Energy-efficient datapath scheduling using multiple voltages and dynamic clocking

Abstract

Recently, dynamic frequency scaling has been explored at the CPU and system levels for power optimization. Low-power datapath scheduling using multiple supply voltages has been well researched. In this work, we develop new datapath scheduling algorithms that use multiple supply voltages and dynamic frequency clocking in a coordinated manner in order to reduce the energy consumption of datapath circuits. In dynamic frequency clocking, the functional units can be operated at different frequencies depending on the computations occurring within the datapath during a given clock cycle. The strategy is to schedule high-energy units, such as multipliers at lower frequencies, so that they can be operated at lower voltages to reduce energy consumption and the low-energy units, such as adders at higher frequencies, to compensate for speed. The proposed time- and resource-constrained algorithms have been applied to various high-level synthesis benchmark circuits under different time and resource constraints. The experimental results show significant reduction in energy for both the algorithms.