Charge-mode parallel architecture for matrix-vector multiplication

Abstract

An internally analog, externally digital architecture for matrix-vector multiplication is presented. Fully parallel processing allows for high data throughput and minimal latency. The analog architecture incorporates an array of charge-mode analog computational cells with dynamic storage and row-parallel flash analog-to-digital converters (ADC). Each of the cells includes a dynamic storage element and a charge injection device computing binary inner product of two arguments. The matrix elements are stored in the array of computational cells in bit-parallel fashion, and the input vector is presented bit-serially. Digital post-processing is then performed on the ADC outputs to construct the resulting product with precision higher than that of each conversion. The analog architecture is tailored for high-density and low power VLSI implementation, and matrix dimensions of 128/spl times/512 and ADC resolution of 6 bits for an overall resolution in excess of 8 bits are feasible on a 3 mm/spl times/3 mm chip in standard CMOS 0.5 /spl mu/m technology.