{"id":21389475,"url":"https://github.com/feifeibear/pstensor","last_synced_at":"2026-05-08T09:33:17.902Z","repository":{"id":85016996,"uuid":"428585151","full_name":"feifeibear/PSTensor","owner":"feifeibear","description":"PSTensor provides a way to hack the memory management of tensors in TensorFlow and PyTorch by defining your own C++ Tensor Class.","archived":false,"fork":false,"pushed_at":"2022-02-10T05:38:46.000Z","size":32,"stargazers_count":10,"open_issues_count":1,"forks_count":0,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-09-02T04:26:31.813Z","etag":null,"topics":["cuda","deeplearning","machinelearning","pytorch","tensorflow2"],"latest_commit_sha":null,"homepage":"","language":"C++","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"other","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/feifeibear.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":"2021-11-16T09:03:11.000Z","updated_at":"2024-10-04T02:04:05.000Z","dependencies_parsed_at":"2023-04-09T04:16:46.894Z","dependency_job_id":null,"html_url":"https://github.com/feifeibear/PSTensor","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/feifeibear/PSTensor","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/feifeibear%2FPSTensor","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/feifeibear%2FPSTensor/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/feifeibear%2FPSTensor/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/feifeibear%2FPSTensor/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/feifeibear","download_url":"https://codeload.github.com/feifeibear/PSTensor/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/feifeibear%2FPSTensor/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":32774897,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-08T08:22:46.396Z","status":"ssl_error","status_checked_at":"2026-05-08T08:22:45.650Z","response_time":54,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.6:443 state=error: 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":["cuda","deeplearning","machinelearning","pytorch","tensorflow2"],"created_at":"2024-11-22T12:26:40.103Z","updated_at":"2026-05-08T09:33:17.882Z","avatar_url":"https://github.com/feifeibear.png","language":"C++","funding_links":[],"categories":[],"sub_categories":[],"readme":"## PSTensor : Customized a Tensor Data Structure Compatible with PyTorch and TensorFlow.\n\n\nYou may need this software in the following cases.\n1. Manage memory allocation by yourself. Sometimes, you are irritated by the framework's memory allocation mechanism. They use a complicated caching-based allocator and generate fragments.\n\n2. Unified framework-agnostic memory management operations.\n\n3. Customized Communication Pattern. Using PyTorch, it is impossible to implement GPU P2P communication, since nccl backend only supports collective communication APIs. Now, you can implement it with help of CUDA-level libraries.\n\n\n## Installation\n```\nmkdir build \u0026\u0026 cd build \u0026\u0026 cmake .. \u0026\u0026 make\npip install `find . -name \"*whl\"`\n```\n\n\n## Usage\nSee [PyTorch Example](./test_torch.py) and [TensorFlow Example](./test_tf.py)  for details.\nMore features are Working In Progress.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffeifeibear%2Fpstensor","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ffeifeibear%2Fpstensor","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffeifeibear%2Fpstensor/lists"}