SCHEMATIC:间歇系统的编译时检查点放置和内存分配

Hugo Reymond, Jean-Luc Béchennec, M. Briday, Sébastien Faucou, Isabelle Puaut, Erven Rohou
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引用次数: 0

摘要

无电池设备能够在难以接近的地方进行传感,为医疗保健、太空或土木工程等各个领域带来了新的机遇。此类设备可收集环境能量并将其储存在电容器中。由于采集能量的不可预测性,断电可能随时发生,导致所有非持久性信息(如处理器寄存器、存储在易失性存储器中的数据)丢失。在非易失性存储器中对易失性数据进行检查点处理可使系统在断电后恢复,但会产生两个问题:(i) 检查点在空间和时间上的位置;(ii) 易失性存储器和非易失性存储器之间变量的存储器分配,总体目标是尽可能高效地使用能源。许多技术都依赖于开发人员来解决这些问题,而我们提出的 Schematic 是一种编译器技术,它能自动进行检查点放置和内存分配,从而最大限度地降低总体能耗。Schematic 可确保程序最终终止(前向进程属性)。此外,检查点放置和内存分配还能适应能量缓冲区的大小和易失性内存的容量。Schematic 利用易失性内存(VM)的优势,通过自动将最常用的变量放入易失性内存来降低能耗。我们针对不同的实验设置(易失性内存和电容器的大小)对 Schematic 进行了测试,结果表明,与相关技术相比,平均能耗降低了 51%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
SCHEMATIC: Compile-Time Checkpoint Placement and Memory Allocation for Intermittent Systems
Battery-free devices enable sensing in hard-to-access locations, opening up new opportunities in various fields such as healthcare, space, or civil engineering. Such devices harvest ambient energy and store it in a capacitor. Due to the unpredictable nature of the harvested energy, a power failure can occur at any time, resulting in a loss of all non-persistent information (e.g., processor registers, data stored in volatile memory). Checkpointing volatile data in non-volatile memory allows the system to recover after a power failure, but raises two issues: (i) spatial and temporal placement of checkpoints; (ii) memory allocation of variables between volatile and non-volatile memory, with the overall objective of using energy as efficiently as possible. While many techniques rely on the developer to address these issues, we present Schematic,a compiler technique that automates checkpoint placement and memory allocation to minimize the overall energy consumption. Schematicensures that programs will eventually terminate (forward progress property). Moreover, checkpoint placement and memory allocation adapt to the size of the energy buffer and the capacity of volatile memory. Schematictakes advantage of volatile memory (VM) to reduce the energy consumed, by automatically placing the most used variables in VM. We tested Schematicfor different experimental settings (size of volatile memory and capacitor) and results show an average energy reduction of 51 % compared to related techniques.
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