Module assignment for low power

We investigate the problem of minimizing the total power consumption during the binding of operations to functional units in a scheduled data path with functional pipelining and conditional branching for data intensive applications. We first present a technique to estimate the power consumption in a functionally pipelined data path and then formulate the power optimization problem as a max cost multi commodity flow problem and solve it optimally. Our proposed method can augment most high level synthesis algorithms as a post processing step for reducing power after the optimizations for area or speed have been completed. An average power savings of 28% has been observed after we apply our method to pipelined designs that have been optimized using conventional techniques