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资源说明：This document describes CUFFT, the NVIDIA® CUDA™
Fast Fourier Transform (FFT)
library. The FFT is a divide-and-conquer algorithm for efficiently computing discrete
Fourier transforms of complex or real-valued data sets. It is one of the most important and
widely used numerical algorithms in computational physics and general signal processing.
The CUFFT library provides a simple interface for computing parallel FFTs on an
NVIDIA GPU, which allows users to leverage the floating-point power and parallelism of
the GPU without having to develop a custom, CUDA FFT implementation.
FFT libraries typically vary in terms of supported transform sizes and data types. For
example, some libraries only implement radix-2 FFTs, restricting the transform size to a
power of two. The CUFFT Library aims to support a wide range of FFT options efficiently
on NVIDIA GPUs. This version of the CUFFT library supports the following features:
I Complex and real-valued input and output
I 1D, 2D, and 3D transforms
I Batch execution for doing multiple transforms of any dimension in parallel
I Transform sizes up to 64 million elements in single precision and up to 128 million
elements in double precision in any dimension, limited by the available GPU memory
I In-place and out-of-place transforms
I Double-precision (64-bit floating point) on compatible hardware (sm1.3 and later)
I Support for streamed execution, enabling asynchronous computation and data
movement
I FFTW compatible data layouts
I Arbitrary intra- and inter-dimension element strides
I Thread-safe API that can be called from multiple independent host threads
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