Energy-aware memory allocation in heterogeneous non-volatile memory systems

Memory systems consume a significant portion of power in hand-held embedded systems. So far, low-power memory techniques have addressed the power consumption when the system is turned on. In this paper, we consider data retention energy during the power-off period. For this purpose, we first characterize the data retention energy and cycle-accurate active mode energy of the nonvolatile memory systems. Next, we present energy-aware memory allocation for a given task set taking into account arrival rate, execution time, code size, user data size and the number of memory transactions by the use of trace-driven simulation. Experiments demonstrate that our optimal configuration can save up to 26% of the memory system energy compared with traditional allocation schemes.