A fast inner product processor based on equal alignments

Abstract

Inner product computation is an important operation, invoked repeatedly in matrix multiplications. A high-speed inner product processor can be very useful (among many possible applications) in real-time signal processing. This paper presents the design of a fast inner product processor, with appreciably reduced latency and cost. The inner product processor is implemented with a tree of carry-propagate or carry-save adders; this structure is obtained with the incorporation of three innovations in the conventional multiply/add tree: (1) The leaf-multipliers are expanded into adder subtrees, thus achieving an O(log Nb) latency, where N denotes the number of elements in a vector and b the number of bits in each element. (2) The partial products, to be summed in producing an inner product, are reordered according to their “minimum alignments.” This reordering brings approximately a 20% saving in hardware—including adders and data paths. The reduction in adder widths also yields savings in carry propagation time for carry-propagate adders. (3) For trees implemented with carry-save adders, the partial product reordering also serves to truncate the carry propagation chain in the final propagation stage by 2 log b − 1 positions, thus significantly reducing the latency further. A form of the Baugh and Wooley algorithm is adopted to implement two's complement notation with changes only in peripheral hardware.