{"library":"nvidia-cufft-cu11","title":"NVIDIA cuFFT (CUDA 11 variant)","description":"The `nvidia-cufft-cu11` package provides the native runtime libraries for NVIDIA's GPU-accelerated Fast Fourier Transform (FFT) library, specifically compiled for CUDA 11.x environments. It enables high-performance FFT computations directly on NVIDIA GPUs for various scientific and engineering applications, including deep learning, computer vision, and computational physics. This package is a low-level dependency providing the C/C++ binaries, and is typically used in conjunction with Python binding libraries like CuPy or nvmath-python. The current version is 10.9.0.58, with a relatively slow release cadence for this specific CUDA 11 variant, as newer CUDA versions often have their own packages (e.g., `nvidia-cufft-cu12`).","language":"python","status":"active","last_verified":"Fri May 15","install":{"commands":["pip install nvidia-cufft-cu11"],"cli":null},"imports":["import cupy as cp\ncp.fft.fft(...)","from nvmath.fft import fft\nfft(...)"],"auth":{"required":false,"env_vars":[]},"quickstart":{"code":"import cupy as cp\nimport numpy as np\n\n# Ensure a CUDA-enabled GPU is available\nif not cp.cuda.is_available():\n    print(\"CUDA is not available. CuPy and cuFFT require a GPU.\")\n    exit()\n\n# Create a CuPy array on the GPU\nn = 1024\nx_gpu = cp.random.rand(n, dtype=cp.float32)\n\n# Perform a 1D FFT using CuPy (which uses cuFFT internally)\ny_gpu = cp.fft.fft(x_gpu)\n\n# Optionally, copy back to host and compare with NumPy\ny_cpu = cp.asnumpy(y_gpu)\nx_cpu = cp.asnumpy(x_gpu)\ny_numpy = np.fft.fft(x_cpu)\n\nprint(f\"Original GPU array type: {type(x_gpu)}\")\nprint(f\"FFT result GPU array type: {type(y_gpu)}\")\nprint(f\"First 5 elements of GPU FFT: {y_gpu[:5]}\")\nprint(f\"First 5 elements of NumPy FFT: {y_numpy[:5]}\")\nprint(f\"Max absolute difference between CuPy FFT and NumPy FFT: {cp.max(cp.abs(y_gpu - cp.asarray(y_numpy))):.6e}\")","lang":"python","description":"This quickstart demonstrates how to perform a 1D Fast Fourier Transform using `CuPy`, which internally leverages the `nvidia-cufft-cu11` native libraries. It creates a random array on the GPU, computes its FFT, and optionally compares the result with a NumPy FFT on the CPU. Ensure `cupy` is installed (`pip install cupy-cuda11x`).","tag":null,"tag_description":null,"last_tested":null,"results":[]},"compatibility":{"tag":null,"tag_description":null,"last_tested":"2026-05-15","installed_version":"10.9.0.58","pypi_latest":"10.9.0.58","is_stale":false,"summary":{"python_range":"3.10–3.9","success_rate":50,"avg_install_s":4.8,"avg_import_s":null,"wheel_type":"wheel"},"results":[{"runtime":"python:3.10-alpine","python_version":"3.10","os_libc":"alpine (musl)","variant":"nvidia-cufft-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-cufft-cu11","exit_code":0,"wheel_type":"wheel","failure_reason":null,"import_side_effects":"broken","install_time_s":4.5,"import_time_s":null,"mem_mb":null,"disk_size":"286M"},{"runtime":"python:3.11-alpine","python_version":"3.11","os_libc":"alpine (musl)","variant":"nvidia-cufft-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-cufft-cu11","exit_code":0,"wheel_type":"wheel","failure_reason":null,"import_side_effects":"broken","install_time_s":4.4,"import_time_s":null,"mem_mb":null,"disk_size":"288M"},{"runtime":"python:3.12-alpine","python_version":"3.12","os_libc":"alpine (musl)","variant":"nvidia-cufft-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-cufft-cu11","exit_code":0,"wheel_type":"wheel","failure_reason":null,"import_side_effects":"broken","install_time_s":5,"import_time_s":null,"mem_mb":null,"disk_size":"280M"},{"runtime":"python:3.13-alpine","python_version":"3.13","os_libc":"alpine (musl)","variant":"nvidia-cufft-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-cufft-cu11","exit_code":0,"wheel_type":"wheel","failure_reason":null,"import_side_effects":"broken","install_time_s":4.5,"import_time_s":null,"mem_mb":null,"disk_size":"280M"},{"runtime":"python:3.9-alpine","python_version":"3.9","os_libc":"alpine (musl)","variant":"nvidia-cufft-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-cufft-cu11","exit_code":0,"wheel_type":"wheel","failure_reason":null,"import_side_effects":"broken","install_time_s":5.5,"import_time_s":null,"mem_mb":null,"disk_size":"286M"}]}}