This work introduces a new idea of batched 3D-FFT with a survey of data decomposition methods and a review of the states-of-arts high performance parallel FFT libraries. Besides, it is argued that the particular usage of multiple FFTs has been associated with the batched execution. The batched 3D-FFT kernel, which is performed on the K computer, shows 45.9% speedup when N and P are 20483 and 128, respectively. The batched FFT allows the developer to take advantage of a flexible internal data layout and scheduling to improve the total performance.
