Approximate computing of two-variable numeric functions using multiplier-less gradients

Approximate computing of non-trivial numeric functions is a well-known design technique and, therefore, used in several different application areas. Its main idea is the relaxation of conventional correctness constraints to achieve high performance results in terms of throughput and/or energy consumption. In this paper we propose an automated approximate design method for the fast hardware generation of two-dimensional numeric functions. By using multiplier-less gradients in combination with an advanced non-uniform segmentation scheme, high hardware performance is achieved. To qualify our approach, exhaustive evaluation is carried out, considering six different two-variable numeric functions. In a first step, a global complexity estimation is performed with varying design constraints on the algorithmic level. Out of this, most suitable candidates are selected for logic and physical CMOS synthesis. The results are compared to actual references highlighting our work as a powerful approach for the hardware-based calculation of two-variable numeric functions, especially in terms of throughput and energy consumption.