--- _id: '66222' abstract: - lang: eng text: |- Dynamic power management (DPM) reduces the power consumption of a computing system when it idles, by switching the system into a low power state for hibernation. When all processors in the system share the same component, e.g., a shared memory, powering off this component during hibernation is only possible when all processors idle at the same time. For a real-time system, the schedulability property has to be guaranteed on every processor, especially if idle intervals are considered to be actively introduced. In this work, we consider real-time systems with hybrid shared-memory architectures, which consist of shared volatile memory (VM) and non-volatile memory (NVM). Energy-efficient execution is achieved by applying DPM to turn off all memories during the hibernation mode. Towards this, we first explore the hybrid memory architectures and suggest a task model, which features configurable hibernation overheads. We propose a multi-processor procrastination algorithm (HEART), based on partitioned earliest-deadline-first (pEDF) scheduling. Our algorithm facilitates reducing the energy consumption by actively enlarging the hibernation time. It enforces all processors to idle simultaneously without violating the schedulability condition, such that the system can enter the hibernation state, where shared memories are turned off. Throughout extensive evaluation of HEART, we demonstrate (1) the increase in potential hibernation time, respectively the decrease in energy consumption, and (2) that our algorithm is not only more general but also has better performance than the state of the art with respect to energy efficiency in most cases. author: - first_name: Mario full_name: Günzel, Mario last_name: Günzel - first_name: Christian full_name: Hakert, Christian last_name: Hakert - first_name: Kuan-Hsun full_name: Chen, Kuan-Hsun last_name: Chen - first_name: Jian-Jia full_name: Chen, Jian-Jia last_name: Chen citation: ama: Günzel M, Hakert C, Chen K-H, Chen J-J. HEART:            <u>H</u>            ybrid Memory and            <u>E</u>            nergy-            <u>A</u>            ware            <u>R</u>            eal-            <u>T</u>            ime Scheduling for Multi-Processor Systems. ACM Transactions on Embedded Computing Systems. 2021;20(5s):1-23. doi:10.1145/3477019 apa: Günzel, M., Hakert, C., Chen, K.-H., & Chen, J.-J. (2021). HEART:            <u>H</u>            ybrid Memory and            <u>E</u>            nergy-            <u>A</u>            ware            <u>R</u>            eal-            <u>T</u>            ime Scheduling for Multi-Processor Systems. ACM Transactions on Embedded Computing Systems, 20(5s), 1–23. https://doi.org/10.1145/3477019 bibtex: '@article{Günzel_Hakert_Chen_Chen_2021, title={HEART:            <u>H</u>            ybrid Memory and            <u>E</u>            nergy-            <u>A</u>            ware            <u>R</u>            eal-            <u>T</u>            ime Scheduling for Multi-Processor Systems}, volume={20}, DOI={10.1145/3477019}, number={5s}, journal={ACM Transactions on Embedded Computing Systems}, publisher={Association for Computing Machinery (ACM)}, author={Günzel, Mario and Hakert, Christian and Chen, Kuan-Hsun and Chen, Jian-Jia}, year={2021}, pages={1–23} }' chicago: 'Günzel, Mario, Christian Hakert, Kuan-Hsun Chen, and Jian-Jia Chen. “HEART:            <u>H</U>            Ybrid Memory and            <u>E</U>            Nergy-            <u>A</U>            Ware            <u>R</U>            Eal-            <u>T</U>            Ime Scheduling for Multi-Processor Systems.” ACM Transactions on Embedded Computing Systems 20, no. 5s (2021): 1–23. https://doi.org/10.1145/3477019.' ieee: 'M. Günzel, C. Hakert, K.-H. Chen, and J.-J. Chen, “HEART:            <u>H</u>            ybrid Memory and            <u>E</u>            nergy-            <u>A</u>            ware            <u>R</u>            eal-            <u>T</u>            ime Scheduling for Multi-Processor Systems,” ACM Transactions on Embedded Computing Systems, vol. 20, no. 5s, pp. 1–23, 2021, doi: 10.1145/3477019.' mla: Günzel, Mario, et al. “HEART:            <u>H</U>            Ybrid Memory and            <u>E</U>            Nergy-            <u>A</U>            Ware            <u>R</U>            Eal-            <u>T</U>            Ime Scheduling for Multi-Processor Systems.” ACM Transactions on Embedded Computing Systems, vol. 20, no. 5s, Association for Computing Machinery (ACM), 2021, pp. 1–23, doi:10.1145/3477019. short: M. Günzel, C. Hakert, K.-H. Chen, J.-J. Chen, ACM Transactions on Embedded Computing Systems 20 (2021) 1–23. date_created: 2026-07-03T21:21:20Z date_updated: 2026-07-05T14:44:23Z doi: 10.1145/3477019 intvolume: ' 20' issue: 5s language: - iso: eng page: 1-23 publication: ACM Transactions on Embedded Computing Systems publication_identifier: issn: - 1539-9087 - 1558-3465 publication_status: published publisher: Association for Computing Machinery (ACM) status: public title: |- HEART: H ybrid Memory and E nergy- A ware R eal- T ime Scheduling for Multi-Processor Systems type: journal_article user_id: '128464' volume: 20 year: '2021' ...