Library with 3D FFT-Based Convolution Support

Accelerated Computing GPU-Accelerated Libraries
1

Hi,

I’m working on an application in which 3D convolution is the bottleneck, and would like to get the best performance possible with preferably an existing library that supports 3D convolution.

I tried using cuDNN and got it to work, however, the user guide stated that FFT-based option (CUDNN_CONVOLUTION_FWD_ALGO_FFT) isn’t supported for 3D convolution. And since FFT is known as one of the fastest ways to compute convolution I was wondering if anyone has answers to any of the following questions:

  1. Is there an existing library with out-of-the-box 3D FFT-based convolution?
  2. Will there be a support for 3D FFT-based convolution in future releases of cuDNN?

Thanks a lot!

2

For future developers who find this question:

Working on the same issue with cuDNN v7.0.5 and CUDA 8.0 I found that the documentation now lists three algorithms supported for 3-D Convolution (page 80; cuDNN API reference; v7). The one with FFT support is CUDNN_CONVOLUTION_FWD_ALGO_FFT_TILING. CUDNN_CONVOLUTION_FWD_ALGO_FFT (without tiling) does not appear to support 3-D convolution as of cuDNN v7.

On a separate note, ArrayFire has a 3D convolution function which I believe uses a cuFFT backend routine which may be faster than cuDNN.