All example, including more advanced onces, are shipped within cuFFTDx package.
This folder demonstrates cuFFTDx APIs usage.
- cuFFTDx/MathDx package
- See cuFFTDx requirements
- CMake 3.18 or newer
- Linux system with installed NVIDIA drivers
- NVIDIA GPU of Volta (SM70) or newer architecture
- You may specify
CUFFTDX_CUDA_ARCHITECTURESto limit CUDA architectures used for compilation (see CMake:CUDA_ARCHITECTURES) mathdx_ROOT- path to mathDx package (XX.Y - version of the package)
mkdir build && cd build
cmake -DCUFFTDX_CUDA_ARCHITECTURES=70-real -Dmathdx_ROOT=/opt/nvidia/mathdx/XX.Y ..
make
// Run
ctest
For the detailed descriptions of the examples please visit Examples section of the cuFFTDx documentation.
| Group | Subgroup | Example | Description |
|---|---|---|---|
| Introduction Examples | introduction_example | cuFFTDx API introduction | |
| Simple FFT Examples | Thread FFT Examples | simple_fft_thread | Complex to complex thread FFT |
| simple_fft_thread_fp16 | Complex to complex thread FFT half precision | ||
| Block FFT Examples | simple_fft_block | Complex to complex block FFT | |
| simple_fft_block_r2c | Real to complex block FFT | ||
| simple_fft_block_c2r | Complex to real block FFT | ||
| simple_fft_block_half2 | Complex to complex block FFT with __half2 as data type |
||
| simple_fft_block_fp16 | Complex to complex block FFT half precision | ||
| simple_fft_block_r2c_fp16 | Real to complex block FFT half precision | ||
| simple_fft_block_c2r_fp16 | Complex to real block FFT half precision | ||
| Extra Block FFT Examples | simple_fft_block_shared | Complex to complex block FFT shared memory API | |
| simple_fft_block_std_complex | Complex to complex block FFT with cuda::std::complex as data type |
||
| simple_fft_block_cub_io | Complex to complex block FFT with CUB used for loading/storing data |
||
| NVRTC Examples | nvrtc_fft_thread | Complex to complex thread FFT | |
| nvrtc_fft_block | Complex to complex block FFT | ||
| FFT Performance | block_fft_performance | Benchmark for C2C block FFT | |
| block_fft_performance_many | Benchmark for C2C/R2C/C2R block FFT | ||
| Convolution Examples | convolution | Simplified FFT convolution | |
| convolution_r2c_c2r | Simplified R2C C2R FFT convolution | ||
| convolution_padded | R2C C2R FFT convolution with optimization and zero padding | ||
| convolution_performance | Benchmark for FFT convolution using cuFFTDx and cuFFT | ||
| conv_3d/convolution_3d | cuFFTDx fused 3D convolution with preprocessing, filtering and postprocessing | ||
| conv_3d/convolution_3d_r2c | cuFFTDx fused 3D R2C/C2R FFT convolution | ||
| conv_3d/convolution_3d_c2r | cuFFTDx fused 3D C2R/R2C FFT convolution | ||
| conv_3d/convolution_3d_padded | cuFFTDx fused 3D FFT convolution using zero padding | ||
| conv_3d/convolution_3d_padded_r2c | uFFTDx fused 3D R2C/C2R FFT convolution with zero padding | ||
| 2D/3D FFT Advanced Examples | fft_2d | Example showing how to perform 2D FP32 C2C FFT with cuFFTDx | |
| fft_2d_r2c_c2r | Example showing how to perform 2D FP32 R2C/C2R convolution with cuFFTDx | ||
| fft_2d_single_kernel | 2D FP32 FFT in a single kernel using Cooperative Groups kernel launch | ||
| fft_3d_box_single_block | Small 3D FP32 FFT that fits into a single block, each dimension is different | ||
| fft_3d_cube_single_block | Small 3D (equal dimensions) FP32 FFT that fits into a single block | ||
| fft_3d | Example showing how to perform 3D FP32 C2C FFT with cuFFTDx | ||
| Mixed Precision Examples | mixed_precision_fft_1d | Example showing how to use separate storage and compute precisions | |
| mixed_precision_fft_2d | Mixed precision 2D FFT with benchmarking and accuracy comparison | ||