Exact and Heuristic Approaches to Input Vector Control for Leakage Power Reduction

Abstract

Leakage power consumption is an increasingly serious problem in very large-scale integration circuits, especially for portable applications. Two novel approaches to leakage power minimization in static complementary metal-oxide-semiconductor circuits that employ input vector control (IVC) are investigated. The authors model leakage effects by means of pseudo-Boolean functions. These functions are linearized and incorporated into an exact (optimal) integer linear programming (ILP) model, called virtual-gate ILP, which analyzes leakage variation with respect to a circuit's input vectors. A heuristic mixed-integer linear programming (MLP) method is also proposed, which has several advantages: it is faster, its accuracy can be quickly estimated, and tradeoffs between runtime and optimality can easily be made. Furthermore, the MLP model also provides a way to estimate a lower bound on circuit leakage current. The proposed methods are used to generate an extensive set of experimental results on leakage reduction. It is shown that average leakage currents are usually 1.25 times the minimum, confirming the effectiveness of IVC. The heuristic MLP approach is shown to be approximately 13.6 times faster than the exact ILP method, whereas finding input vectors whose power consumption is only a few percent above the optimum. In addition, the lower bound estimated by the MLP model is also within a few percent of the optimal value