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This brief presents novel parallel pipelined architectures for the computation of the fast Fourier transform (FFT) of real signals and inverse FFT of Hermitian-symmetric signals using only real datapaths. The real FFT structure is transformed by transferring twiddle factors to subsequent stages, such that each stage in the proposed flow graph contains one column of butterfly units and one column of twiddle factor blocks, and each column of the flow graph contains only N samples. This is a key requirement for the design of architectures that are based on only real datapaths. This structure is then mapped to pipelined architectures. The proposed architectures can be used with any FFT size or level of parallelism, which is a power of two. A systematic method to design architectures for FFTs with different levels of parallelism and radix values is presented. By modifying the FFT flow graph for real-valued samples, this methodology leads to architectures with fewer adders, delays, and interconnections.