3-dimensional Fast Fourier Transform (3D FFT) parallel computations are an important part of many scientific calculations. For example, 3D FFT is a critical component of molecular dynamics codes when they compute long range electrostatic computations. Parallel distributed 3D FFT computations involve redistributing intermediate data, which constitutes a substantial portion of overall execution time of these operations. There are two primary methods for handling this communication phase: explicitly packing and unpacking data, or using Message Passing Interface (MPI) derived datatypes. Derived datatypes have several advantages in that they are easy to work with and don’t require explicit memory pack and unpack operations. As such we propose enhancements for derived datatypes in MPI specifically for 3D FFT calculations which improves upon state of the art methods [8] by using MPI_Type_create_subarray to support arbitrary storage orders. Our method reduces the performance issues associated with MPI derived datatype solutions and benefits from avoiding strided-memory operations in FFT execution. Results show that we can speedup even strong scaled 3DFFT by 1.17X to 1.44X using our method over previous state of the art methods.