defined by spherical harmonics, it is required that any line segment drawn from an origin inside the particle crosses the contour of the particle's three-dimensional surface only once. If the ‘shdem’ atom style is used, the current implementation
{"title":"Spherical harmonic–based DEM in LAMMPS: Implementation, verification and performance assessment","authors":"Mohammad Imaran , James Young , Rosario Capozza , Kevin Stratford , Kevin J. Hanley","doi":"10.1016/j.cpc.2024.109290","DOIUrl":"https://doi.org/10.1016/j.cpc.2024.109290","url":null,"abstract":"<div><p>Particle shape plays a major role in the behaviour of most granular systems. This has led to increasing interest in the representation of arbitrarily shaped particles in discrete element method (DEM) simulations. In this paper, we present a simulation approach based on the representation of particle shapes using spherical harmonics where their radii can be calculated in spherical coordinates. An energy-conserving contact model is adopted which is based on the volume of overlap between interacting particles. Contact detection makes use of the bounding spheres of the interacting particles, simplifying its incorporation within a conventional sphere-based DEM code. The volume of overlap and other required quantities are calculated using Gaussian quadrature integration of the spherical cap formed by the bounding spheres. Both the accuracy and the computational cost increase with the number of quadrature points. The algorithm has been implemented as a LAMMPS user package, and verified by means of energy conservation. The performance and parallel scaling of the approach are illustrated, and an observed scaling limitation owing to load imbalance arising from the evaluation of the overlap volume is discussed.</p></div><div><h3>Program summary</h3><p><em>Program Title:</em> SH-DEM LAMMPS package</p><p><em>CPC Library link to program files:</em> <span>https://doi.org/10.17632/vk6fj6yjtf.1</span><svg><path></path></svg></p><p><em>Developer's repository link:</em> <span>https://github.com/EPCCed/lammps/tree/feature-sh-dem</span><svg><path></path></svg></p><p><em>Licensing provisions:</em> GPLv2</p><p><em>Programming language:</em> C++</p><p><em>Nature of problem:</em> Particles are often highly non-spherical. Spherical harmonics provide a natural way to represent complex particle shapes within a discrete element method (DEM) simulation. However, there is no publicly available DEM code which allows particle shapes to be represented using spherical harmonics.</p><p><em>Solution method:</em> The <em>SH-DEM</em> package extends the capabilities of LAMMPS so that irregularly shaped particles can be represented using spherical harmonics. The package includes the definition of a new ‘shdem’ atom style for spherical harmonic particles, a time integration scheme for these particles based on the Velocity Verlet algorithm, algorithms for detecting and evaluating contacts between spherical harmonic particles, evaluation of the contact forces between these particles and rigid walls, and two energy computes for groups of spherical harmonic particles.</p><p><em>Additional comments including restrictions and unusual features:</em> The <em>SH-DEM</em> package is applicable only to 3D simulations. In order for a particle to be defined by spherical harmonics, it is required that any line segment drawn from an origin inside the particle crosses the contour of the particle's three-dimensional surface only once. If the ‘shdem’ atom style is used, the current implementation","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":null,"pages":null},"PeriodicalIF":7.2,"publicationDate":"2024-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0010465524002133/pdfft?md5=6a37d7ef4a05ac7454f2edf50210087d&pid=1-s2.0-S0010465524002133-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141539385","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-25DOI: 10.1016/j.cpc.2024.109286
Simone Zanotti , Momchil Minkov , Davide Nigro , Dario Gerace , Shanhui Fan , Lucio Claudio Andreani
We describe legume, a free electromagnetic solver that implements the guided-mode expansion method for patterned multilayer waveguides, or photonic crystal slabs. legume has a built-in tool for automatic differentiation, which makes it suitable for the inverse design of photonic crystal structures with desired physical properties. Compared to a previous version of the method (M. Minkov et al., 2020 [12]), here we introduce several new features of the code, we discuss additional technical aspects of the method and its numerical implementation. The novel features that are treated in this paper include: (i) the separation of modes according to their mirror symmetry with respect to a vertical symmetry plane of the photonic structure, (ii) the problem of polarization mixing in coupling to far-field radiation modes, and (iii) the description of active two-dimensional layers through a suitably formulated radiation-matter coupling Hamiltonian, allowing to describe the physics of both weakly and strongly coupled exciton-photon modes, the latter leading to photonic crystal polariton eigenmodes. Detailed and direct comparisons with rigorous coupled-wave analysis simulations are used to test the accuracy of the method and the numerical efficiency of the code. These newly added features of the legume code significantly increase the prospective applications of guided-mode expansion, making it a very practical and versatile tool enabling the design of advanced photonic structures and the description of radiation-matter interaction.
Program summary
Program Title:legume
CPC Library link to program files:https://doi.org/10.17632/kf3cwknx4d.1
Nature of problem: Dispersion and radiative losses of photonic eigenmodes in patterned multilayer waveguides/photonic crystal slabs/periodic metasurfaces. Interaction of photonic modes with exciton resonances leading to exciton-polaritons. Inverse design by optimization of the parameters.
Solution method: Finite-basis expansion using a basis of guided modes of an effective homogeneous waveguide, perturbation theory to describe coupling with far-field radiation. Quantum theory of excitons, photons and their interaction to describe the occurrence of exciton-polaritons. Automatic differentiation via Autograd to implement inverse design. In this upgraded version of the legume code we implement symmetrization with respect to a vertical mirror plane and light-matter interaction for exciton-polaritons. Inverse design has been described previously, here we focus on the new features and applications of the code.
{"title":"Legume: A free implementation of the guided-mode expansion method for photonic crystal slabs","authors":"Simone Zanotti , Momchil Minkov , Davide Nigro , Dario Gerace , Shanhui Fan , Lucio Claudio Andreani","doi":"10.1016/j.cpc.2024.109286","DOIUrl":"https://doi.org/10.1016/j.cpc.2024.109286","url":null,"abstract":"<div><p>We describe <span>legume</span>, a free electromagnetic solver that implements the guided-mode expansion method for patterned multilayer waveguides, or photonic crystal slabs. <span>legume</span> has a built-in tool for automatic differentiation, which makes it suitable for the inverse design of photonic crystal structures with desired physical properties. Compared to a previous version of the method (M. Minkov et al., 2020 <span>[12]</span>), here we introduce several new features of the code, we discuss additional technical aspects of the method and its numerical implementation. The novel features that are treated in this paper include: (i) the separation of modes according to their mirror symmetry with respect to a vertical symmetry plane of the photonic structure, (ii) the problem of polarization mixing in coupling to far-field radiation modes, and (iii) the description of active two-dimensional layers through a suitably formulated radiation-matter coupling Hamiltonian, allowing to describe the physics of both weakly and strongly coupled exciton-photon modes, the latter leading to photonic crystal polariton eigenmodes. Detailed and direct comparisons with rigorous coupled-wave analysis simulations are used to test the accuracy of the method and the numerical efficiency of the code. These newly added features of the <span>legume</span> code significantly increase the prospective applications of guided-mode expansion, making it a very practical and versatile tool enabling the design of advanced photonic structures and the description of radiation-matter interaction.</p></div><div><h3>Program summary</h3><p><em>Program Title:</em> <span>legume</span></p><p><em>CPC Library link to program files:</em> <span>https://doi.org/10.17632/kf3cwknx4d.1</span><svg><path></path></svg></p><p><em>Developer's repository link:</em> <span>https://github.com/fancompute/legume</span><svg><path></path></svg></p><p><em>Licensing provisions:</em> MIT</p><p><em>Programming language:</em> Python</p><p><em>Nature of problem:</em> Dispersion and radiative losses of photonic eigenmodes in patterned multilayer waveguides/photonic crystal slabs/periodic metasurfaces. Interaction of photonic modes with exciton resonances leading to exciton-polaritons. Inverse design by optimization of the parameters.</p><p><em>Solution method:</em> Finite-basis expansion using a basis of guided modes of an effective homogeneous waveguide, perturbation theory to describe coupling with far-field radiation. Quantum theory of excitons, photons and their interaction to describe the occurrence of exciton-polaritons. Automatic differentiation via Autograd to implement inverse design. In this upgraded version of the <span>legume</span> code we implement symmetrization with respect to a vertical mirror plane and light-matter interaction for exciton-polaritons. Inverse design has been described previously, here we focus on the new features and applications of the code.</p></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":null,"pages":null},"PeriodicalIF":7.2,"publicationDate":"2024-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0010465524002091/pdfft?md5=c9a5f8f0d85ec817bff548b0b92ec8f6&pid=1-s2.0-S0010465524002091-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141539381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-25DOI: 10.1016/j.cpc.2024.109288
Bowen Han , Andrei T. Savici , Mingda Li , Yongqiang Cheng
Inelastic neutron scattering (INS) has unique advantages in probing how atoms vibrate and how the vibrations propagate and interact. Such dynamic information is crucial in understanding various material properties, from heat capacity, thermal conductivity, phase transitions, and chemical reactions to more exotic quantum behavior. The analysis and interpretation of the INS spectra often start from a model structure of the sample, followed by a series of calculations to obtain the simulated spectra to compare with experiments. The conventional way to perform such calculations usually requires significant time, computing resources, and specialized expertise. Here, we present a new program named INSPIRED (Inelastic Neutron Scattering Prediction for Instantaneous Results and Experimental Design), which enables users to perform rapid INS simulations in several different ways on their personal computers in just a few clicks, with the crystal structure as the only input file. Specifically, the users can choose a pre-trained symmetry-aware neural network (coupled with an autoencoder) to predict the phonon density of states (DOS), 1D S(E) and 2D S(,E) spectra for any given structure. One can also choose an existing density functional theory (DFT) calculation from a database (containing over 12,000 crystals), and quickly obtain the simulated INS spectra for single crystals and powders. It is also possible to use pre-trained universal machine learning force fields to relax a given crystal structure, calculate the phonon dispersion and DOS, and, subsequently, the INS spectra. All these functions are implemented with a PyQt graphic user interface. We expect these new tools will benefit broad user communities and significantly improve the efficiency of experiment design, execution, and data analysis for INS.
Program summary
Program Title: INSPIRED
CPC Library link to program files:https://doi.org/10.17632/8g3s8f9n2p.1
Nature of problem: How to easily and quickly assess the expected INS spectra for a given crystal structure has been a major challenge in the INS user community. It is a main bottleneck affecting almost every stage of the workflow, from experimental design and steering to data analysis and interpretation. The widely used approach involving DFT calculations is time-consuming, requires advanced computing resources, and has a steep learning curve. With the growing power of neutron sources and more hig
非弹性中子散射（INS）在探测原子如何振动以及振动如何传播和相互作用方面具有独特的优势。这些动态信息对于了解各种材料特性至关重要，从热容量、热导率、相变、化学反应到更奇特的量子行为。对 INS 图谱的分析和解释通常从样品的模型结构开始，然后通过一系列计算获得模拟图谱，并与实验结果进行比较。进行此类计算的传统方法通常需要大量时间、计算资源和专业知识。在此，我们介绍一种名为 INSPIRED（非弹道中子散射瞬时结果和实验设计预测）的新程序，用户只需点击几下，就能在个人电脑上以几种不同的方式快速进行 INS 模拟，而晶体结构则是唯一的输入文件。具体来说，用户可以选择预先训练好的对称性感知神经网络（与自动编码器相结合）来预测任何给定结构的声子态密度（DOS）、一维 S(E) 和二维 S(|Q|,E) 光谱。还可以从数据库（包含 12,000 多种晶体）中选择现有的密度泛函理论（DFT）计算，快速获得单晶体和粉末的模拟 INS 光谱。还可以使用预先训练好的通用机器学习力场来松弛给定的晶体结构，计算声子色散和 DOS，进而计算 INS 光谱。所有这些功能都是通过 PyQt 图形用户界面实现的。我们希望这些新工具能惠及广大用户群体，并显著提高 INS 实验设计、执行和数据分析的效率：INSPIREDCPC 库与程序文件的链接：https://doi.org/10.17632/8g3s8f9n2p.1Developer's repository 链接：https://github.com/cyqjh/inspired（软件）、https://doi.org/10.5281/zenodo.11478889（数据库、模型文件和虚拟机设备文件）许可条款：MIT 编程语言：Python问题性质：如何方便快捷地评估给定晶体结构的预期 INS 光谱一直是 INS 用户社区面临的主要挑战。从实验设计和指导到数据分析和解释，它几乎是影响工作流程每个阶段的主要瓶颈。广泛使用的 DFT 计算方法耗时长，需要先进的计算资源，而且学习曲线陡峭。随着中子源和更多高通量 INS 实验的日益强大，迫切需要解决这一问题，最好是利用机器学习和人工智能的最新发展：我们采用数据驱动的方法来解决这个问题。我们训练了一个对称感知神经网络，从晶体结构直接预测一维光谱或潜在空间向量，然后解码重建二维光谱。用于训练的数据库包含一万多个晶体，也可用于计算单晶体和粉末的 INS 光谱。最近出现的通用机器学习力场为大幅加速模拟提供了另一个途径。所有这些解决方案都是通过图形用户界面实现的，因此没有建模/编程背景或无法使用强大计算机的用户也能轻松运行工作流程。
{"title":"INSPIRED: Inelastic neutron scattering prediction for instantaneous results and experimental design","authors":"Bowen Han , Andrei T. Savici , Mingda Li , Yongqiang Cheng","doi":"10.1016/j.cpc.2024.109288","DOIUrl":"https://doi.org/10.1016/j.cpc.2024.109288","url":null,"abstract":"<div><p>Inelastic neutron scattering (INS) has unique advantages in probing how atoms vibrate and how the vibrations propagate and interact. Such dynamic information is crucial in understanding various material properties, from heat capacity, thermal conductivity, phase transitions, and chemical reactions to more exotic quantum behavior. The analysis and interpretation of the INS spectra often start from a model structure of the sample, followed by a series of calculations to obtain the simulated spectra to compare with experiments. The conventional way to perform such calculations usually requires significant time, computing resources, and specialized expertise. Here, we present a new program named INSPIRED (Inelastic Neutron Scattering Prediction for Instantaneous Results and Experimental Design), which enables users to perform rapid INS simulations in several different ways on their personal computers in just a few clicks, with the crystal structure as the only input file. Specifically, the users can choose a pre-trained symmetry-aware neural network (coupled with an autoencoder) to predict the phonon density of states (DOS), 1D S(E) and 2D S(<span><math><mo>|</mo><mtext>Q</mtext><mo>|</mo></math></span>,E) spectra for any given structure. One can also choose an existing density functional theory (DFT) calculation from a database (containing over 12,000 crystals), and quickly obtain the simulated INS spectra for single crystals and powders. It is also possible to use pre-trained universal machine learning force fields to relax a given crystal structure, calculate the phonon dispersion and DOS, and, subsequently, the INS spectra. All these functions are implemented with a PyQt graphic user interface. We expect these new tools will benefit broad user communities and significantly improve the efficiency of experiment design, execution, and data analysis for INS.</p></div><div><h3>Program summary</h3><p><em>Program Title:</em> INSPIRED</p><p><em>CPC Library link to program files:</em> <span><span>https://doi.org/10.17632/8g3s8f9n2p.1</span></span><svg><path></path></svg></p><p><em>Developer's repository link:</em> <span><span>https://github.com/cyqjh/inspired</span></span><svg><path></path></svg> (software), <span><span>https://doi.org/10.5281/zenodo.11478889</span></span><svg><path></path></svg> (database, models files, and virtual machine appliance file)</p><p><em>Licensing provisions:</em> MIT</p><p><em>Programming language:</em> Python</p><p><em>Nature of problem:</em> How to easily and quickly assess the expected INS spectra for a given crystal structure has been a major challenge in the INS user community. It is a main bottleneck affecting almost every stage of the workflow, from experimental design and steering to data analysis and interpretation. The widely used approach involving DFT calculations is time-consuming, requires advanced computing resources, and has a steep learning curve. With the growing power of neutron sources and more hig","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":null,"pages":null},"PeriodicalIF":7.2,"publicationDate":"2024-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141539384","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-22DOI: 10.1016/j.cpc.2024.109287
Jacob R. Gissinger , Benjamin D. Jensen , Kristopher E. Wise
From batteries to biology, many important technologies and physical phenomena operate as out-of-equilibrium reactive systems. Accurately modeling the nanoscale dynamics of non-equilibrium reactive systems and how they respond to external stimuli is challenging, especially if both atomistic resolution and large scales (>105 atoms) are required. REACTER is a protocol for modeling chemical reactions during classical molecular dynamics (MD) simulations. Coupling traditional fixed-valence force fields with heuristic reactive MD is advantageous for large-scale simulations of dynamic systems that can include the complex reaction mechanisms common in organic chemistry. This paper details the current features of the LAMMPS implementation of REACTER, known as fix bond/react, and surveys recent applications of the protocol in a variety of fields, including photopolymers, high-performance composites, and membranes. Conceived as a tool for modeling polymerization processes, the scope of REACTER is expanding as it is applied to new materials and supporting features are implemented. Three new case studies are presented that highlight the capabilities of REACTER, including modeling hierarchical materials, the mechanics of molecular machines, and large-scale dynamics of heterogeneous catalysis.
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Pub Date : 2024-06-21DOI: 10.1016/j.cpc.2024.109285
Francesco De Vanna , Giacomo Baldan
We present URANOS-2.0, the second major release of our massively parallel, GPU-accelerated solver for compressible wall flow applications. This latest version represents a significant leap forward in our initial tool, which was launched in 2023 (De Vanna et al. [1]), and has been specifically optimized to take full advantage of the opportunities offered by the cutting-edge pre-exascale architectures available within the EuroHPC JU. In particular, URANOS-2.0 emphasizes portability and compatibility improvements with the two top-ranked supercomputing architectures in Europe: LUMI and Leonardo. These systems utilize different GPU architectures, AMD and NVIDIA, respectively, which necessitates extensive efforts to ensure seamless usability across their distinct structures. In pursuit of this objective, the current release adheres to the OpenACC standard. This choice not only facilitates efficient utilization of the full potential inherent in these extensive GPU-based architectures but also upholds the principles of vendor neutrality, a distinctive characteristic of URANOS solvers in the CFD solvers' panorama. However, the URANOS-2.0 version goes beyond the goals of improving usability and portability; it introduces performance enhancements and restructures the most demanding computational kernels. This translates into a 2× speedup over the same architecture. In addition to its enhanced single-GPU performance, the present solver release demonstrates very good scalability in multi-GPU environments. URANOS-2.0, in fact, achieves strong scaling efficiencies of over 80% across 64 compute nodes (256 GPUs) for both LUMI and Leonardo. Furthermore, its weak scaling efficiencies reach approximately 95% and 90% on LUMI and Leonardo, respectively, when up to 256 nodes (1024 GPUs) are considered. These significant performance advancements position URANOS-2.0 as a state-of-the-art supercomputing platform tailored for compressible wall turbulence applications, establishing the solver as an integrated tool for various aerospace and energy engineering applications, which can span from direct numerical simulations, wall-resolved large eddy simulations, up to most recent wall-modeled large eddy simulations.
Program summary
Program title: Unsteady Robust All-around Navier-StOkes Solver (URANOS)
CPC Library link to program files:https://doi.org/10.17632/pw5hshn9k6.2
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