文件名称：CUFFT_Library cuda fft变换 库文档
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更新时间：2016-07-25 06:09:42
CUFFT cuda fft fftw 库
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