Abstract

Embedded systems are subject to timing and power constraints. To support both, software currently must integrate multiple tools, resulting in additional complexity. We address this problem with a unified, portable framework called Bard which uses control theory to meet the primary constraint and linear programming to optimize the other. We evaluate Bard on two embedded platforms that exhibit different performance and power/energy characteristics and show that it achieves less than 2% error in meeting power constraints while maintaining nearly 95% of optimal performance. Additionally, Bard supports changing the primary constraint type at runtime while still achieving similar results.

Date

July 17, 2016

Authors

Connor Imes, Henry Hoffmann

Conference

2016 International Conference on Embedded Computer Systems: Architectures, Modeling and Simulation (SAMOS)

Pages

31-38

Publisher

IEEE