P. Anagnostou, Andres Gomez, P. Hager, H. Fatemi, J. P. D. Gyvez, L. Thiele, L. Benini
{"title":"Torpor:用于能量收集物联网soc的功耗感知硬件调度器","authors":"P. Anagnostou, Andres Gomez, P. Hager, H. Fatemi, J. P. D. Gyvez, L. Thiele, L. Benini","doi":"10.1109/PATMOS.2018.8464146","DOIUrl":null,"url":null,"abstract":"The recent growth of applications in the emerging Internet of Things field is posing new challenges in the longterm deployments of sensing devices. Currently, system designers rely on energy harvesting to reduce battery size and extend system lifetime. While some system functions need constant power supply, others can have their service adapted dynamically to available harvested energy. In this work we propose Torpor, a power-aware HW scheduler which continuously monitors harvesting power and in combination with its software runtime, dynamically activates system functions depending on the available energy. By performing a few key functions in HW, Torpor incurs a very low power overhead during continuous monitoring, while the software runtime provides a high degree of flexibility to enable different scheduling policies. We implemented Torpor on a FPGA-based prototype and demonstrated that with a sample power-aware dynamic scheduling policy, we can have a 2x or more improvement in execution rates compared to static (power-ignorant) policies. The power consumption of Torpor's always-on hardware integrated on chip is estimated to be less than 4 μW, making it a very promising power-management add-on for microprocessors used in IoT nodes.","PeriodicalId":234100,"journal":{"name":"2018 28th International Symposium on Power and Timing Modeling, Optimization and Simulation (PATMOS)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"Torpor: A Power-Aware HW Scheduler for Energy Harvesting IoT SoCs\",\"authors\":\"P. Anagnostou, Andres Gomez, P. Hager, H. Fatemi, J. P. D. Gyvez, L. Thiele, L. Benini\",\"doi\":\"10.1109/PATMOS.2018.8464146\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The recent growth of applications in the emerging Internet of Things field is posing new challenges in the longterm deployments of sensing devices. Currently, system designers rely on energy harvesting to reduce battery size and extend system lifetime. While some system functions need constant power supply, others can have their service adapted dynamically to available harvested energy. In this work we propose Torpor, a power-aware HW scheduler which continuously monitors harvesting power and in combination with its software runtime, dynamically activates system functions depending on the available energy. By performing a few key functions in HW, Torpor incurs a very low power overhead during continuous monitoring, while the software runtime provides a high degree of flexibility to enable different scheduling policies. We implemented Torpor on a FPGA-based prototype and demonstrated that with a sample power-aware dynamic scheduling policy, we can have a 2x or more improvement in execution rates compared to static (power-ignorant) policies. The power consumption of Torpor's always-on hardware integrated on chip is estimated to be less than 4 μW, making it a very promising power-management add-on for microprocessors used in IoT nodes.\",\"PeriodicalId\":234100,\"journal\":{\"name\":\"2018 28th International Symposium on Power and Timing Modeling, Optimization and Simulation (PATMOS)\",\"volume\":\"2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 28th International Symposium on Power and Timing Modeling, Optimization and Simulation (PATMOS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PATMOS.2018.8464146\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 28th International Symposium on Power and Timing Modeling, Optimization and Simulation (PATMOS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PATMOS.2018.8464146","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Torpor: A Power-Aware HW Scheduler for Energy Harvesting IoT SoCs
The recent growth of applications in the emerging Internet of Things field is posing new challenges in the longterm deployments of sensing devices. Currently, system designers rely on energy harvesting to reduce battery size and extend system lifetime. While some system functions need constant power supply, others can have their service adapted dynamically to available harvested energy. In this work we propose Torpor, a power-aware HW scheduler which continuously monitors harvesting power and in combination with its software runtime, dynamically activates system functions depending on the available energy. By performing a few key functions in HW, Torpor incurs a very low power overhead during continuous monitoring, while the software runtime provides a high degree of flexibility to enable different scheduling policies. We implemented Torpor on a FPGA-based prototype and demonstrated that with a sample power-aware dynamic scheduling policy, we can have a 2x or more improvement in execution rates compared to static (power-ignorant) policies. The power consumption of Torpor's always-on hardware integrated on chip is estimated to be less than 4 μW, making it a very promising power-management add-on for microprocessors used in IoT nodes.