Energy-Aware Memory Mapping for Hybrid FRAM-SRAM MCUs in Intermittently-Powered IoT Devices
Energy-Aware Memory Mapping for Hybrid FRAM-SRAM MCUs in Intermittently-Powered IoT Devices
复制标题
间歇供电物联网设备中混合 FRAM-SRAM MCU 的能源感知内存映射
DOI：
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发表时间：
2017
影响因子：
2
通讯作者：
V. Raghunathan
中科院分区：
文献类型：
--
作者：
H. Jayakumar;Arnab Raha;Jacob R. Stevens;V. Raghunathan
据预测，到2020年，将有大约500亿台设备连接到物联网（IoT），其中大部分将不受限制和不插电。虽然环境能源收集是为这些物联网边缘设备供电的一种有前途的解决方案，但由于环境能源的不可靠性，它引入了新的复杂性。在存在不可靠的电源的情况下，系统状态的频繁检查点设置变得势在必行，并且最近的研究已经提出了通过使用铁电RAM（弗拉姆）（一种新兴的非易失性存储器技术）作为这些系统中的统一存储器的原位检查点设置的概念。尽管完全基于FRAM的解决方案提供可靠性，但由于弗拉姆的较高访问延迟，与SRAM相比，它的能量效率较低。另一方面，完全基于SRAM的解决方案具有很高的能效，但在功率损耗方面不可靠。本文主张在混合FRAM-SRAM微控制器的中间方法，涉及明智的存储器映射的程序部分，以保留弗拉姆提供的可靠性的好处，同时执行几乎一样有效的SRAM为基础的系统。我们提出了一种能量感知的内存映射技术，映射不同的程序部分的混合FRAM-SRAM微控制器，使能源消耗最小化，而不牺牲可靠性。我们的技术包括eM-map，它执行一次性表征，以找到构成程序和能量对齐的功能的最佳内存映射，这是一种新颖的硬件-软件技术，将系统的通电时间间隔与功能执行边界对齐，从而进一步提高能效和性能。使用MSP430 FR 5739微控制器获得的实验结果表明，与最先进的基于FRAM的解决方案相比，性能显著提高了2倍，能耗降低了20%。最后，我们提出了一个案例研究，展示了我们的技术在一个真实的物联网应用程序的背景下实现。
Forecasts project that by 2020, there will be around 50 billion devices connected to the Internet of Things (IoT), most of which will operate untethered and unplugged. While environmental energy harvesting is a promising solution to power these IoT edge devices, it introduces new complexities due to the unreliable nature of ambient energy sources. In the presence of an unreliable power supply, frequent checkpointing of the system state becomes imperative, and recent research has proposed the concept of in-situ checkpointing by using ferroelectric RAM (FRAM), an emerging non-volatile memory technology, as unified memory in these systems. Even though an entirely FRAM-based solution provides reliability, it is energy inefficient compared to SRAM due to the higher access latency of FRAM. On the other hand, an entirely SRAM-based solution is highly energy efficient but is unreliable in the face of power loss. This paper advocates an intermediate approach in hybrid FRAM-SRAM microcontrollers that involves judicious memory mapping of program sections to retain the reliability benefits provided by FRAM while performing almost as efficiently as an SRAM-based system. We propose an energy-aware memory mapping technique that maps different program sections to the hybrid FRAM-SRAM microcontroller such that energy consumption is minimized without sacrificing reliability. Our technique consists of eM-map, which performs a one-time characterization to find the optimal memory map for the functions that constitute a program and energy-align, a novel hardware-software technique that aligns the system’s powered-on time intervals to function execution boundaries, which results in further improvements in energy efficiency and performance. Experimental results obtained using the MSP430FR5739 microcontroller demonstrate a significant performance improvement of up to 2x and energy reduction of up to 20% over a state-of-the-art FRAM-based solution. Finally, we present a case study that shows the implementation of our techniques in the context of a real IoT application.
DOI：
10.1109/tcad.2016.2547919
发表时间：
2016-12-01
影响因子：
2.9
作者：
Balsamo, Domenico;Weddell, Alex S.;Benini, Luca
通讯作者：
Benini, Luca