tag:joss.theoj.org,2005:/papers/tagged/parallelizationJournal of Open Source Software2023-10-03T20:23:42ZJournal of Open Source Softwarehttps://joss.theoj.orgtag:joss.theoj.org,2005:Paper/46002023-10-03T20:23:42Z2023-10-04T10:38:48ZepiworldR: Fast Agent-Based Epi Modelsaccepted0.0-22023-07-13 15:39:41 UTC902023-10-03 20:23:42 UTC820235781DerekMeyerDivision of Epidemiology, University of Utah, Salt Lake City, UT, United States of America0009-0005-1350-6988GeorgeG VegaYonDivision of Epidemiology, University of Utah, Salt Lake City, UT, United States of America0000-0002-3171-084410.21105/joss.05781https://doi.org/10.5281/zenodo.8327345R, M4, C++https://joss.theoj.org/papers/10.21105/joss.05781.pdfABM, epiworldR, parallel computingtag:joss.theoj.org,2005:Paper/43862023-08-10T20:44:28Z2023-08-14T09:04:08ZGMP-Featurizer: A parallelized Python package for efficiently computing the Gaussian Multipole features of atomic systemsacceptedv1.0.02023-04-04 20:31:28 UTC882023-08-10 20:44:28 UTC820235476XiangyunLeiToyota Research Institute, Los Altos, CA, United States of America0000-0002-2333-9205JosephMontoyaToyota Research Institute, Los Altos, CA, United States of America0000-0001-5760-286010.21105/joss.05476https://doi.org/10.5281/zenodo.8170029Python, C++, Chttps://joss.theoj.org/papers/10.21105/joss.05476.pdfParallelization, Machine Learning, Chemistry, Molecular Dynamicstag:joss.theoj.org,2005:Paper/32712023-04-22T07:17:47Z2023-04-26T19:28:11ZHylleraasMD: Massively parallel hybrid particle-field molecular dynamics in Pythonacceptedv1.0.32022-01-07 23:14:41 UTC842023-04-22 07:17:47 UTC820234149MortenLedumDepartment of Chemistry, and Hylleraas Centre for Quantum Molecular Sciences, University of Oslo, PO Box 1033 Blindern, 0315 Oslo, Norway0000-0003-4244-4876ManuelCarrerDepartment of Chemistry, and Hylleraas Centre for Quantum Molecular Sciences, University of Oslo, PO Box 1033 Blindern, 0315 Oslo, Norway0000-0002-8777-4310SamiranSenDepartment of Chemistry, and Hylleraas Centre for Quantum Molecular Sciences, University of Oslo, PO Box 1033 Blindern, 0315 Oslo, Norway0000-0002-1922-7796XinmengLiDepartment of Chemistry, and Hylleraas Centre for Quantum Molecular Sciences, University of Oslo, PO Box 1033 Blindern, 0315 Oslo, Norway0000-0002-6863-6078MicheleCascellaDepartment of Chemistry, and Hylleraas Centre for Quantum Molecular Sciences, University of Oslo, PO Box 1033 Blindern, 0315 Oslo, Norway0000-0003-2266-5399SigbjørnLølandBoreDepartment of Chemistry and Biochemistry, University of California San Diego, La Jolla, California 92093, United States of America0000-0002-8620-488510.21105/joss.04149https://doi.org/10.5281/zenodo.7839898Python, Fortranhttps://joss.theoj.org/papers/10.21105/joss.04149.pdfchemistry, physics, molecular dynamics, coarse-grained, hybrid particle-fieldtag:joss.theoj.org,2005:Paper/35992023-02-03T19:16:38Z2023-02-04T00:00:45ZParMOO: A Python library for parallel multiobjective simulation optimizationacceptedv0.1.02022-05-13 00:36:38 UTC822023-02-03 19:16:38 UTC820234468TylerH.ChangMathematics and Computer Science Division, Argonne National Laboratory, USA0000-0001-9541-7041StefanM.WildApplied Mathematics and Computational Research Division, Lawrence Berkeley National Laboratory, USA, Mathematics and Computer Science Division, Argonne National Laboratory, USA, NAISE, Northwestern University, USA0000-0002-6099-277210.21105/joss.04468https://doi.org/10.5281/zenodo.7600559Pythonhttps://joss.theoj.org/papers/10.21105/joss.04468.pdfnumerical optimization, multiobjective optimization, response surface methodology, parallel simulationstag:joss.theoj.org,2005:Paper/33052022-10-16T18:11:19Z2022-10-17T00:01:29ZDeepSynth: Scaling Neural Program Synthesis with Distribution-based Searchacceptedv1.02022-01-25 09:55:56 UTC782022-10-16 18:11:19 UTC720224151ThéoMatriconCNRS, LaBRI and Université de Bordeaux, France0000-0002-5043-3221NathanaëlFijalkowCNRS, LaBRI and Université de Bordeaux, France, The Alan Turing Institute of data science, United Kingdom0000-0002-6576-4680GuillaumeLagardeCNRS, LaBRI and Université de Bordeaux, FranceKevinEllisCornell University, United States10.21105/joss.04151https://doi.org/10.5281/zenodo.7194579Python, Slashhttps://joss.theoj.org/papers/10.21105/joss.04151.pdfprogram synthesis, programming by example, neuro-symbolic methods, parallel search procedurestag:joss.theoj.org,2005:Paper/36742022-08-17T19:22:52Z2022-08-18T00:01:30ZGlobalSensitivity.jl: Performant and Parallel Global Sensitivity Analysis with Juliaacceptedv2.0.02022-06-24 10:15:50 UTC762022-08-17 19:22:52 UTC720224561VaibhavKumarDixitJulia Computing0000-0001-7763-2717ChristopherRackauckasJulia Computing, Massachusetts Institute of Technology, Pumas-AI0000-0001-5850-066310.21105/joss.04561https://doi.org/10.5281/zenodo.6993162Juliahttps://joss.theoj.org/papers/10.21105/joss.04561.pdfjulia, global sensitivity analysistag:joss.theoj.org,2005:Paper/36902022-08-09T14:09:57Z2022-08-10T00:01:11ZMallob: Scalable SAT Solving On Demand With Decentralized Job Schedulingacceptedv1.0.02022-06-29 13:27:02 UTC762022-08-09 14:09:57 UTC720224591PeterSandersKarlsruhe Institute of Technology, Germany0000-0003-3330-9349DominikSchreiberKarlsruhe Institute of Technology, Germany0000-0002-4185-185110.21105/joss.04591v1.1.0Pythonhttps://joss.theoj.org/papers/10.21105/joss.04591.pdfC++, online job scheduling, malleability, load balancing, propositional satisfiability, SAT solving, parallel processing, HPCtag:joss.theoj.org,2005:Paper/36872022-08-03T13:26:59Z2023-08-21T09:34:38ZAccelerating Parallel Operation for Compacting Selected Elements on GPUsaccepted1.02022-06-28 19:04:46 UTC752022-08-03 13:26:59 UTC720224589JohannesFettTU Dresden, Germany0000-0001-7898-0502UrsKoberTU Dresden, GermanyChristianSchwarzTU Dresden, GermanyDirkHabichTU Dresden, GermanyWolfgangLehnerTU Dresden, Germany10.21105/joss.04589https://doi.org/10.5281/zenodo.6884000Python, Cudahttps://joss.theoj.org/papers/10.21105/joss.04589.pdfCompacting, GPU, Optimization, Parallel, Euro-Partag:joss.theoj.org,2005:Paper/34442022-06-25T17:36:18Z2022-06-26T00:01:16ZpyABC: Efficient and robust easy-to-use approximate Bayesian computationaccepted0.12.22022-03-26 22:08:05 UTC742022-06-25 17:36:18 UTC720224304YannikSchälteFaculty of Mathematics and Natural Sciences, University of Bonn, Bonn, Germany, Institute of Computational Biology, Helmholtz Center Munich, Neuherberg, Germany, Center for Mathematics, Technical University Munich, Garching, Germany0000-0003-1293-820XEmmanuelKlingerInstitute of Computational Biology, Helmholtz Center Munich, Neuherberg, Germany, Center for Mathematics, Technical University Munich, Garching, Germany, Department of Connectomics, Max Planck Institute for Brain Research, Frankfurt, GermanyEmadAlamoudiFaculty of Mathematics and Natural Sciences, University of Bonn, Bonn, Germany0000-0002-9129-4635JanHasenauerFaculty of Mathematics and Natural Sciences, University of Bonn, Bonn, Germany, Institute of Computational Biology, Helmholtz Center Munich, Neuherberg, Germany, Center for Mathematics, Technical University Munich, Garching, Germany0000-0002-4935-331210.21105/joss.04304https://doi.org/10.5281/zenodo.6677826Python, Makohttps://joss.theoj.org/papers/10.21105/joss.04304.pdfapproximate Bayesian computation, ABC, likelihood-free inference, high-performance computing, parallel, sequential Monte Carlotag:joss.theoj.org,2005:Paper/32942022-06-09T14:33:25Z2022-06-10T00:01:17ZGridapDistributed: a massively parallel finite element toolbox in Juliaacceptedv0.2.42022-01-18 08:34:54 UTC742022-06-09 14:33:25 UTC720224157SantiagoBadiaSchool of Mathematics, Monash University, Clayton, Victoria, 3800, Australia., Centre Internacional de Mètodes Numèrics en Enginyeria, Esteve Terrades 5, E-08860 Castelldefels, Spain.0000-0003-2391-4086AlbertoF.MartínSchool of Mathematics, Monash University, Clayton, Victoria, 3800, Australia.0000-0001-5751-4561FrancescVerdugoCentre Internacional de Mètodes Numèrics en Enginyeria, Esteve Terrades 5, E-08860 Castelldefels, Spain.0000-0003-3667-443X10.21105/joss.04157https://doi.org/10.5281/zenodo.6622081Juliahttps://joss.theoj.org/papers/10.21105/joss.04157.pdfPartial Differential Equations, Finite Elements, Distributed memory parallelization, High Performance Computing