{"library":"nvidia-curand-cu11","title":"NVIDIA CURAND for CUDA 11","description":"The `nvidia-curand-cu11` package provides the native runtime libraries for NVIDIA's CUDA Random Number Generation (CURAND) library, specifically compiled for CUDA 11 environments. CURAND delivers high-performance GPU-accelerated random number generation, offering various algorithms and distribution options for scientific computing, machine learning, and deep learning applications. This package acts as a low-level dependency for higher-level Python libraries that utilize GPU-accelerated random number generation. The current version is 10.3.0.86, with releases typically having a slow cadence.","language":"python","status":"active","last_verified":"Fri May 15","install":{"commands":["pip install nvidia-curand-cu11"],"cli":null},"imports":["Functionality accessed via libraries like CuPy, Numba, or PyTorch."],"auth":{"required":false,"env_vars":[]},"quickstart":{"code":"# This package provides runtime libraries; direct import is not applicable.\n# Instead, CURAND's functionality (GPU random numbers) is typically accessed via other Python libraries.\n# Here's an example using CuPy, which implicitly uses CURAND:\n\ntry:\n    import cupy as cp\n    import numpy as np\n\n    # Initialize a GPU random number generator\n    rng = cp.random.default_rng()\n\n    # Generate 5 random floats on the GPU\n    gpu_random_numbers = rng.random(5)\n    print(f\"GPU Random Numbers (CuPy): {gpu_random_numbers}\")\n\n    # Transfer to CPU for verification (optional)\n    cpu_array = gpu_random_numbers.get()\n    print(f\"CPU Array (NumPy from CuPy): {cpu_array}\")\n\nexcept ImportError:\n    print(\"CuPy not installed. Install with: pip install cupy-cuda11x\")\nexcept Exception as e:\n    print(f\"An error occurred: {e}\")\n    print(\"Ensure you have a compatible NVIDIA GPU, CUDA 11 toolkit, and appropriate drivers installed.\")","lang":"python","description":"Since `nvidia-curand-cu11` is a runtime library, it doesn't have a direct Python quickstart. Instead, you would use a Python library like CuPy (shown below) or PyTorch, which leverage the underlying CURAND functionalities for GPU-accelerated random number generation. This example demonstrates generating random numbers directly on the GPU using CuPy's random number generator, which is built upon CURAND.","tag":null,"tag_description":null,"last_tested":null,"results":[]},"compatibility":{"tag":null,"tag_description":null,"last_tested":"2026-05-15","installed_version":"10.3.0.86","pypi_latest":"10.3.0.86","is_stale":false,"summary":{"python_range":"3.10–3.9","success_rate":50,"avg_install_s":2.4,"avg_import_s":null,"wheel_type":"wheel"},"results":[{"runtime":"python:3.10-alpine","python_version":"3.10","os_libc":"alpine (musl)","variant":"nvidia-curand-cu11","exit_code":1,"wheel_type":null,"failure_reason":"build_error","import_side_effects":null,"install_time_s":null,"import_time_s":null,"mem_mb":null,"disk_size":null},{"runtime":"python:3.10-slim","python_version":"3.10","os_libc":"slim (glibc)","variant":"nvidia-curand-cu11","exit_code":0,"wheel_type":"wheel","failure_reason":null,"import_side_effects":"broken","install_time_s":2.2,"import_time_s":null,"mem_mb":null,"disk_size":"117M"},{"runtime":"python:3.11-alpine","python_version":"3.11","os_libc":"alpine (musl)","variant":"nvidia-curand-cu11","exit_code":1,"wheel_type":null,"failure_reason":"build_error","import_side_effects":null,"install_time_s":null,"import_time_s":null,"mem_mb":null,"disk_size":null},{"runtime":"python:3.11-slim","python_version":"3.11","os_libc":"slim (glibc)","variant":"nvidia-curand-cu11","exit_code":0,"wheel_type":"wheel","failure_reason":null,"import_side_effects":"broken","install_time_s":2.4,"import_time_s":null,"mem_mb":null,"disk_size":"119M"},{"runtime":"python:3.12-alpine","python_version":"3.12","os_libc":"alpine (musl)","variant":"nvidia-curand-cu11","exit_code":1,"wheel_type":null,"failure_reason":"build_error","import_side_effects":null,"install_time_s":null,"import_time_s":null,"mem_mb":null,"disk_size":null},{"runtime":"python:3.12-slim","python_version":"3.12","os_libc":"slim (glibc)","variant":"nvidia-curand-cu11","exit_code":0,"wheel_type":"wheel","failure_reason":null,"import_side_effects":"broken","install_time_s":2.3,"import_time_s":null,"mem_mb":null,"disk_size":"111M"},{"runtime":"python:3.13-alpine","python_version":"3.13","os_libc":"alpine (musl)","variant":"nvidia-curand-cu11","exit_code":1,"wheel_type":null,"failure_reason":"build_error","import_side_effects":null,"install_time_s":null,"import_time_s":null,"mem_mb":null,"disk_size":null},{"runtime":"python:3.13-slim","python_version":"3.13","os_libc":"slim (glibc)","variant":"nvidia-curand-cu11","exit_code":0,"wheel_type":"wheel","failure_reason":null,"import_side_effects":"broken","install_time_s":2.1,"import_time_s":null,"mem_mb":null,"disk_size":"110M"},{"runtime":"python:3.9-alpine","python_version":"3.9","os_libc":"alpine (musl)","variant":"nvidia-curand-cu11","exit_code":1,"wheel_type":null,"failure_reason":"build_error","import_side_effects":null,"install_time_s":null,"import_time_s":null,"mem_mb":null,"disk_size":null},{"runtime":"python:3.9-slim","python_version":"3.9","os_libc":"slim (glibc)","variant":"nvidia-curand-cu11","exit_code":0,"wheel_type":"wheel","failure_reason":null,"import_side_effects":"broken","install_time_s":3,"import_time_s":null,"mem_mb":null,"disk_size":"117M"}]}}