{"id":21087,"library":"cupy-cuda11x","title":"CuPy for CUDA 11.x","description":"CuPy is a NumPy/SciPy-compatible array library for GPU-accelerated computing with CUDA 11.x. This package is specifically built for CUDA 11.x environments. Current version: 13.6.0. Release cadence: regular, matching the main CuPy release cycle.","status":"active","version":"13.6.0","language":"python","source_language":"en","source_url":"https://github.com/cupy/cupy","tags":["gpu","cuda","array","numpy","scientific-computing"],"install":[{"cmd":"pip install cupy-cuda11x","lang":"bash","label":"Install CuPy for CUDA 11.x"}],"dependencies":[{"reason":"Required for CuPy runtime","package":"fastrlock","optional":false}],"imports":[{"note":"Standard import for CuPy","symbol":"cupy","correct":"import cupy"},{"note":"CuPy extensions (scipy, sparse, etc.)","symbol":"cupyx","correct":"import cupyx"}],"quickstart":{"code":"import cupy as cp\nimport numpy as np\n\n# Create a GPU array\nx_gpu = cp.array([1, 2, 3, 4, 5])\nprint(x_gpu)\n\n# Perform operations on GPU\nprint(cp.sum(x_gpu))\n\n# Create a random matrix on GPU\nA = cp.random.randn(1000, 1000)\nprint(A.shape)\n\n# Verify CUDA and CuPy version\nprint(cp.__version__)\nprint(cp.cuda.runtime.runtimeGetVersion())","lang":"python","description":"Basic usage of CuPy on GPU with CUDA 11.x."},"warnings":[{"fix":"Upgrade CUDA to 11.4+ or use cupy-cuda11x version 12.x for older CUDA 11.x.","message":"CuPy v13 drops support for CUDA 11.0-11.3; only CUDA 11.4+ is supported. Ensure your CUDA version is 11.4 or higher.","severity":"breaking","affected_versions":">=13.0"},{"fix":"Ensure that the installed CUDA toolkit version matches the package: CUDA 11.4+ for cupy-cuda11x.","message":"Installing cupy-cuda11x on a system with mismatched CUDA runtime version may cause import errors or silent fallback to CPU. Check with `nvidia-smi` and `nvcc --version`.","severity":"gotcha","affected_versions":"all"},{"fix":"Use `with cp.cuda.Device(1):` to perform operations on a different GPU.","message":"CuPy arrays created on one GPU device cannot be directly accessed on another device. Use `cp.cuda.Device(n)` context manager to switch devices.","severity":"gotcha","affected_versions":"all"},{"fix":"Use `with cupy.cuda.Device(0):` syntax; it remains the same but is no longer considered experimental.","message":"The `cupy.cuda.Device` context management API is deprecated in favor of `cupy.cuda.Device.__enter__` and `__exit__`; use the `with` statement as usual.","severity":"deprecated","affected_versions":">=12.0"}],"env_vars":null,"last_verified":"2026-04-27T00:00:00.000Z","next_check":"2026-07-26T00:00:00.000Z","problems":[{"fix":"Install the correct CUDA toolkit version (11.4+) or use a cupy-cuda package matching your CUDA version (e.g., cupy-cuda12x).","cause":"The installed cupy-cuda11x package expects CUDA 11.x runtime, but the system has a different or missing CUDA installation.","error":"ImportError: libcudart.so.11.0: cannot open shared object file: No such file or directory"},{"fix":"Check GPU presence with `nvidia-smi`. Install appropriate NVIDIA drivers.","cause":"No NVIDIA GPU is available or the GPU driver is not properly installed.","error":"cupy.cuda.runtime.CUDARuntimeError: cudaErrorNoDevice: no CUDA-capable device is detected"},{"fix":"Install with `pip install cupy-cuda11x` and verify import with `import cupy`.","cause":"CuPy has not been installed or the wrong package (e.g., cupy-cuda11x vs cupy) was not installed.","error":"ModuleNotFoundError: No module named 'cupy'"}],"ecosystem":"pypi","meta_description":null,"install_score":null,"install_tag":null,"quickstart_score":null,"quickstart_tag":null}