{"library":"rmm-cu12","type":"library","category":null,"description":"RMM (RAPIDS Memory Manager) is a C++ and Python library for efficient GPU memory management. It provides a highly optimized allocation and deallocation framework tailored for NVIDIA GPUs, often used within the RAPIDS ecosystem to improve performance of data science workloads. The current version is 26.4.0, and it generally follows a monthly release cadence.","language":"python","status":"active","version":"26.4.0","tags":["GPU","memory management","CUDA","RAPIDS","data science"],"install":[{"cmd":"pip install rmm-cu12","imports":["import rmm","from rmm.mr import PoolMemoryResource","from rmm.mr import CudaMemoryResource","No direct import; use public rmm or rmm.mr APIs."]}],"homepage":"https://docs.rapids.ai/api/rmm/stable/","github":"https://github.com/rapidsai/rmm","docs":null,"changelog":null,"pypi":"https://pypi.org/project/rmm-cu12/","npm":null,"openapi_spec":null,"status_page":null,"smithery":null,"compatibility":{"summary":{"python_range":"3.10–3.9","success_rate":50,"avg_install_s":5.7,"avg_import_s":0.49,"wheel_type":"wheel"},"url":"https://checklist.day/v1/registry/rmm-cu12/compatibility"},"provenance":{"verified_status":"passing","verified_at":"Sun Jun 28","last_verified":"Sun Jun 28","next_check":"Tue Jul 28","install_tag":null}}