{"categories":[{"label":"Software Development","url":"https://skillfed.io/packages/category/software-development/4"},{"label":"Libraries","url":"https://skillfed.io/packages/category/software-development-libraries/3"},{"label":"Scientific/Engineering","url":"https://skillfed.io/packages/category/scientific-engineering/2"},{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/2"},{"label":"Mathematics","url":"https://skillfed.io/packages/category/scientific-engineering-mathematics"}],"enrichment":{"capability":"Provides NVIDIA CUBLAS native runtime libraries for CUDA 11, enabling GPU-accelerated linear algebra operations in Python applications on x86_64 and ARM64 Linux, Windows platforms.","skillfed_tags":["cuda-runtime","gpu-computing","abandoned"],"use_cases":["Satisfy GPU linear algebra dependencies for PyTorch or TensorFlow installations targeting CUDA 11 environments.","Enable GPU-accelerated matrix operations in scientific computing workflows on x86_64 or ARM64 Linux systems.","Provide CUBLAS runtime binaries for Windows-based deep learning development without manual CUDA toolkit installation.","Support legacy projects locked to CUDA 11 that require explicit CUBLAS runtime availability."],"what_it_does":"nvidia-cublas-cu11 is a runtime library package that bundles NVIDIA's CUBLAS (CUDA Basic Linear Algebra Subroutines) native binaries for CUDA 11. It provides no Python API of its own; instead, it serves as a dependency for machine learning and scientific computing frameworks that need GPU-accelerated linear algebra operations. The package distributes precompiled binaries for Linux (x86_64 and ARM64) and Windows (x86_64), allowing downstream packages to locate and load the CUBLAS runtime at install time rather than requiring users to manually install CUDA.\n\nThe package is abandoned, with its last release over 1396 days ago and no active repository or maintenance. It carries an unclear proprietary license from NVIDIA. Users typically encounter this as a transitive dependency of PyTorch, TensorFlow, or similar frameworks rather than installing it directly. Because it is no longer maintained and CUDA tooling has evolved, new projects should evaluate whether to use this version or migrate to newer CUDA runtime packages.","worth_installing":"No for new projects. This package is abandoned (last release 1396 days ago) and carries an unclear proprietary license. Newer CUDA runtime packages and updated frameworks have superseded it. Install only if you are maintaining legacy code explicitly pinned to CUDA 11 and cannot upgrade; otherwise, use current nvidia-cublas packages or let your framework (PyTorch, TensorFlow) manage CUDA runtime dependencies."},"id":"nvidia-cublas-cu11","links":{"html":"https://skillfed.io/packages/nvidia-cublas-cu11","md":"https://skillfed.io/packages/nvidia-cublas-cu11.md","pypi":"https://pypi.org/project/nvidia-cublas-cu11/"},"maintenance":{"status":"abandoned"},"meta":{"latest_release":"2022-10-18","license_spdx":null,"license_treatment":"unclear","name":"nvidia-cublas-cu11","python_support":"supports_current","summary":"CUBLAS native runtime libraries"},"popularity":{"monthly_downloads":2584912,"position":2984,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"11.11.3.6"}