{"library":"nvshmem4py-cu13","type":"library","category":null,"description":"NVSHMEM4Py is the official Python language binding for NVSHMEM, a high-performance parallel programming interface based on OpenSHMEM. It provides a Pythonic interface to NVSHMEM's functionality, enabling applications to leverage the Partitioned Global Address Space (PGAS) programming model for efficient multi-GPU and multi-node communication. Key features include seamless integration with NumPy, CuPy, and PyTorch, symmetric memory management, and support for one-sided communication operations (put/get, collectives, atomics) and synchronization primitives. The library `nvshmem4py-cu13` specifically targets CUDA 13.x. The project demonstrates a healthy version release cadence, with the latest version 0.3.0 released in March 2026.","language":"python","status":"active","version":"0.3.0","tags":["HPC","GPU","CUDA","NVSHMEM","distributed computing","PGAS","Python bindings","scientific computing"],"install":[{"cmd":"pip install nvshmem4py-cu13 nvidia-nvshmem-cu13","imports":["import nvshmem.core as nvshmem"]}],"homepage":null,"github":null,"docs":null,"changelog":null,"pypi":"https://pypi.org/project/nvshmem4py-cu13/","npm":null,"openapi_spec":null,"status_page":null,"smithery":null,"compatibility":{"summary":{"python_range":"3.10–3.9","success_rate":50,"avg_install_s":9.4,"avg_import_s":0.77,"wheel_type":"wheel"},"url":"https://checklist.day/v1/registry/nvshmem4py-cu13/compatibility"},"provenance":{"verified_status":"install_fail","verified_at":"Sun Jun 28","last_verified":"Sun Jun 28","next_check":"Sun Jul 05","install_tag":null}}