{"id":23747859,"url":"https://github.com/ktaletsk/gpu_dsm","last_synced_at":"2025-09-10T21:10:00.981Z","repository":{"id":20948437,"uuid":"24236916","full_name":"ktaletsk/gpu_dsm","owner":"ktaletsk","description":"🔗Accessible quantitative polymer rheology predictions with slip-links on GPU","archived":false,"fork":false,"pushed_at":"2020-03-27T17:23:12.000Z","size":2778,"stargazers_count":7,"open_issues_count":1,"forks_count":2,"subscribers_count":5,"default_branch":"master","last_synced_at":"2024-08-21T19:32:14.465Z","etag":null,"topics":["c-plus-plus","cuda","gpu","polymer","rheology"],"latest_commit_sha":null,"homepage":"http://www.chbe.iit.edu/~schieber/","language":"C++","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/ktaletsk.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":"2014-09-19T16:24:56.000Z","updated_at":"2023-04-08T08:36:32.000Z","dependencies_parsed_at":"2022-08-30T21:30:57.215Z","dependency_job_id":null,"html_url":"https://github.com/ktaletsk/gpu_dsm","commit_stats":null,"previous_names":[],"tags_count":10,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ktaletsk%2Fgpu_dsm","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ktaletsk%2Fgpu_dsm/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ktaletsk%2Fgpu_dsm/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ktaletsk%2Fgpu_dsm/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ktaletsk","download_url":"https://codeload.github.com/ktaletsk/gpu_dsm/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":231999629,"owners_count":18458180,"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":["c-plus-plus","cuda","gpu","polymer","rheology"],"created_at":"2024-12-31T14:58:10.442Z","updated_at":"2024-12-31T14:58:10.894Z","avatar_url":"https://github.com/ktaletsk.png","language":"C++","funding_links":[],"categories":[],"sub_categories":[],"readme":"### **The Discrete Slip-Link Model (DSM)** is a mathematical model that describes the dynamics of flexible entangled polymer melts.\n\n**GPU DSM** is a computational implementation of that model on CUDA/C++. GPU DSM is developed in [The Center for molecular study of condensed soft matter (μCoSM)](http://www.chbe.iit.edu/~schieber/index.html). GPU DSM is free open-source software under the GNU GPL v3.0 license.\n\n**[Download latest Linux GUI version](https://github.com/ktaletsk/gpu_dsm/releases)**\n\n### Compilation instructions:\n\n#### Linux (tested on Ubuntu/Kubuntu 14.04)\n\nRequirements:\n\ng++\n\n**[Cuda Toolkit](https://developer.nvidia.com/cuda-toolkit)** (6.0, 6.5, 7.0, 7.5, 8.0, 9.0, 9.1)\n\n**[Qt](http://www.qt.io/download-open-source/)** (for GUI)\n\noptional: make\n    \n1. Open terminal.\n    \n2a. Compile the command line interface (CLI) version, navigate to the directory where you extracted the zip file:\n`cd \u003cpath_to_repository\u003e/gpu_dsm/CLI`.\n    \n2b. Compile the graphical user interface (GUI) version, navigate to the directory where you extracted the zip file:\n`cd \u003cpath_to_repository\u003e/gpu_dsm/GUI`.\n\n3a. Run `make all` to complie **gpu_DSM**.\n\n3b. Run `\u003cpath_to_Qt\u003e/\u003cversion_of_Qt\u003e/gcc_64/bin/qmake -spec linux-g++ -o Makefile dsm.pro`. Current version of Qt is 5.6.\n\nRun `make all` to compile **dsm**.\n    \n4a. You can test it by running `./gpu_DSM`.\n    \n4b. You can test it by running `./dsm` or clicking to the app icon in a file manager.\n\n#### Windows (tested on Windows 10, 64bit)\n\nRequirements:\n\n**[Microsoft Visual Studio 2017](https://www.visualstudio.com/downloads/)** (Community/Professional/Enterprise)\n\n**[CUDA Toolkit](https://developer.nvidia.com/cuda-toolkit)**\n\n0. Install Visual Studio first, then install CUDA.\n\n1. Open x64 Native Tools Command Prompt for VS 2017.\n\n2. Move to `\u003cpath_to_repository\u003e/gpu_dsm/CLI`.\n\n3. Compile code using `make.bat` command. Make sure to change `-gencode arch=compute_50,code=sm_50` to reflect appropriate compute capability of your Nvidia GPU. To find compute capability of your GPU check [this page](https://developer.nvidia.com/cuda-gpus). For example, NVIDIA TITAN X has compute capability 6.1 and you will need to change the command flag to `-gencode arch=compute_61,code=sm_61`.\n\n4. You can test it by running `gpu_DSM.exe`.\n\n#### Running (CLI):\n    \n**gpu_DSM** command line parameters:\n\nfirst parameter is seed/job_ID\nexample: \n`./gpu_DSM 1`\nall the files generated in this run will have \"_1\" in the filename.\nadditionally 1 will be used as a seed number for pseudo random number generator\n\n-s filename \nsaves chain conformations in \"filename\" file in the end of run.\n\n-l filename\nloads previously saved chain conformations from the \"filename\" file in the beginning of run.\n\n-d number\nselects GPU to use. Useful if multiple GPU are present in the system. Numberring starts from 0.\n    \n-distr\nsaves final Z,N,Q distributions in .dat files\n\n### Citation\n[![DOI](https://zenodo.org/badge/24236916.svg)](https://zenodo.org/badge/latestdoi/24236916)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fktaletsk%2Fgpu_dsm","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fktaletsk%2Fgpu_dsm","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fktaletsk%2Fgpu_dsm/lists"}