In this section, we collect a few tips on getting the best performance out of FFTW’s MPI transforms.
First, because of the 1d block distribution, FFTW’s parallelization is currently limited by the size of the first dimension. (Multidimensional block distributions may be supported by a future version.) More generally, you should ideally arrange the dimensions so that FFTW can divide them equally among the processes. See Load balancing.
Second, if it is not too inconvenient, you should consider working with transposed output for multidimensional plans, as this saves a considerable amount of communications. See Transposed distributions.
Third, the fastest choices are generally either an in-place transform
or an out-of-place transform with the
(which allows the input array to be used as scratch space). In-place
is especially beneficial if the amount of data per process is large.
Fourth, if you have multiple arrays to transform at once, rather than calling FFTW’s MPI transforms several times it usually seems to be faster to interleave the data and use the advanced interface. (This groups the communications together instead of requiring separate messages for each transform.)