clFFT is a software library containing FFT functions written in OpenCL. In addition to GPU devices, the library also supports running on CPU devices to facilitate debugging and heterogeneous programming.
Pre-built binaries are available here.
The FFT is an implementation of the Discrete Fourier Transform (DFT) that makes use of symmetries in the FFT definition to reduce the mathematical intensity required from O(N^2) to O(N log2(N)) when the sequence length N is the product of small prime factors. Currently, there is no standard API for FFT routines. Hardware vendors usually provide a set of high-performance FFTs optimized for their systems: no two vendors employ the same interfaces for their FFT routines. clFFT provides a set of FFT routines that are optimized for AMD graphics processors, but also are functional across CPU and other compute devices.
The clFFT library is an open source OpenCL library implementation of discrete Fast Fourier Transforms. The library:
provides a fast and accurate platform for calculating discrete FFTs.
works on CPU or GPU backends.
supports in-place or out-of-place transforms.
supports 1D, 2D, and 3D transforms with a batch size that can be greater than 1.
supports planar (real and complex components in separate arrays) and interleaved (real and complex components as a pair contiguous in memory) formats.
supports dimension lengths that can be any combination of powers of 2, 3, 5, 7, 11 and 13.
Supports single and double precision floating point formats.
Library and API documentation for developers is available online as a GitHub Pages website
Two mailing lists exist for the clMath projects:
clmath@googlegroups.com - group whose focus is to answer questions on using the library or reporting issues
clmath-developers@googlegroups.com - group whose focus is for developers interested in contributing to the library code
Good software is typically the result of the loop of feedback and iteration; software interfaces no less so. clFFT follows the semantic versioning guidelines. The version number used is of the form MAJOR.MINOR.PATCH.
The project wiki contains helpful documentation, including a build primer
Please refer to and read the Contributing document for guidelines on how to contribute code to this open source project. The code in the /master branch is considered to be stable, and all pull-requests must be made against the /develop branch.
The source for clFFT is licensed under the Apache License, Version 2.0
The following simple example shows how to use clFFT to compute a simple 1D forward transform
#include <stdlib.h>
/* No need to explicitely include the OpenCL headers */
#include <clFFT.h>
int main( void )
{
cl_int err;
cl_platform_id platform = 0;
cl_device_id device = 0;
cl_context_properties props[3] = { CL_CONTEXT_PLATFORM, 0, 0 };
cl_context ctx = 0;
cl_command_queue queue = 0;
cl_mem bufX;
float *X;
cl_event event = NULL;
int ret = 0;
size_t N = 16;
/* FFT library realted declarations */
clfftPlanHandle planHandle;
clfftDim dim = CLFFT_1D;
size_t clLengths[1] = {N};
/* Setup OpenCL environment. */
err = clGetPlatformIDs( 1, &platform, NULL );
err = clGetDeviceIDs( platform, CL_DEVICE_TYPE_GPU, 1, &device, NULL );
props[1] = (cl_context_properties)platform;
ctx = clCreateContext( props, 1, &device, NULL, NULL, &err );
queue = clCreateCommandQueue( ctx, device, 0, &err );
/* Setup clFFT. */
clfftSetupData fftSetup;
err = clfftInitSetupData(&fftSetup);
err = clfftSetup(&fftSetup);
/* Allocate host & initialize data. */
/* Only allocation shown for simplicity. */
X = (float *)malloc(N * 2 * sizeof(*X));
/* Prepare OpenCL memory objects and place data inside them. */
bufX = clCreateBuffer( ctx, CL_MEM_READ_WRITE, N * 2 * sizeof(*X), NULL, &err );
err = clEnqueueWriteBuffer( queue, bufX, CL_TRUE, 0,
N * 2 * sizeof( *X ), X, 0, NULL, NULL );
/* Create a default plan for a complex FFT. */
err = clfftCreateDefaultPlan(&planHandle, ctx, dim, clLengths);
/* Set plan parameters. */
err = clfftSetPlanPrecision(planHandle, CLFFT_SINGLE);
err = clfftSetLayout(planHandle, CLFFT_COMPLEX_INTERLEAVED, CLFFT_COMPLEX_INTERLEAVED);
err = clfftSetResultLocation(planHandle, CLFFT_INPLACE);
/* Bake the plan. */
err = clfftBakePlan(planHandle, 1, &queue, NULL, NULL);
/* Execute the plan. */
err = clfftEnqueueTransform(planHandle, CLFFT_FORWARD, 1, &queue, 0, NULL, NULL, &bufX, NULL, NULL);
/* Wait for calculations to be finished. */
err = clFinish(queue);
/* Fetch results of calculations. */
err = clEnqueueReadBuffer( queue, bufX, CL_TRUE, 0, N * 2 * sizeof( *X ), X, 0, NULL, NULL );
/* Release OpenCL memory objects. */
clReleaseMemObject( bufX );
free(X);
/* Release the plan. */
err = clfftDestroyPlan( &planHandle );
/* Release clFFT library. */
clfftTeardown( );
/* Release OpenCL working objects. */
clReleaseCommandQueue( queue );
clReleaseContext( ctx );
return ret;
}
To develop the clFFT library code on a Windows operating system, ensure to install the following packages on your system:
Windows® 7/8.1
Visual Studio 2012 or later
Latest CMake
An OpenCL SDK, such as APP SDK 3.0
To develop the clFFT library code on a Linux operating system, ensure to install the following packages on your system:
GCC 4.6 and onwards
Latest CMake
An OpenCL SDK, such as APP SDK 3.0
To develop the clFFT library code on a Mac OS X, it is recommended to generate Unix makefiles with cmake.
To test the developed clFFT library code, ensure to install the following packages on your system:
Googletest v1.6
Latest FFTW
Latest Boost
To measure the performance of the clFFT library code, ensure that the Python package is installed on your system.
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