Leakage power analysis and reduction during behavioral synthesis

This paper presents a high-level leakage power analysis and reduction algorithm. The algorithm uses device-level models for leakage to precharacterize a given register-transfer level module library. This is used to estimate the power consumption of a circuit due to leakage. The algorithm can also identify and extract the frequently idle modules in the datapath, which may be targeted for low-leakage optimization. Leakage optimization is based on the use of dual threshold voltage (V_T) technology. The algorithm prioritizes modules giving a high-level synthesis system an indication of where most gains for leakage reduction may be found. We tested our algorithm using a number of benchmarks from various sources. We ran a series of experiments by integrating our algorithm into a low-power high-level synthesis system. In addition to reducing the power consumption due to switching activity, our algorithm provides the high-level synthesis system with the ability to detect and reduce leakage power consumption, hence, further reducing total power consumption. This is shown over a number of technology generations. The trend in these generations indicates that leakage becomes the dominant component of power at smaller feature size and lower supply voltages. Results show that using a dual-V_T library during high-level synthesis can reduce leakage power by an average of 58% for the different technology generations. Total power can be reduced by an average of 15.0%-45.0% for 0.18-0.07 μm technologies, respectively. The contribution of leakage power to overall power consumption ranges from 22.6% to 56.2%. Our approach reduced these values to 11.7%-26.9%.