{"id":13574245,"url":"https://github.com/artecs-group/k-means","last_synced_at":"2025-10-05T00:32:41.150Z","repository":{"id":185547375,"uuid":"639743822","full_name":"artecs-group/k-means","owner":"artecs-group","description":"Multi-device K-Means based on the He-Vialle implementation. ","archived":false,"fork":false,"pushed_at":"2023-05-12T06:26:41.000Z","size":19109,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":6,"default_branch":"master","last_synced_at":"2024-11-05T09:44:09.564Z","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":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/artecs-group.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}},"created_at":"2023-05-12T06:08:46.000Z","updated_at":"2024-10-31T16:00:59.000Z","dependencies_parsed_at":"2024-01-14T04:07:26.398Z","dependency_job_id":null,"html_url":"https://github.com/artecs-group/k-means","commit_stats":null,"previous_names":["artecs-group/k-means"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/artecs-group%2Fk-means","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/artecs-group%2Fk-means/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/artecs-group%2Fk-means/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/artecs-group%2Fk-means/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/artecs-group","download_url":"https://codeload.github.com/artecs-group/k-means/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":243526934,"owners_count":20305115,"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","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":"2024-08-01T15:00:48.688Z","updated_at":"2025-10-05T00:32:31.473Z","avatar_url":"https://github.com/artecs-group.png","language":"C++","funding_links":[],"categories":["Table of Contents","Projects"],"sub_categories":["AI - Machine Learning","AI"],"readme":"# K-Means\n\n\u003cimg alt=\"license\" src=\"https://img.shields.io/github/license/mashape/apistatus.svg\"/\u003e\n\nThis repository contains a k-means implementation for CUDA and SYCL.\n\n## Requirements\nYou have to intall the following dependencies:\n\n* [CUDA Toolkit 11.7](https://developer.nvidia.com/cuda-11-7-0-download-archive)\n* [oneAPI 2022.3](https://www.intel.com/content/www/us/en/developer/tools/oneapi/base-toolkit-download.html)\n* [Intel Clang/LLVM](https://github.com/intel/llvm/blob/sycl/sycl/doc/GetStartedGuide.md) -\u003e In order to run SYCL over Nvidia GPUs.\n* [hipSYCL](https://github.com/OpenSYCL/OpenSYCL) -\u003e Optional.\n\n## Project Structure\nThe repository is ordered in this folders:\n\n* [He_Vialle_impl](/He_Vialle_impl/): Has the original implementation, you can found it [here](https://gitlab-research.centralesupelec.fr/Stephane.Vialle/cpu-gpu-kmeans).\n* [custom_impl](/custom_impl/): Has the CUDA and SYCL custom implementations based on the original one.\n* [etc](/etc/): Has the scripts to automatically get the application times.\n* [data](/data/): You have there all the data requiered to reproduce the experiments.\n\n## Publications\n* Youssef Faqir-Rhazoui and Carlos García (2023). \"Exploring the Performance and Portability of the k-means Algorithm on SYCL Across CPU and GPU Architectures\". The Journal of Supercomputing.\n    * [Free available here](https://doi.org/10.21203/rs.3.rs-2402689/v1).\n\n## Acknowledgements\nThis work has been supported by the EU (FEDER), the Spanish MINECO and CM under grants S2018/TCS-4423, PID2021-126576NB-I00 funded by MCIN/AEI/10.13039/501100011033 and by \"ERDF A way of making Europe\".\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fartecs-group%2Fk-means","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fartecs-group%2Fk-means","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fartecs-group%2Fk-means/lists"}