f90wrap is a tool to automatically generate Python extension modules which interface to Fortran libraries that makes use of derived types. It builds on the capabilities of the popular f2py utility by ...generating a simpler Fortran 90 interface to the original Fortran code which is then suitable for wrapping with f2py, together with a higher-level Pythonic wrapper that makes the existance of an additional layer transparent to the final user. f90wrap has been used to wrap a number of large software packages of relevance to the condensed matter physics community, including the QUIP molecular dynamics code and the CASTEP density functional theory code.
In this work, we demonstrate the process for porting the cloud resolving model (CRM) used in the Energy Exascale Earth System Model Multi-Scale Modeling Framework (E3SM-MMF) from its original Fortran ...code base to C++ code using a portability library. This porting process is performed using the Yet Another Kernel Library (YAKL), a simplified C++ portability library that specializes in Fortran porting. In particular, we detail our step-by-step approach for porting the System for Atmospheric Modeling (SAM), the CRM used in E3SM-MMF, using a hybrid Fortran/C++ framework that allows for systematic reproduction and correctness testing of gradually ported YAKL C++ code. Additionally, analysis is done on the performance of the ported code using OLCF’s Summit supercomputer.
The iEBE-VISHNU code package performs event-by-event simulations for relativistic heavy-ion collisions using a hybrid approach based on (2+1)-dimensional viscous hydrodynamics coupled to a hadronic ...cascade model. We present the detailed model implementation, accompanied by some numerical code tests for the package. iEBE-VISHNU forms the core of a general theoretical framework for model-data comparisons through large scale Monte-Carlo simulations. A numerical interface between the hydrodynamically evolving medium and thermal photon radiation is also discussed. This interface is more generally designed for calculations of all kinds of rare probes that are coupled to the temperature and flow velocity evolution of the bulk medium, such as jet energy loss and heavy quark diffusion.
Program title: iEBE-VISHNU
Catalogue identifier: AEYA_v1_0
Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEYA_v1_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.: 5257939
No. of bytes in distributed program, including test data, etc.: 262822421
Distribution format: tar.gz
Programming language: Fortran, C++, python, bash, SQLite.
Computer: Laptop, desktop, cluster.
Operating system: Tested on GNU/Linux Ubuntu 12.04 x64, Red Hat Linux 6, Mac OS X 10.8+.
RAM: 2G bytes
Classification: 17.11, 17.16, 17.20.
External routines: GNU Scientific Library (GSL), HDF5 (Fortran and C++ enabled), Numpy
Nature of problem: Relativistic heavy-ion collisions are tiny in size (V≈10−42m3) and live in a flash (∼5×10−23s). It is impossible to use external probes to study the properties of the quark-gluon plasma (QGP), a novel state of matter created during the collisions. Experiments can only measure the momentum information of stable hadrons, who are the remnants of the collisions. In order to extract the thermal and transport properties of the QGP one needs to rely on Monte-Carlo event-by-event model simulations, which reverse-engineer the experimental measurements to the early time dynamics of the relativistic heavy-ion collisions.
Solution method: Relativistic heavy-ion collisions contain multiple stages of evolution. The physics that governs each stage is implemented into individual code components. A general driver script glues all the modular packages as a whole to perform large-scale Monte-Carlo simulations. The final results are stored into SQLite database, which supports standard querying for massive data analysis. By tuning transport coefficients of the QGP as free parameters, e.g. the specific shear viscosity η/s, we can constrain various transport properties of the QGP through model-data comparisons.
Additional comments: !!! The distribution file for this program is over 260 Mbytes and therefore is not delivered directly when download or Email is requested. Instead a html file giving details of how the program can be obtained is sent. !!!
Running time: The following running time is tested on a laptop computer with a 2.4 GHz Intel Core i5 CPU, 4 GB memory. All the C++ and Fortran codes are compiled with the GNU Compiler Collection (GCC) 4.9.2 and -O3 optimization (Table 1).
The R package lcmm provides a series of functions to estimate statistical models based on linear mixed model theory. It includes the estimation of mixed models and latent class mixed models for ...Gaussian longitudinal outcomes (hlme), curvilinear and ordinal univariate longitudinal outcomes (lcmm) and curvilinear multivariate outcomes (multlcmm), as well as joint latent class mixed models (Jointlcmm) for a (Gaussian or curvilinear) longitudinal outcome and a time-to-event outcome that can be possibly left-truncated right-censored and defined in a competing setting. Maximum likelihood esimators are obtained using a modified Marquardt algorithm with strict convergence criteria based on the parameters and likelihood stability, and on the negativity of the second derivatives. The package also provides various post-fit functions including goodness-of-fit analyses, classification, plots, predicted trajectories, individual dynamic prediction of the event and predictive accuracy assessment. This paper constitutes a companion paper to the package by introducing each family of models, the estimation technique, some implementation details and giving examples through a dataset on cognitive aging
We present a fast and user friendly exoplanet transit light-curve modelling package pytransit, implementing optimized versions of the Gimenez and Mandel & Agol transit models. The package offers an ...object-oriented python interface to access the two models implemented natively in fortran with OpenMP parallelization. A partial OpenCL version of the quadratic Mandel-Agol model is also included for GPU-accelerated computations. The aim of pytransit is to facilitate the analysis of photometric time series of exoplanet transits consisting of hundreds of thousands of data points, and of multipassband transit light curves from spectrophotometric observations, as a part of a researcher's programming toolkit for building complex, problem-specific analyses.
We present a new Fortran library to evaluate all harmonic polylogarithms up to weight four numerically for any complex argument. The algorithm is based on a reduction of harmonic polylogarithms up to ...weight four to a minimal set of basis functions that are computed numerically using series expansions allowing for fast and reliable numerical results.
Program title: Chaplin
Catalogue identifier: AETC_v1_0
Program summary URL: http://cpc.cs.qub.ac.uk/summaries/AETC_v1_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.: 101192
No. of bytes in distributed program, including test data, etc.: 729234
Distribution format: tar.gz
Programming language: Fortran 77.
Computer: Computing systems on which Fortran 77 compilers are available.
Operating system: Operating systems on which Fortran 77 compilers are available.
Classification: 11.1.
Nature of problem:
Numerical evaluation of harmonic polylogarithms.
Solution method:
Inside the unit circle: series expansion. Outside the unit circle: inversion relations.
Restrictions:
Only harmonic polylogarithms up to weight four are supported.
Unusual features:
Allows the evaluation of HPL’s numerically for any point in the complex plane.
Running time:
Depending on the weight vector and argument of the HPL, between 0.2 and 400 μs.
•A GPU-based discrete-finite element method is developed by using the CUDA FORTRAN.•The effectiveness and scalability of the method are validated.•The developed method is applied to tire-sand ...interaction simulations.•A speedup of more than 15 is achieved in tire-sand interaction simulation.•Simulation results of tire-sand interaction cases agree well with experimental results.
Recently, the discrete-finite element method (DEM-FEM) has proved to be an advanced technique for solid-particle interaction simulations. However, the low computational efficiency limits its applications to practical engineering problems. To achieve this end, this paper proposes a Graphics Processing Unit (GPU) based DEM-FEM, including contact detection, force calculation and information update, in the context of Compute Unified Device Architecture (CUDA) FORTRAN environment. Three numerical examples are performed to validate the efficiency, effectiveness and scalability of the developed method. On this basis, the GPU-based DEM-FEM is extended to a computing platform, and programmed into our in-house code PDFP-OVS for a typical solid-particle interaction problem, i.e. the running performance of a pneumatic tire on granular sand. Numerical result shows that a speedup of more than 15 can be achieved. The simulation results are found to be in good agreement with the experiment results in terms of the gross tractive effort, the drawbar pull and the running resistance, which validates the capacity of the platform in the travel performance analysis of the tire on granular sand.
HiggsSignals is a Fortran90 computer code that allows to test the compatibility of Higgs sector predictions against Higgs rates and masses measured at the LHC or the Tevatron. Arbitrary models with ...any number of Higgs bosons can be investigated using a model-independent input scheme based on HiggsBounds. The test is based on the calculation of a
χ
2
measure from the predictions and the measured Higgs rates and masses, with the ability of fully taking into account systematics and correlations for the signal rate predictions, luminosity and Higgs mass predictions. It features two complementary methods for the test. First, the peak-centered method, in which each observable is defined by a Higgs signal rate measured at a specific hypothetical Higgs mass, corresponding to a tentative Higgs signal. Second, the mass-centered method, where the test is evaluated by comparing the signal rate measurement to the theory prediction at the Higgs mass predicted by the model. The program allows for the simultaneous use of both methods, which is useful in testing models with multiple Higgs bosons. The code automatically combines the signal rates of multiple Higgs bosons if their signals cannot be resolved by the experimental analysis. We compare results obtained with HiggsSignals to official ATLAS and CMS results for various examples of Higgs property determinations and find very good agreement. A few examples of HiggsSignals applications are provided, going beyond the scenarios investigated by the LHC collaborations. For models with more than one Higgs boson we recommend to use HiggsSignals and HiggsBounds in parallel to exploit the full constraining power of Higgs search exclusion limits and the measurements of the signal seen at
m
H
≈
125.5
GeV.
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