Power-Aware Scheduling of Data-Flow Hardware Circuits with Symbolic Control

Abstract

We devise a tool-supported framework for achieving power-efficiency of data-flow hardware circuits. Our approach relies on formal control techniques, where the goal is to compute a strategy that can be used to drive a given model so that it satisfies a set of control objectives. More specifically, we give an algorithm that derives abstract behavioral models directly in a symbolic form from original designs described at Register-transfer Level using a Hardware Description Language, and for formulating suitable scheduling constraints and power-efficiency objectives. We show how a resulting strategy can be translated into a piece of synchronous circuit that, when paired with the original design, ensures the aforementioned objectives. We illustrate and validate our approach experimentally using various hardware designs and objectives.