Optimum Wordlength Search Using Sensitivity Information

Many digital signal processing algorithms are first developed in floating point and later converted into fixed point for digital hardware implementation. During this conversion, more than 50% of the design time may be spent for complex designs, and optimum wordlengths are searched by trading off hardware complexity for arithmetic precision at system outputs. We propose a fast algorithm for searching for an optimum wordlength. This algorithm uses sensitivity information of hardware complexity and system output error with respect to the signal wordlengths, while other approaches use only one of the two sensitivities. This paper presents various optimization methods, and compares sensitivity search methods. Wordlength design case studies for a wireless demodulator show that the proposed method can find an optimum solution in one fourth of the time that the local search method takes. In addition, the optimum wordlength searched by the proposed method yields 30% lower hardware implementation costs than the sequential searchmethod in wireless demodulators. Case studies demonstrate the proposedmethod is robust for searching for the optimum wordlength in a nonconvex space.