Word-length optimization for high-level synthesis of digital signal processing systems

Abstract

Word-length optimization software is developed not only to reduce the hardware cost but also to minimize the optimization time. It inserts quantizers to a data flow graph representation, partitions the resultant graph, determines the minimum required word-length for each partitioned signal, conducts scheduling and binding using the minimum word-length information, and finally optimizes the word-lengths of functional units. Fixed-point simulation results are used as for the performance measure, thus this method can be applied to nonlinear and time-varying algorithms. Although this approach requires iterative fixed-point simulations, the search space is reduced significantly by grouping signals using the high-level synthesis, or hardware sharing, results. A fourth-order IIR filter, a fifth-order elliptic filter, and a 12th-order adaptive LMS filter are implemented using this software. The hardware cost of functional units is reduced by 25% in the IIR filter and 7% in the elliptic filter compared to the previous results.