cupyfft

CuPy FFT is a Python library that provides a Fast Fourier Transform (FFT) implementation that runs on NVIDIA GPUs using the CUDA platform. It is part of the CuPy ecosystem, which aims to provide a NumPy-like interface for GPU-accelerated array computations. CuPy FFT leverages the highly optimized cuFFT library provided by NVIDIA.

The primary benefit of using CuPy FFT over CPU-based FFT implementations like NumPy's FFT is its significant speedup for large datasets. By offloading the computation to the GPU, CuPy FFT can achieve orders of magnitude faster performance. This makes it particularly useful for scientific computing, signal processing, image processing, and machine learning applications where FFTs are frequently used.

CuPy FFT offers a similar API to NumPy's FFT module, making it easy for users familiar with NumPy to transition to GPU acceleration. Common functions like `fft`, `ifft`, `rfft`, and `irfft` are available, supporting various dimensions and data types. Users can seamlessly integrate CuPy arrays into their existing NumPy workflows by converting them to CuPy arrays before performing FFT operations and then converting the results back if needed.

To use CuPy FFT, users need to have a compatible NVIDIA GPU and the CUDA toolkit installed. CuPy itself can be installed using pip. Once installed, importing and using the `cupy.fft` module is straightforward, allowing for direct GPU computation of FFTs without extensive code modifications.