The NVIDIA CUDA Fast Fourier Transform library (cuFFT) provides a simple interface for computing FFTs up to 10x faster. By using hundreds of processor cores inside NVIDIA GPUs, cuFFT delivers the floating‐point performance of a GPU without having to develop your own custom GPU FFT implementation.
Widely used in applications ranging from computational physics to image processing and general signal processing, the Fast Fourier Transform is an efficient algorithm for computing discrete Fourier transforms of complex or real‐valued data sets. cuFFT uses algorithms based on the well-known Cooley-Tukey and Bluestein algorithms, so you can be confident that you’re getting accurate results faster than ever.
Review the latest CUDA 6.5 performance report to learn how much you could accelerate your code.
Source Code Example
3D Complex-to-Complex Transforms
#define NX 64
/* Transform the first signal in place. */
/* Transform the second signal using the same plan. */
/* Destroy the cuFFT plan. */
The cuFFT library is freely available as part of the CUDA Toolkit.
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