A dynamic-programming algorithm for reducing the energy consumption of pipelined System-Level streaming applications

In this paper we present a System-Level technique for reducing energy consumption. The technique is applicable to pipelined applications represented as chain-structured graphs and targets the energy overhead of switching between active and sleep mode. The overhead is reduced by increasing the number of consecutive executions of the pipeline stages. The technique has no impact on the average throughput. We derive upper bounds on the number of consecutive executions and present a dynamic-programming algorithm that finds the optimal solution using these bounds. For specific cases we derive a quality metric that can be used to trade quality of the result for running-time.