Partitioning and Allocation of Scratch-Pad Memory in Priority-Based Multi-Task Systems

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Energy consumption has become one of the major concerns in modern embedded systems. Recently memory subsystems have become consumed large amount of total energy in the embedded processors. This paper proposes partitioning and allocation approaches of scratch-pad memory in non-preemptive fixed-priority multi-task systems. We propose three approaches (i.e., spatial, temporal, and hybrid approaches) which enable energy efficient usage of the scratch-pad region. These approaches can reduce energy consumption of instruction memory. Each approach is formulated as an integer programming problem that simultaneously determines (1) partitioning of the scratch-pad memory space for the tasks, and (2) allocation of functions to the scratch-pad memory space for each task. Our formulations pay attention to the task periods for the purpose of energy minimization. The experimental results show up to 47% of energy reduction in the instruction memory subsystems can be achieved by the proposed approaches.