Kokkos-fft implements local interfaces between Kokkos and de facto standard FFT libraries, including fftw, cufft, hipfft (rocfft), and oneMKL. "Local" means not using MPI, or running within a single MPI process without knowing about MPI. We are inclined to implement the numpy.fft-like interfaces adapted for Kokkos. A key concept is that "As easy as numpy, as fast as vendor libraries". Accordingly, our API follows the API by numpy.fft with minor differences. A FFT library dedicated to Kokkos Device backend (e.g. cufft for CUDA backend) is automatically used.
Kokkos-fft is open source and available on GitHub.
Here is an example for 1D real to complex transform with rfft in Kokkos-fft.
#include <Kokkos_Core.hpp>
#include <Kokkos_Complex.hpp>
#include <Kokkos_Random.hpp>
#include <KokkosFFT.hpp>
using execution_space = Kokkos::DefaultExecutionSpace;
template <typename T> using View1D = Kokkos::View<T*, execution_space>;
constexpr int n = 4;
View1D<double> x("x", n);
View1D<Kokkos::complex<double> > x_hat("x_hat", n/2+1);
Kokkos::Random_XorShift64_Pool<> random_pool(12345);
Kokkos::fill_random(x, random_pool, 1);
Kokkos::fence();
KokkosFFT::rfft(execution_space(), x, x_hat);This is equivalent to the following python script.
import numpy as np
x = np.random.rand(4)
x_hat = np.fft.rfft(x)Note
It is assumed that backend FFT libraries are appropriately installed on the system.
getting_started finding_libraries api_reference examples