Abstract: The proposed hardware architecture is integrated onto a Digital Signal Processor (DSP) as a coprocessor to assist in the computation of sum of absolute differences, symmetrical row/column Finite Impulse Response (FIR) filtering with a downsampling (or upsampling) option, row/column Discrete Cosine Transform (DCT)/Inverse Discrete Cosine Transform (IDCT), and generic algebraic functions. The architecture is called IPP, which stands for image processing peripheral, and consists of 8 hardware multiply-accumulate units connected in parallel and routed and multiplexed together. The architecture can be dependent upon a Direct Memory Access (DMA) controller to retrieve and write back data from/to DSP memory without intervention from the DSP core. The DSP can set up the DMA transfer and IPP/DMA synchronization in advance, then go on its own processing task. Alternatively, the DSP can perform the data transfers and synchronization itself by synchronizing with the IPP architecture on these transfers.

Abstract: The proposed architecture is integrated onto a Digital Signal Processor (DSP) as a coprocessor to assist in the computation of sum of absolute differences, symmetrical row/column Finite Impulse Response (FIR) filtering with a downsampling (or upsampling) option, row/column Discrete Cosine Transform (DCT)/Inverse Discrete Cosine Transform (IDCT), and generic algebraic functions. The architecture is called IPP, which stands for image processing peripheral, and consists of 8 multiply-accumulate hardware units connected in parallel and routed and multiplexed together. The architecture can be dependent upon a Direct Memory Access (DMA) controller to retrieve and write back data from/to DSP memory without intervention from the DSP core. The DSP can set up the DMA transfer and IPP/DMA synchronization in advance, then go on its own processing task. Alternatively, the DSP can perform the data transfers and synchronization itself by synchronizing with the IPP architecture on these transfers.