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The power consumed by the memory hierarchy of a microprocessor can contribute to as much as 50% of the total microprocessor system power, and is thus a good candidate for optimizations. We present an automated method for tuning two-level caches to embedded applications for reduced energy consumption. The method is applicable to both a simulation-based exploration environment and a hardware-based system prototyping environment. We introduce the two-level cache tuner, or TCaT - a heuristic for searching the huge solution space of possible configurations. The heuristic interlaces the exploration of the two cache levels and searches the various cache parameters in a specific order based on their impact on energy. We show the integrity of our heuristic across multiple memory configurations and even in the presence of hardware/software partitioning - a common optimization capable of achieving significant speedups and/or reduced energy consumption. We apply our exploration heuristic to a large set of embedded applications. Our experiments demonstrate the efficacy of our heuristic: on average the heuristic examines only 7% of the possible cache configurations, but results in cache sub-system energy savings of 53%, only 1% more than the optimal cache configuration. In addition, the configured cache achieves an average speedup of 30% over the base cache configuration due to tuning of cache line size to the application's needs.