GPU FFT and simple profiler

[srcejon]

This PR adds support for running FFT on GPU using the VkFFT library, with either Vulkan or CUDA backend, as per #1166

To allow easier performance comparisons, I have updated the FFTEngine and FFTFactory class to support multiple simultaneous FFTEngines, so a user can switch between FFTW, Kiss and VkFFT at run-time via a GUI option (Preferences > FFT). Also, different bits of SDRangel can request different FFTEngines. So FFTW could be used generally, but a specific plugin could request VkFFT if it thinks it will benefit from it.

I have also added a simple profiler, that displays average execution time in a dialog (View > Profile Data...). Profiling is enabled via the cmake -DENABLE_PROFILER=ON option. It is disabled by default, and when disabled, there should be no performance impact as the profiling code is not included in the executable. It can also be used to easily profile other parts of SDRangel - here showing GL spectrum draw time, as well as FFT. To profille some code, you just need to stick the PROFILE_START() and PROFILE_STOP("name") macros around the code.

Whether VkFFT uses Vulkan or CUDA is a cmake option, -DVKFFT_BACKEND=0 for Vulkan and -DVKFFT_BACKEND=1 for CUDA. The code should compile without VkFFT if neither the Vulkan or CUDA SDKs are available.

On Windows, VkFFT is automatically downloaded as an external project. If external project is off, then it can be downloaded with:

cd /opt/build
git clone https://github.com/DTolm/VkFFT.git
cd VkFFT
git checkout v1.3.1

It's a header only library, so doesn't need to be built.

Either the Vulkan or CUDA SDKs need to be installed to compile it:

Linux Vulkan Setup

cd /opt/install
mkdir -p vulkansdk
cd vulkansdk
wget https://vulkan.lunarg.com/sdk/download/1.3.250.1/linux/vulkansdk-linux-x86_64-1.3.250.1.tar.gz
tar xf vulkansdk-linux-x86_64-1.3.250.1.tar.gz
source /opt/install/vulkansdk/1.3.250.1/setup-env.sh
...
cmake -DVKFFT_INCLUDE_DIR=/opt/build/VkFFT/vkFFT/ -DVKFFT_BACKEND=0 ..

Linux CUDA setup

Install CUDA toolkit from https://developer.nvidia.com/cuda-downloads
export PATH=/usr/local/cuda/bin:%PATH
...
cmake -DVKFFT_INCLUDE_DIR=/opt/build/VkFFT/vkFFT/ -DVKFFT_BACKEND=1 ..

Windows Vulkan Setup

Install Vulkan SDK (With optional 64-bit Debug libraries) from https://vulkan.lunarg.com/sdk/home#windows
Copy include\glslang\Include\glslang_c_interface. and include\glslang\Include\glslang_c_shader_types.h from Linux SDK as they are missing (See https://vulkan.lunarg.com/issue/view/63d158a85df11200d569b2ab)
set VULKAN_SDK=C:\VulkanSDK\1.3.250.1  (or where ever you installed it)
cmake -DVKFFT_BACKEND=0 ..

Windows CUDA Setup

Install CUDA toolkit from https://developer.nvidia.com/cuda-downloads (This creates CUDA_PATH environment variable)
cmake -DVKFFT_BACKEND=1 ..

Unfortunately, on my PCs, using the GPU (via either Vulkan or CUDA) is much slower than using FFTW, due to the overhead of getting the data from the CPU to the GPU. It may be more beneficial on embedded SoCs that have unified memory and relatively slower CPUs, but haven't tried. To get better performance, we'd probably need to submit FFTs in batches, rather than one at a time (or do additional processing on the GPU). So there's no reason to try to enable this in the release builds now, but it's the first step towards GPU support.

[f4exb]

To get better performance, we'd probably need to submit FFTs in batches, rather than one at a time (or do additional processing on the GPU)

The problem in this case is that the rendering will probably be sketchy. It may be more beneficial to processes using FFT heavily in the background.

[RobRich999]

Just rolled an updated local build. I will probably look into profiling actual performance later, but for now according to mesa debugging info, VkFFT Vulkan under SDRangel appears to be working okay on my Kubuntu 23.04 system with AMDPU and RADV.

AMD 5700u processor here, so AMD Vega GPU with 8 CUs.

Thanks to the project devs for the feature and support. :)

[savagesmc]

Thank you for adding this feature!

[srcejon]

I wouldn't get too excited - it seems to be much slower than using the CPU!