A. Bakar, Rishabh Goel, Jasper de Winkel, Jason Huang, Saad Ahmed, Bashima Islam, P. Pawełczak, K. Yıldırım, Josiah D. Hester
{"title":"Protean:自适应硬件加速间歇计算","authors":"A. Bakar, Rishabh Goel, Jasper de Winkel, Jason Huang, Saad Ahmed, Bashima Islam, P. Pawełczak, K. Yıldırım, Josiah D. Hester","doi":"10.1145/3599184.3599186","DOIUrl":null,"url":null,"abstract":"Today's smart devices have short battery lifetimes, high installation and maintenance costs, and rapid obsolescence - all leading to the explosion of electronic waste in the past two decades. These problems will worsen as the number of connected devices grows to one trillion by 2035. Energy harvesting, battery-free devices offer an alternative. Getting rid of the battery reduces e-waste, promises long lifetimes, and enables deployment in new applications and environments. Unfortunately, developing sophisticated inference-capable applications is still challenging. The lack of platform support for advanced (32-bit) microprocessors and specialized accelerators, which can execute dataintensive machine-learning tasks, has held back batteryless devices.","PeriodicalId":29918,"journal":{"name":"GetMobile-Mobile Computing & Communications Review","volume":"12 1","pages":"5 - 10"},"PeriodicalIF":0.7000,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Protean: Adaptive Hardware-Accelerated Intermittent Computing\",\"authors\":\"A. Bakar, Rishabh Goel, Jasper de Winkel, Jason Huang, Saad Ahmed, Bashima Islam, P. Pawełczak, K. Yıldırım, Josiah D. Hester\",\"doi\":\"10.1145/3599184.3599186\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Today's smart devices have short battery lifetimes, high installation and maintenance costs, and rapid obsolescence - all leading to the explosion of electronic waste in the past two decades. These problems will worsen as the number of connected devices grows to one trillion by 2035. Energy harvesting, battery-free devices offer an alternative. Getting rid of the battery reduces e-waste, promises long lifetimes, and enables deployment in new applications and environments. Unfortunately, developing sophisticated inference-capable applications is still challenging. The lack of platform support for advanced (32-bit) microprocessors and specialized accelerators, which can execute dataintensive machine-learning tasks, has held back batteryless devices.\",\"PeriodicalId\":29918,\"journal\":{\"name\":\"GetMobile-Mobile Computing & Communications Review\",\"volume\":\"12 1\",\"pages\":\"5 - 10\"},\"PeriodicalIF\":0.7000,\"publicationDate\":\"2023-05-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"GetMobile-Mobile Computing & Communications Review\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3599184.3599186\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"TELECOMMUNICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"GetMobile-Mobile Computing & Communications Review","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3599184.3599186","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"TELECOMMUNICATIONS","Score":null,"Total":0}
Today's smart devices have short battery lifetimes, high installation and maintenance costs, and rapid obsolescence - all leading to the explosion of electronic waste in the past two decades. These problems will worsen as the number of connected devices grows to one trillion by 2035. Energy harvesting, battery-free devices offer an alternative. Getting rid of the battery reduces e-waste, promises long lifetimes, and enables deployment in new applications and environments. Unfortunately, developing sophisticated inference-capable applications is still challenging. The lack of platform support for advanced (32-bit) microprocessors and specialized accelerators, which can execute dataintensive machine-learning tasks, has held back batteryless devices.