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Computer Physics Communications

ISSN: 0010-4655

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Datasets associated with articles published in Computer Physics Communications

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1970 2024
5920 results
  • Massively parallel implementation of iterative eigensolvers in large-scale plane-wave density functional theory
    The Kohn-sham density functional theory (DFT) is a powerful method to describe the electronic structures of molecules and solids in condensed matter physics, computational chemistry and materials science. However, large and accurate DFT calculations within plane waves process a cubic-scaling computational complexity, which is usually limited by expensive computation and communication costs. The rapid development of high performance computing (HPC) on leadership supercomputers brings new opportunities for developing plane-wave DFT calculations for large-scale systems. Here, we implement parallel iterative eigensolvers in large-scale plane-wave DFT calculations, including Davidson, locally optimal block preconditioned conjugate gradient (LOBPCG), projected preconditioned conjugate gradient (PPCG) and the Chebyshev subspace iteration (CheFSI) algorithms, and analyze the performance of these algorithms in massively parallel plane-wave computing tasks. We adopt a two-level parallelization strategy that combines the message passing interface (MPI) with open multi-processing (OpenMP) parallel programming to handle data exchange and matrix operations in the construction and diagonalization of large-scale Hamiltonian matrix within plane waves. Numerical results illustrate that these iterative eigensolvers can scale up to 42,592 processing cores with high peak performance of 30% on leadship supercomputers to study the electronic structures of bulk silicon systems containing 10,648 atoms.
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  • micrOMEGAs 6.0: N-component dark matter
    micrOMEGAs is a numerical code to compute dark matter (DM) observables in generic extensions of the Standard Model (SM) of particle physics. We present a new version of micrOMEGAs that includes a generalization of the Boltzmann equations governing the DM cosmic abundance evolution which can be solved to compute the relic density of N-component DM. The direct and indirect detection rates in such scenarios take into account the relative contribution of each component such that constraints on the combined signal of all DM components can be imposed. The co-scattering mechanism for DM production is also included, whereas the routines used to compute the relic density of feebly interacting particles have been improved in order to take into account the effect of thermal masses of t-channel particles. Finally, the tables for the DM self-annihilation - induced photon spectra have been extended down to DM masses of 110 MeV, and they now include annihilation channels into light mesons.
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  • A SPIRED code for the reconstruction of spin distribution
    In Nuclear Magnetic Resonance (NMR), it is of crucial importance to have an accurate knowledge of the spin probability distribution corresponding to inhomogeneities of the magnetic fields. An accurate identification of the sample distribution requires a set of experimental data that is sufficiently rich to extract all fundamental information. These data depend strongly on the control fields (and their number) used experimentally to perturb the spin system. In this work, we present and analyze a greedy reconstruction algorithm, and provide the corresponding SPIRED code, for the computation of a set of control functions allowing the generation of data that are appropriate for the accurate reconstruction of a sample probability distribution. In particular, the focus is on NMR and spin dynamics governed by the Bloch system with inhomogeneities in both the static and radio-frequency magnetic fields applied to the sample. We show numerically that the algorithm is able to reconstruct non trivial joint probability distributions of the two inhomogeneous Hamiltonian parameters. A rigorous convergence analysis of the algorithm is also provided.
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  • PolyHoop: Soft particle and tissue dynamics with topological transitions
    We present PolyHoop, a lightweight standalone C++ implementation of a mechanical model to simulate the dynamics of soft particles and cellular tissues in two dimensions. With only few geometrical and physical parameters, PolyHoop is capable of simulating a wide range of particulate soft matter systems: from biological cells and tissues to vesicles, bubbles, foams, emulsions, and other amorphous materials. The soft particles or cells are represented by continuously remodeling, non-convex, high-resolution polygons that can undergo growth, division, fusion, aggregation, and separation. With PolyHoop, a tissue or foam consisting of a million cells with high spatial resolution can be simulated on conventional laptop computers.
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  • Quadrature of functions with endpoint singular and generalised polynomial behaviour in computational physics
    Fast and accurate numerical integration always represented a bottleneck in high-performance computational physics, especially in large and multiscale industrial simulations involving Finite (FEM) and Boundary Element Methods (BEM). The computational demand escalates significantly in problems modelled by irregular or endpoint singular behaviours which can be approximated with generalised polynomials of real degree. This is due to both the practical limitations of finite-arithmetic computations and the inefficient samples distribution of traditional Gaussian quadrature rules. We developed a non-iterative mathematical software implementing an innovative numerical quadrature which largely enhances the precision of Gauss-Legendre formulae (G-L) for integrands modelled as generalised polynomial with the optimal amount of nodes and weights capable of guaranteeing the required numerical precision. This methodology avoids to resort to more computationally expensive techniques such as adaptive or composite quadrature rules. From a theoretical point of view, the numerical method underlying this work was preliminary presented in [1] by constructing the monomial transformation itself and providing all the necessary conditions to ensure the numerical stability and exactness of the quadrature up to machine precision. The novel contribution of this work concerns the optimal implementation of said method, the extension of its applicability at run-time with different type of inputs, the provision of additional insights on its functionalities and its straightforward implementation, in particular FEM applications or other mathematical software either as an external tool or embedded suite. The open-source, cross-platform C++ library Monomial Transformation Quadrature Rule (MTQR) has been designed to be highly portable, fast and easy to integrate in larger codebases. Numerical examples in multiple physical applications showcase the improved efficiency and accuracy when compared to traditional schemes.
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  • ERSN-OpenMC-Py: A python-based open-source software for OpenMC Monte Carlo code
    The graphical user interface is a key element in facilitating the use of complex simulation software. This project describes the development of a graphical user interface called “ERSN-OpenMC-Py” for an existing neutron simulation code, OpenMC. The main goal is to make simulation more accessible to a wider audience by providing a user-friendly and intuitive user interface. The process of developing the graphical user interface is described in detail, including the different stages of development such as user interface design, user interface implementation, and user interface integration with the OpenMC simulation code. The development tools used, such as Python3 and PyQt5, are also explained. The user interface allows the user to control the simulation parameters and interact with the simulation results. Key features of the user interface include visualization of simulation results, modification of simulation parameters, saving and loading simulation configurations, as well as managing output files. The end result is a functional user interface that allows users to easily visualize simulation results and control simulation parameters in an intuitive manner. This user interface also provides a better user experience for non-programming experts who wish to use the simulation code for their own projects.
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  • openFuelCell2: A new computational tool for fuel cells, electrolyzers, and other electrochemical devices and processes
    Fuel cells/electrolyzers are efficient and clean electrochemical devices that convert chemical energy directly into electricity and vice versa. They have attracted sustainable attention over the past decade from multiple experimental and numerical studies. However, detailed experimental investigations are typically expensive and challenging for providing a number of operating conditions and designs. Computational analysis offers an alternative approach for these studies. With the steadily increasing high-performance computing resources available, the limitations of numerical simulations have substantially decreased. This contribution details the design choice and code structure of modern electrochemical devices, which have been implemented as a versatile C++ library named openFuelCell2 within the open-source platform OpenFOAM, allowing for large-scale parallel calculations to be performed. The solver considers the major transport phenomena in a typical electrochemical device, including fluid flow, heat and mass transfer, species and charge transfer, and electrochemical reaction. This enables numerical simulations on popular electrochemical devices, such as fuel cells and electrolyzers, to be conducted. The paper also describes the domain decomposition, and parallel performance issues, as well as future applications.
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  • Multi-GPU UNRES for scalable coarse-grained simulations of very large protein systems
    Graphical Processor Units (GPUs) are nowadays widely used in all-atom molecular simulations because of the advantage of efficient partitioning of atom pairs between the kernels to compute the contributions to energy and forces, thus enabling the treatment of very large systems. Extension of time- and size-scale of computations is also sought through the development of coarse-grained (CG) models, in which atoms are merged into extended interaction sites. Implementation of CG codes on the GPUs, particularly the multiple-GPU platforms is, however, a challenge due to more complicated potentials and removing the explicit solvent, forcing developers to do interaction- rather than space-domain decomposition. In this paper, we propose a design of a multi-GPU coarse-grained simulator and report the implementation of the heavily coarse-grained physics-based UNited RESidue (UNRES) model of polypeptide chains. By moving all computations to GPUs and keeping the communication with CPUs to a minimum, we managed to achieve almost 5-fold speed-up with 8 A100 GPU accelerators for systems with over 200,000 amino-acid residues, this result making UNRES the best scalable coarse-grained software and enabling us to do laboratory-time millisecond-scale simulations of such cell components as tubulin within days of wall-clock time.
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  • UKRmol-scripts: A Perl-based system for the automated operation of the photoionization and electron/positron scattering suite UKRmol+
    UKRmol-scripts is a set of Perl scripts to automatically run the UKRmol+ codes, a complex software suite based on the R-matrix method to model fixed-nuclei photoionization and electron- and positron-scattering for polyatomic molecules. Starting with several basic parameters, the scripts operatively produce all necessary input files and run all codes for electronic structure and scattering calculations as well as gather the more frequently required outputs. The scripts provide a simple way to run such calculations for many molecular geometries concurrently and collect the resulting data for easier post-processing and visualization. We describe the structure of the scripts and the input parameters as well as provide examples for photoionization and electron and positron collisions with molecules. The codes are freely available from Zenodo.
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  • The QISG suite: High-performance codes for studying quantum Ising spin glasses
    We release a set of GPU programs for the study of the Quantum (S = 1/2) Spin Glass on a square lattice, with binary couplings. The library contains two main codes: MCQSG (that carries out Monte Carlo simulations using both the Metropolis and the Parallel Tempering algorithms, for the problem formulated in the Trotter-Suzuki approximation), and EDQSG (that obtains the extremal eigenvalues of the Transfer Matrix using the Lanczos algorithm). EDQSG has allowed us to diagonalize transfer matrices with size up to 2^36 x 2^36. From its side, MCQSG running on four NVIDIA A100 cards delivers a sub-picosecond time per spin-update, a performance that is competitive with dedicated hardware. We include as well in our library GPU programs for the analysis of the spin configurations generated by MCQSG. Finally, we provide two auxiliary codes: the first generates the lookup tables employed by the random number generator of MCQSG; the second one simplifies the execution of multiple runs using different input data.
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