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Lookup NU author(s): Dr Osama Bin TariqORCiD, Dr Domenico Balsamo
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
Intermittent systems powered by harvested energy frequently encounter power outages, requiring efficient mechanisms to save and restore their internal state, to ensure computational progress. In these systems, minimising the overhead of state retention, comprising CPU core registers and main volatile memory contents (a snapshot), is essential to maximise computational progress within the constraints of limited energy availability. This paper introduces a hardware module, MeTra (MEmory TRAcing), designed to enhance energy-efficient state retention in intermittent systems. This is achieved by tracing and selectively saving the modified parts of the main volatile memory (RAM) to non-volatile memory (NVM), i.e. FRAM. Additionally, MeTra dynamically adjusts the voltage threshold that initiates state saving, optimizing energy usage for each snapshot and enabling the system to dedicate more harvested energy to useful computations. MeTra was integrated with an Arm Cortex-M1 processor on an FPGA and evaluated using benchmarks including matrix multiplication, array sorting, and advanced encryption standard (AES), demonstrating its effectiveness in reducing state saving time and improving energy efficiency by selectively saving modified RAM regions instead of the entire memory. Experimental results demonstrate that snapshot time can be reduced by 48.34% to 57.56% in FRAM-based systems, leading to an improvement in energy efficiency of 65.24% to 77.76%. These gains are achieved by selectively saving 5.66% to 19.82% of RAM, using MeTra, compared to saving entire RAM.
Author(s): Tariq OB, Verykios TD, Merrett GV, Balsamo D
Publication type: Article
Publication status: Published
Journal: IEEE Transactions on Sustainable Computing
Year: 2025
Pages: epub ahead of print
Online publication date: 14/10/2025
Acceptance date: 05/10/2025
Date deposited: 29/10/2025
ISSN (electronic): 2377-3782
Publisher: IEEE
URL: https://doi.org/10.1109/TSUSC.2025.3621509
DOI: 10.1109/TSUSC.2025.3621509
ePrints DOI: 10.57711/yd9n-s742
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