Connor Imes, David H. K. Kim, M. Maggio, H. Hoffmann
{"title":"POET:一种在软实时约束下最小化能量的便携式方法","authors":"Connor Imes, David H. K. Kim, M. Maggio, H. Hoffmann","doi":"10.1109/RTAS.2015.7108419","DOIUrl":null,"url":null,"abstract":"Embedded real-time systems must meet timing constraints while minimizing energy consumption. To this end, many energy optimizations are introduced for specific platforms or specific applications. These solutions are not portable, however, and when the application or the platform change, these solutions must be redesigned. Portable techniques are hard to develop due to the varying tradeoffs experienced with different application/platform configurations. This paper addresses the problem of finding and exploiting general tradeoffs, using control theory and mathematical optimization to achieve energy minimization under soft real-time application constraints. The paper presents POET, an open-source C library and runtime system that takes a specification of the platform resources and optimizes the application execution. We test POET's ability to portably deliver predictable timing and energy reduction on two embedded systems with different tradeoff spaces - the first with a mobile Intel Haswell processor, and the second with an ARM big.LITTLE System on Chip. POET achieves the desired latency goals with small error while consuming, on average, only 1.3% more energy than the dynamic optimal oracle on the Haswell and 2.9% more on the ARM. We believe this open-source, library-based approach to resource management will simplify the process of writing portable, energy-efficient code for embedded systems.","PeriodicalId":320300,"journal":{"name":"21st IEEE Real-Time and Embedded Technology and Applications Symposium","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"106","resultStr":"{\"title\":\"POET: a portable approach to minimizing energy under soft real-time constraints\",\"authors\":\"Connor Imes, David H. K. Kim, M. Maggio, H. Hoffmann\",\"doi\":\"10.1109/RTAS.2015.7108419\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Embedded real-time systems must meet timing constraints while minimizing energy consumption. To this end, many energy optimizations are introduced for specific platforms or specific applications. These solutions are not portable, however, and when the application or the platform change, these solutions must be redesigned. Portable techniques are hard to develop due to the varying tradeoffs experienced with different application/platform configurations. This paper addresses the problem of finding and exploiting general tradeoffs, using control theory and mathematical optimization to achieve energy minimization under soft real-time application constraints. The paper presents POET, an open-source C library and runtime system that takes a specification of the platform resources and optimizes the application execution. We test POET's ability to portably deliver predictable timing and energy reduction on two embedded systems with different tradeoff spaces - the first with a mobile Intel Haswell processor, and the second with an ARM big.LITTLE System on Chip. POET achieves the desired latency goals with small error while consuming, on average, only 1.3% more energy than the dynamic optimal oracle on the Haswell and 2.9% more on the ARM. We believe this open-source, library-based approach to resource management will simplify the process of writing portable, energy-efficient code for embedded systems.\",\"PeriodicalId\":320300,\"journal\":{\"name\":\"21st IEEE Real-Time and Embedded Technology and Applications Symposium\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-04-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"106\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"21st IEEE Real-Time and Embedded Technology and Applications Symposium\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/RTAS.2015.7108419\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"21st IEEE Real-Time and Embedded Technology and Applications Symposium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RTAS.2015.7108419","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
POET: a portable approach to minimizing energy under soft real-time constraints
Embedded real-time systems must meet timing constraints while minimizing energy consumption. To this end, many energy optimizations are introduced for specific platforms or specific applications. These solutions are not portable, however, and when the application or the platform change, these solutions must be redesigned. Portable techniques are hard to develop due to the varying tradeoffs experienced with different application/platform configurations. This paper addresses the problem of finding and exploiting general tradeoffs, using control theory and mathematical optimization to achieve energy minimization under soft real-time application constraints. The paper presents POET, an open-source C library and runtime system that takes a specification of the platform resources and optimizes the application execution. We test POET's ability to portably deliver predictable timing and energy reduction on two embedded systems with different tradeoff spaces - the first with a mobile Intel Haswell processor, and the second with an ARM big.LITTLE System on Chip. POET achieves the desired latency goals with small error while consuming, on average, only 1.3% more energy than the dynamic optimal oracle on the Haswell and 2.9% more on the ARM. We believe this open-source, library-based approach to resource management will simplify the process of writing portable, energy-efficient code for embedded systems.