{"id":20172649,"url":"https://github.com/usarmyresearchlab/arl-hierarchical-multiscale-framework","last_synced_at":"2026-06-06T04:31:53.484Z","repository":{"id":248742143,"uuid":"825763884","full_name":"USArmyResearchLab/ARL-Hierarchical-Multiscale-Framework","owner":"USArmyResearchLab","description":"The ARL Hierarchical MultiScale Framework (ARL-HMS) is a software library for development of multiscale models on heterogeneous high-performance computing systems.","archived":false,"fork":false,"pushed_at":"2024-07-18T12:05:52.000Z","size":1634,"stargazers_count":1,"open_issues_count":0,"forks_count":2,"subscribers_count":4,"default_branch":"main","last_synced_at":"2025-03-03T04:41:29.248Z","etag":null,"topics":["adaptive-computation","multiscale-modeling","scale-bridging"],"latest_commit_sha":null,"homepage":"","language":"C++","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"cc0-1.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/USArmyResearchLab.png","metadata":{"files":{"readme":"README.md","changelog":"ChangeLog","contributing":null,"funding":null,"license":"COPYING","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":"AUTHORS","dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-07-08T12:57:55.000Z","updated_at":"2025-01-24T23:35:55.000Z","dependencies_parsed_at":null,"dependency_job_id":"ea61ee72-4ab2-4468-9ebb-75f104489ea2","html_url":"https://github.com/USArmyResearchLab/ARL-Hierarchical-Multiscale-Framework","commit_stats":null,"previous_names":["usarmyresearchlab/arl-hierarchical-multiscale-framework"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/USArmyResearchLab/ARL-Hierarchical-Multiscale-Framework","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/USArmyResearchLab%2FARL-Hierarchical-Multiscale-Framework","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/USArmyResearchLab%2FARL-Hierarchical-Multiscale-Framework/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/USArmyResearchLab%2FARL-Hierarchical-Multiscale-Framework/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/USArmyResearchLab%2FARL-Hierarchical-Multiscale-Framework/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/USArmyResearchLab","download_url":"https://codeload.github.com/USArmyResearchLab/ARL-Hierarchical-Multiscale-Framework/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/USArmyResearchLab%2FARL-Hierarchical-Multiscale-Framework/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":33969883,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-26T15:22:16.424Z","status":"online","status_checked_at":"2026-06-06T02:00:07.033Z","response_time":107,"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":["adaptive-computation","multiscale-modeling","scale-bridging"],"created_at":"2024-11-14T01:31:43.988Z","updated_at":"2026-06-06T04:31:53.469Z","avatar_url":"https://github.com/USArmyResearchLab.png","language":"C++","funding_links":[],"categories":[],"sub_categories":[],"readme":"## ARL Hierarchical MultiScale Framework (ARL-HMS)\n\nThe ARL Hierarchical MultiScale Framework (ARL-HMS) is a software\nlibrary for development of multiscale models on heterogeneous\nhigh-performance computing systems. Multiscale models are created in\nARL-HMS from an assembly of individual at-scale model components. A\nruntime system adaptively evaluates at-scale model components in\nparallel and performs data extraction necessary for\nscale-bridging. Adaptive machine learning methods are also available\nin ARL-HMS to significantly reduce computational expense.\n\nThe ARL-HMS software is implemented in C++ and includes bindings to\nPython. It can incorporate individual at-scale model components\nwritten in any programming language and can also incorporate\nclosed-source or proprietary software allowing users to leverage\nexisting complex at-scale models for multiscale model development.\n\nA User's Guide to ARL-HMS is included in this software repository\n(ARL-TR-9820.pdf). The User's Guide documents the steps necessary to\ndevelop multiscale models with ARL-HMS. It includes an overview of the\nmathematical approach to multiscale modeling the framework adopts, the\nsteps necessary to incorporate at-scale models, use of the ARL-HMS\nBroker to perform at-scale model evaluation and data extraction, and\nuse of the adaptive surrogate modeling capabilities implemented in\nARL-HMS. A simple example ARL-HMS application, implemented in both C++\nand Python, is included that performs Monte Carlo estimation of\n$\\pi$. The example application is also included in the repository in\nthe examples/mcpi directory.\n\n### ARL-HMS Dependencies and Compilation Steps\n\nARL-HMS requires a compiled Boost C++ installation for data\nserialization and shared pointer capabilities.\n\nOptional dependencies include a Message Passing Interface (MPI)\nlibrary to enable MPI communication and fan-in data communication\nbetween ARL-HMS components. A Python installation is required to build\nthe ARL-HMS Python bindings. The Adaptive Sampling Framework (ASF)\nlibrary from LLNL (https://github.com/exmatex/aspa) is also required\nto use the Kriging database interpolation method.\n\nARL-HMS uses a standard autotools installation procedure (configure,\nmake, make install) documented in Section 5 of the ARL-HMS User's\nGuide.\n\n### ARL-HMS Citations\n\nWe request that if you publish results that make use of the ARL-HMS\nsoftware, please cite the following paper and ARL-HMS User's Guide:\n\n```\n@article{Knap2016,\n  author = {Knap, J. and Spear, C. and Leiter, K. and Becker, R. and Powell, D.},\n  title = {A computational framework for scale-bridging in multi-scale simulations},\n  journal = {International Journal for Numerical Methods in Engineering},\n  volume = {108},\n  number = {13},\n  pages = {1649-1666},\n  doi = {https://doi.org/10.1002/nme.5270},\n  year = {2016}\n}\n```\n```\n@techreport{Leiter2023,\n  institution = {{DEVCOM} Army Research Laboratory},\n  title={User's Guide for the {Hierarchical MultiScale Framework} ({HMS})},\n  author={Leiter, Kenneth W and Crone, Joshua C and Knap, Jaroslaw},\n  year={2023},\n  month={Oct},\n  number={ARL-TR-9820}\n}\n```\n### License\n\nARL Hierarchical MultiScale Framework (ARL-HMS) is licensed under the\nCreative Commons Zero 1.0 Universal (CC0 1.0) license. Please see\n[LICENSE](LICENSE) for details.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fusarmyresearchlab%2Farl-hierarchical-multiscale-framework","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fusarmyresearchlab%2Farl-hierarchical-multiscale-framework","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fusarmyresearchlab%2Farl-hierarchical-multiscale-framework/lists"}