The thing that stuck out to me is the assertion that FFT is poorly supported on modern GPU. That's surprising to me, as there's cuFFT offically supported by Nvidia, and vkFFT that achieves similar performance portably using compute shaders. I believe these are based on f32 math, so perhaps the potential win is using tensor cores to compute FFT at lower precision? It seems surprising to me that decomposing into matrix operations is the win here, it seems you'd do better writing a kernel that makes use of the cooperative matrix (aka WMMA, tensor core, simd_matrix) capabilities of the GPU.