{"id":18634592,"url":"https://github.com/abrg-models/neoarealize","last_synced_at":"2025-10-16T17:51:40.161Z","repository":{"id":77802491,"uuid":"139155028","full_name":"ABRG-Models/NeoArealize","owner":"ABRG-Models","description":"Neo-cortex arealization modelling","archived":false,"fork":false,"pushed_at":"2020-01-10T16:25:01.000Z","size":6447,"stargazers_count":0,"open_issues_count":0,"forks_count":1,"subscribers_count":3,"default_branch":"master","last_synced_at":"2024-12-27T08:27:10.380Z","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-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/ABRG-Models.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}},"created_at":"2018-06-29T13:49:46.000Z","updated_at":"2019-09-16T09:59:59.000Z","dependencies_parsed_at":null,"dependency_job_id":"7ec19f9f-131b-4381-bd1c-286bc6e64db9","html_url":"https://github.com/ABRG-Models/NeoArealize","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ABRG-Models%2FNeoArealize","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ABRG-Models%2FNeoArealize/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ABRG-Models%2FNeoArealize/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ABRG-Models%2FNeoArealize/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ABRG-Models","download_url":"https://codeload.github.com/ABRG-Models/NeoArealize/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":239432873,"owners_count":19637799,"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":"2024-11-07T05:19:44.699Z","updated_at":"2025-10-16T17:51:40.092Z","avatar_url":"https://github.com/ABRG-Models.png","language":"C++","funding_links":[],"categories":[],"sub_categories":[],"readme":"# NeoArealize\n\nA model of reaction-diffusion pattern formation in neocortex.\n\nPre-requisites:\n\nBuild and install morphologica from:\n\nhttps://github.com/ABRG-Models/morphologica\n\nMake sure these packages are installed (Debian/Ubuntu example):\n\nsudo apt install python python-numpy xterm\n\nBuild and install jsoncpp (in a directory '~/src', just for example,\nyou can build it wherever suits):\n\n```bash\nmkdir -p ~/src\ncd ~/src\ngit clone https://github.com/open-source-parsers/jsoncpp.git\ncd jsoncpp\nmkdir build\ncd build\ncmake -DCMAKE_INSTALL_PREFIX=/usr/local -DBUILD_SHARED_LIBS=YES ..\nmake\nsudo make install\n```\n\nNow you can build NeoArealize:\n\n```bash\ncd NeoArealize\nmkdir build\ncd build\ncmake ..\nmake\ncd ..\n```\n\nTo run:\n\n```bash\n./build/sim/james1 ./configs/c1.json\n```\n\nThe program reads parameters from c1.json and writes results into\n./logs/\n\nThe program is multi-threaded (using OpenMP pragmas). To get the best\nperformance it's usually necessary to experiment. Use a computation\nonly program (like james1c) and set different values for\nOMP_NUM_THREADS. For example:\n\n```bash\nexport OMP_NUM_THREADS=10 \u0026\u0026 time ./build/sim/james1c ./configs/c1.json \u003e/dev/null\n```\n\nOr use the findfastest.sh script in misc/.\n\nOn an Intel i9 7980XE with 18 cores, 13 seems to be fastest, but\nthere's not much difference for the range 6 cores to 18 cores.\n\nOn an AMD Threadripper 2990WX with 32 cores, about 20 seems to be\nfastest. This CPU is slower for these reaction diffusion equations\nthan the 7980XE. (2 seconds for the Intel, 3 seconds for the AMD).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fabrg-models%2Fneoarealize","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fabrg-models%2Fneoarealize","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fabrg-models%2Fneoarealize/lists"}