Liang, Yu PeiYu PeiLiangFang, Yu TingYu TingFangChen, Shuo HanShuo HanChenYEN-TING CHENChen, Tseng YiTseng YiChenWang, Wei LinWei LinWangShih, Wei KuanWei KuanShihChang, Yuan HaoYuan HaoChang2023-09-232023-09-232021-05-01978166540386315453421https://scholars.lib.ntu.edu.tw/handle/123456789/635692Intermittent systems enable continuous and accumulative process execution under constraint or unstable power supply. To enable intermittent computing, process status and data are typically checkpointed from volatile memory (VM) to nonvolatile memory (NVM) before running out of power. After power resumes, these logged data can be loaded back from NVM to VM for continuous execution. Nevertheless, existing approaches rarely considered the energy consumed during moving data and may waste precious power resource over data movement, instead of computation. Such observation motivates us to propose an energy-reduction on-chip memory management (ERCM2) scheme to utilize the high cell density and non-volatility of SpinTransfer Torque RAM (STT-RAM) for enabling a hybrid on chip memory architecture. The experimental results show that the proposed scheme can achieve the access performance close to conventional SRAM-based on-chip memory architecture with lower energy consumption.embedded system | energy reduction | intermittent systems | scartchpad memory[SDGs]SDG7conference paper10.1109/RTAS52030.2021.000442-s2.0-85113816232https://api.elsevier.com/content/abstract/scopus_id/85113816232