Dongliang Chen, J. Edstrom, Xiaowei Chen, W. Jin, Jinhui Wang, Na Gong
{"title":"基于自适应电能质量权衡的数据驱动低成本片上存储器","authors":"Dongliang Chen, J. Edstrom, Xiaowei Chen, W. Jin, Jinhui Wang, Na Gong","doi":"10.1145/2934583.2934619","DOIUrl":null,"url":null,"abstract":"Nowadays, people enjoy watching mobile videos more than ever and mobile video streaming contributes to the majority of the total mobile data traffic. However, due to the high power consumption of mobile video decoders, especially the on-chip memories, short battery life represents one of the biggest contributors to user dissatisfaction. Various mobile embedded memory techniques have been investigated to reduce power consumption and prolong battery life. Unfortunately, the existing hardware-level research suffers from high implementation complexity and large overhead. In this paper, by introducing advanced data-mining techniques, we investigate meaningful data patterns hidden in mobile video data and apply the identified patterns to implement a low-power flexible hardware design with dynamic power-quality trade-off. A 45nm 32kb SRAM is presented that enables three levels of power-quality trade-off (up to 43.7% power savings) with negligible area overhead (0.06%).","PeriodicalId":142716,"journal":{"name":"Proceedings of the 2016 International Symposium on Low Power Electronics and Design","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Data-Driven Low-Cost On-Chip Memory with Adaptive Power-Quality Trade-off for Mobile Video Streaming\",\"authors\":\"Dongliang Chen, J. Edstrom, Xiaowei Chen, W. Jin, Jinhui Wang, Na Gong\",\"doi\":\"10.1145/2934583.2934619\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Nowadays, people enjoy watching mobile videos more than ever and mobile video streaming contributes to the majority of the total mobile data traffic. However, due to the high power consumption of mobile video decoders, especially the on-chip memories, short battery life represents one of the biggest contributors to user dissatisfaction. Various mobile embedded memory techniques have been investigated to reduce power consumption and prolong battery life. Unfortunately, the existing hardware-level research suffers from high implementation complexity and large overhead. In this paper, by introducing advanced data-mining techniques, we investigate meaningful data patterns hidden in mobile video data and apply the identified patterns to implement a low-power flexible hardware design with dynamic power-quality trade-off. A 45nm 32kb SRAM is presented that enables three levels of power-quality trade-off (up to 43.7% power savings) with negligible area overhead (0.06%).\",\"PeriodicalId\":142716,\"journal\":{\"name\":\"Proceedings of the 2016 International Symposium on Low Power Electronics and Design\",\"volume\":\"20 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-08-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2016 International Symposium on Low Power Electronics and Design\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2934583.2934619\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2016 International Symposium on Low Power Electronics and Design","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2934583.2934619","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Data-Driven Low-Cost On-Chip Memory with Adaptive Power-Quality Trade-off for Mobile Video Streaming
Nowadays, people enjoy watching mobile videos more than ever and mobile video streaming contributes to the majority of the total mobile data traffic. However, due to the high power consumption of mobile video decoders, especially the on-chip memories, short battery life represents one of the biggest contributors to user dissatisfaction. Various mobile embedded memory techniques have been investigated to reduce power consumption and prolong battery life. Unfortunately, the existing hardware-level research suffers from high implementation complexity and large overhead. In this paper, by introducing advanced data-mining techniques, we investigate meaningful data patterns hidden in mobile video data and apply the identified patterns to implement a low-power flexible hardware design with dynamic power-quality trade-off. A 45nm 32kb SRAM is presented that enables three levels of power-quality trade-off (up to 43.7% power savings) with negligible area overhead (0.06%).