Question 1

How do I set up VkFFT with the CUDA backend?

Accepted Answer

Include vkFFT.h and ensure NVRTC is available, then set VKFFT_BACKEND=1 in CMakeLists.txt. Build the benchmark by replacing the backend value and optionally enabling FFTW for comparisons, as detailed in the CUDA/HIP installation section.

Question 2

Is VkFFT more accurate than cuFFT?

Accepted Answer

Precision tests show VkFFT has logarithmic error scaling similar to cuFFT. With FP128 precomputation, it's more precise in double precision; in single precision, it's comparable but can be improved with FP64 precomputation, as seen in the precision comparison plots.

Question 3

Does VkFFT support multi-GPU FFT computations?

Accepted Answer

No, VkFFT currently lacks native multi-GPU support; it's planned as a future feature. For now, computations are limited to a single GPU per instance, which may restrict scalability for very large datasets.

Question 4

How to perform a convolution with VkFFT?

Accepted Answer

Configure the FFT setup for 1x1, 2x2, or 3x3 convolutions by specifying symmetric or nonsymmetric kernels in the VkFFT parameters. Use the native zero padding for open system modeling, as demonstrated in the sample applications like VkFFT_TestSuite.cpp.

Question 5

VkFFT or FFTW for my GPU project?

Accepted Answer

VkFFT is GPU-accelerated across multiple APIs, offering significant speedups for compatible hardware, while FFTW is CPU-based. Choose VkFFT for GPU workloads requiring cross-platform support, but opt for FFTW if CPU execution or simplicity is prioritized.

Question 6

Can I use VkFFT on Apple Silicon Macs?

Accepted Answer

Yes, VkFFT supports Metal backend for Apple GPUs, including those on Apple Silicon. Set VKFFT_BACKEND=5 and use metal-cpp bindings, as outlined in the Metal installation section for macOS compatibility.

VkFFT

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