{"id":48082542,"url":"https://github.com/sandialabs/rol","last_synced_at":"2026-04-04T14:58:09.497Z","repository":{"id":313274436,"uuid":"1050748387","full_name":"sandialabs/rol","owner":"sandialabs","description":"Rapid Optimization Library","archived":false,"fork":false,"pushed_at":"2026-04-03T21:02:37.000Z","size":23245,"stargazers_count":18,"open_issues_count":3,"forks_count":6,"subscribers_count":1,"default_branch":"develop","last_synced_at":"2026-04-03T22:33:12.350Z","etag":null,"topics":["large-scale-optimization","numerical-optimization","optimal-experimental-design","pde-constrained-optimization","scr-1629","snl-science-libs","stochastic-optimization","trust-region-methods"],"latest_commit_sha":null,"homepage":"https://rol.sandia.gov","language":"C++","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"bsd-3-clause","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/sandialabs.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null,"notice":null,"maintainers":null,"copyright":"COPYRIGHT","agents":null,"dco":null,"cla":null}},"created_at":"2025-09-04T21:57:43.000Z","updated_at":"2026-03-31T10:40:36.000Z","dependencies_parsed_at":"2025-10-30T23:25:29.796Z","dependency_job_id":null,"html_url":"https://github.com/sandialabs/rol","commit_stats":null,"previous_names":["sandialabs/rol"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/sandialabs/rol","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sandialabs%2Frol","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sandialabs%2Frol/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sandialabs%2Frol/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sandialabs%2Frol/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/sandialabs","download_url":"https://codeload.github.com/sandialabs/rol/tar.gz/refs/heads/develop","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sandialabs%2Frol/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":31403942,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-04T10:20:44.708Z","status":"ssl_error","status_checked_at":"2026-04-04T10:20:06.846Z","response_time":60,"last_error":"SSL_read: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"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":["large-scale-optimization","numerical-optimization","optimal-experimental-design","pde-constrained-optimization","scr-1629","snl-science-libs","stochastic-optimization","trust-region-methods"],"created_at":"2026-04-04T14:58:08.759Z","updated_at":"2026-04-04T14:58:09.491Z","avatar_url":"https://github.com/sandialabs.png","language":"C++","readme":"# Rapid Optimization Library (ROL)\n\n![Rapid Optimization Library](https://raw.githubusercontent.com/sandialabs/rol/refs/heads/develop/rol.png)\n\n**ROL** (as in rock and _roll_) is a high-performance C++ library for numerical optimization.\nROL brings an extensive collection of state-of-the-art optimization algorithms to virtually\nany application. Its programming interface supports any computational hardware, including\nheterogeneous many-core systems with digital and analog accelerators. ROL has been used with\ngreat success for optimal control, optimal design, inverse problems, image processing and\nmesh optimization, in application areas including geophysics, structural dynamics, fluid\ndynamics, electromagnetics, quantum computing, hypersonics and geospatial imaging.\n\nFor additional details, see [https://rol.sandia.gov](https://rol.sandia.gov).\n\nFeature highlights:\n\n1. Vector abstractions and matrix-free interface for universal applicability\n2. Modern algorithms for unconstrained and constrained optimization\n3. Easy-to-use methods for stochastic and risk-aware optimization\n4. Fast and robust algorithms for nonsmooth optimization\n5. Trust-region methods for inexact and adaptive computations\n6. PDE-OPT application development kit for PDE-constrained optimization\n7. Interfaces and algorithms for optimal experimental design\n\n\n## Getting Started\nROL is a C++ library with a cmake build system.\nThere are minimal third-party library requirements consisting of BLAS and LAPACK\nwhich also require a suitable Fortran compiler on the system.\nOn Linux-based systems with an apt package manager,\nthe dependencies may be installed with\n```\napt install cmake gfortran libopenblas-dev liblapack3\n```\n\nSome typical configure scripts may be found in the `.github/workflows/` directory.\nAn in-source release build including ROL's examples and tests may be configured\nfrom within the source directory with\n```\ncmake -D CMAKE_BUILD_TYPE:STRING=RELEASE \\\n      -D ENABLE_EXAMPLES:BOOL=ON \\\n      -D ENABLE_TESTS:BOOL=ON \\\n      -B build \\\n      .\n```\n\nAfter a successful configure, ROL is built by then changing\nto the build directory and running `make`\n```\ncd build\nmake\n```\n\n\n## Copyright and License\nSee COPYRIGHT and LICENSE.\n\n\n## Questions?\nContact team or developers:\n\n* ROL Team     (GitHub handle: @sandialabs/rol)\n* Drew Kouri   (GitHub handle: [dpkouri](https://github.com/dpkouri) or dpkouri@sandia.gov)\n* Denis Ridzal (GitHub handle: [dridzal](https://github.com/dridzal) or dridzal@sandia.gov)\n\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsandialabs%2Frol","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsandialabs%2Frol","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsandialabs%2Frol/lists"}