{"id":21044310,"url":"https://github.com/trixi-framework/paper-2021-juliacon","last_synced_at":"2025-10-15T22:51:01.537Z","repository":{"id":45006204,"uuid":"388016130","full_name":"trixi-framework/paper-2021-juliacon","owner":"trixi-framework","description":"Adaptive numerical simulations with Trixi.jl: A case study of Julia for scientific computing","archived":false,"fork":false,"pushed_at":"2022-01-15T09:13:53.000Z","size":7904,"stargazers_count":6,"open_issues_count":0,"forks_count":0,"subscribers_count":3,"default_branch":"main","last_synced_at":"2025-10-06T03:01:12.668Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"","language":"TeX","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/trixi-framework.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE.md","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2021-07-21T06:24:39.000Z","updated_at":"2024-03-17T20:27:21.000Z","dependencies_parsed_at":"2022-09-22T15:52:27.268Z","dependency_job_id":null,"html_url":"https://github.com/trixi-framework/paper-2021-juliacon","commit_stats":null,"previous_names":[],"tags_count":3,"template":false,"template_full_name":null,"purl":"pkg:github/trixi-framework/paper-2021-juliacon","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/trixi-framework%2Fpaper-2021-juliacon","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/trixi-framework%2Fpaper-2021-juliacon/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/trixi-framework%2Fpaper-2021-juliacon/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/trixi-framework%2Fpaper-2021-juliacon/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/trixi-framework","download_url":"https://codeload.github.com/trixi-framework/paper-2021-juliacon/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/trixi-framework%2Fpaper-2021-juliacon/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":279124093,"owners_count":26108835,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","status":"online","status_checked_at":"2025-10-15T02:00:07.814Z","response_time":56,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-11-19T14:16:16.095Z","updated_at":"2025-10-15T22:51:01.501Z","avatar_url":"https://github.com/trixi-framework.png","language":"TeX","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Adaptive numerical simulations with Trixi.jl: A case study of Julia for scientific computing\n\n[![License: MIT](https://img.shields.io/badge/License-MIT-success.svg)](https://opensource.org/licenses/MIT)\n[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.5201484.svg)](https://doi.org/10.5281/zenodo.5201484)\n[![status](https://proceedings.juliacon.org/papers/e0a710cb74904fbd77e6528d4b55c7ce/status.svg)](https://proceedings.juliacon.org/papers/e0a710cb74904fbd77e6528d4b55c7ce)\n\nThis repository contains the source files of the paper on\n[Trixi.jl](https://github.com/trixi-framework/Trixi.jl) to be submitted\nto the proceedings of JuliaCon 2021. Additionally, it also contains\nmaterial to reproduce the numerical experiments reported therein.\n\n## Abstract\n\nWe present Trixi.jl, a Julia package for adaptive high-order numerical simulations\nof hyperbolic partial differential equations. Utilizing Julia's strengths,\nTrixi.jl is extensible, easy to use, and fast. We describe the main design choices\nthat enable these features and compare Trixi.jl with a mature open\nsource Fortran code that uses the same numerical methods.\nWe conclude with an assessment of Julia for simulation-focused scientific\ncomputing, an area that is still dominated by traditional high-performance\ncomputing languages such as C, C++, and Fortran.\n\n\n## Referencing\n\nThis repository contains information and code to reproduce the results presented in the article\n```bibtex\n@article{ranocha2022adaptive,\n  title={Adaptive numerical simulations with {T}rixi.jl:\n         {A} case study of {J}ulia for scientific computing},\n  author={Ranocha, Hendrik and Schlottke-Lakemper, Michael and Winters, Andrew Ross\n          and Faulhaber, Erik and Chan, Jesse and Gassner, Gregor},\n  journal={Proceedings of the JuliaCon Conferences},\n  volume={1},\n  number={1},\n  pages={77},\n  year={2022},\n  month={01},\n  publisher={The Open Journal},\n  doi={10.21105/jcon.00077},\n  eprint={2108.06476},\n  eprinttype={arXiv},\n  eprintclass={cs.MS}\n}\n```\n\nIf you find these results useful, please cite the article mentioned above. If you\nuse the implementations provided here, please **also** cite this repository as\n```bibtex\n@misc{ranocha2021adaptiveRepro,\n  title={Reproducibility repository for\n         Adaptive numerical simulations with {T}rixi.jl:\n         {A} case study of {J}ulia for scientific computing},\n  author={Ranocha, Hendrik and Schlottke-Lakemper, Michael and Winters, Andrew Ross\n          and Faulhaber, Erik and Chan, Jesse and Gassner, Gregor},\n  year={2021},\n  month={08},\n  howpublished={\\url{https://github.com/trixi-framework/paper-2021-juliacon}},\n  doi={10.5281/zenodo.5201484}\n}\n```\n\n\n## Reproducing the numerical experiments\n\n- All material necessary to reproduce the simulation of a Mach 2000 jet shown\n  in the paper is contained in the folder [`figure_jet`](figure_jet/),\n  including a [`README.md`](figure_jet/README.md) with instructions.\n- All material necessary to reproduce the simulation of a Kelvin-Helmholtz\n  shown in the paper is contained in the folder\n  [`figure_kelvin_helmholtz`](figure_kelvin_helmholtz/),\n  including a [`README.md`](figure_kelvin_helmholtz/README.md) with instructions.\n- All material necessary to reproduce the acoustics simulation on a curved\n  high-order mesh shown in the paper is contained in the folder\n  [`figure_gingerbread_man`](figure_gingerbread_man/),\n  including a [`README.md`](figure_gingerbread_man/README.md) with instructions.\n- All material necessary to reproduce the performance comparison with the Fortran\n  code [FLUXO](https://gitlab.com/project-fluxo/fluxo) is contained in the folder\n  [`pid_runs`](pid_runs/),\n  including a [`README.md`](pid_runs/README.md) with instructions.\n\n\n## Building the paper\n\nThe source files of the paper are contained in the folder [`paper`](paper/).\nBuild the paper by running\n```bash\nmake\n```\nClean up your mess afterwards with\n```bash\nmake clean\n```\n\n\n## Useful links\n\n* JuliaCon Proceedings: https://proceedings.juliacon.org/\n* Author's guide: https://juliacon.github.io/proceedings-guide/author/\n\n\n## License\n\nThe source code included in this repository is licensed under the MIT license\n(see [LICENSE.md](LICENSE.md)). The manuscript is subject to the license of\nthe JuliaCon proceedings.\n\n\n## Disclaimer\n\nEverything is provided as is and without warranty. Use at your own risk!\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftrixi-framework%2Fpaper-2021-juliacon","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftrixi-framework%2Fpaper-2021-juliacon","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftrixi-framework%2Fpaper-2021-juliacon/lists"}