Hardware approximate computing: how, why, when and where? (special session)

Abstract

Approximate computing in hardware is generally aimed at power or energy optimization as the primary target. We suggest that hardware approximate computing can be more beneficial when area reduction is the primary target. Additionally, we advocate that the hardware approximation schemes which allow usage of high-level libraries for their sub-components can leverage the power offered by modern synthesis tools. We demonstrate using experimental results that such approximations therefore achieve more efficient synthesis than the deeply hierarchical approximations.