{"id":38665593,"url":"https://github.com/lene/lina","last_synced_at":"2026-01-17T09:47:29.017Z","repository":{"id":31531280,"uuid":"35095817","full_name":"lene/lina","owner":"lene","description":"Linear Algebra library in C++ and OpenCL for machine learning algorithms","archived":false,"fork":false,"pushed_at":"2016-03-03T15:07:30.000Z","size":101,"stargazers_count":4,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-03-21T22:02:57.586Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"C++","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/lene.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}},"created_at":"2015-05-05T11:41:46.000Z","updated_at":"2023-12-24T06:09:55.000Z","dependencies_parsed_at":"2022-09-09T20:41:47.634Z","dependency_job_id":null,"html_url":"https://github.com/lene/lina","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/lene/lina","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lene%2Flina","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lene%2Flina/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lene%2Flina/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lene%2Flina/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/lene","download_url":"https://codeload.github.com/lene/lina/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lene%2Flina/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":28505565,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-01-17T06:57:29.758Z","status":"ssl_error","status_checked_at":"2026-01-17T06:56:03.931Z","response_time":85,"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":[],"created_at":"2026-01-17T09:47:28.889Z","updated_at":"2026-01-17T09:47:28.984Z","avatar_url":"https://github.com/lene.png","language":"C++","funding_links":[],"categories":[],"sub_categories":[],"readme":"# lina\nLinear Algebra library in C++ and OpenCL for machine learning algorithms.\nGPU-accelerated routines for multidimensional optimization, linear regression,\nlogistic regression. Later: neural networks. Even later: SVM and recommender systems. \n\n**This is pretty much dead since Google published the [TensorFlow](http://www.tensorflow.org/) \nmachine learning library which does anything this project can ever hope to do.**\n\n## Dependencies:\n\n### Boost uBLAS\n\n    sudo apt-get install libboost-dev\n    \n### ViennaCl\n\n    sudo apt-get install libviennacl-dev\n    \n### OpenCl headers and drivers\n\nYMMV, packages to install depend on present GPU:\n\n    sudo apt-get install ocl-icd-libopencl1 ocl-icd-opencl-dev opencl-headers\n    \n### Google Test\n\n    sudo apt-get install libgtest-dev\n    cd /usr/src/gtest\n    sudo cmake CMakeLists.txt\n    sudo make\n    sudo cp *.a /usr/lib\n\n## To do\n\n* improve RegressionSolver\n  * make the kind of regression a class template parameter\n  * add predict() function\n  * add function to determine training accuracy\n* use smart pointers again (in gradient descent)\n* logistic regression\n  * minimization - is there a better way than gradient descent? does GD always give so bad results in nontrivial systems?\n  * training accuracy\n  * regularization\n    * coursera example\n  * multi-class classification\n* ensure that only one matrix is stored in GPU memory at each time when using LinearRegressionSolver\n* gradient descent seems to run on one CPU core only, at least with logistic regression\n* factor out matrix and vector types so they can be used as template parameters\n  * easier conversion between ublas and viennacl data types and algorithms?\n* neural networks\n* compile conditionally on presence of gtest so that it can be distributed without it\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flene%2Flina","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Flene%2Flina","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flene%2Flina/lists"}