objects solutions and advantages of the present disclosure become more apparent in parallel fft computation a computation module reads data and respective twiddle factors for multiple butterfly units from a multi granularity parallel memory performs a plurality of multi stage butterfly computations in parallel and then writes computation results in parallel into the memory for use in the next stage as shown in fig3 here assuming that the data length is 64 and parallel granularity is 4 that is the multi granularity parallel memory 305 support reading writing 4 pieces of data each time meanwhile 4 data dependent butterfly units 303 in two adjacent stages form a butterfly group 302 and the butterfly groups in the two adjacent stages form a computation node 301 the butterfly computation module reads data points and twiddle factors required for one butterfly group in parallel from the memory 305 and writes computation results in parallel into the memory 305 after completing the computation of the butterfly group in the butterfly group 302 the input a b and w to each butterfly unit must satisfy the internal correspondence therefore in the parallel fft computation consideration must be made as to the distribution of data and twiddle factors in the memory and read write r w addresses and r w schemes for each butterfly group 302 in order to guarantee that the butterfly computation module can always read desired data and twiddle factors in parallel for the parallel fft read write and computation definitions are first given as follows parallel granularity 2 l l is a positive integer parallel granularity refers to the number of data which can be read in parallel from a buffer and used independently in.