基于人工智能的嵌入式实时系统功率优化与自适应

2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS) Pub Date : 2022-11-24 DOI:10.1109/ICAISS55157.2022.10011023

Nilamani Ganesan, T. Muthumanickam

{"title":"基于人工智能的嵌入式实时系统功率优化与自适应","authors":"Nilamani Ganesan, T. Muthumanickam","doi":"10.1109/ICAISS55157.2022.10011023","DOIUrl":null,"url":null,"abstract":"This research study focuses on finding solutions to the emerging challenges in the embedded systems' power consumption optimization. First, the challenges in physical CMOS power consumption are analyzed and further various real-time limitationsand load characteristics are explored. Further, various power consumption techniques are considered by including DMP, DVS/DFS, AVS, and ABB. Issues with organising a feedback and determining adaptability for various embedded systems are investigated.","PeriodicalId":243784,"journal":{"name":"2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Artificial Intelligence System based Embedded Real-Time System Power Optimization and Adaptability\",\"authors\":\"Nilamani Ganesan, T. Muthumanickam\",\"doi\":\"10.1109/ICAISS55157.2022.10011023\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This research study focuses on finding solutions to the emerging challenges in the embedded systems' power consumption optimization. First, the challenges in physical CMOS power consumption are analyzed and further various real-time limitationsand load characteristics are explored. Further, various power consumption techniques are considered by including DMP, DVS/DFS, AVS, and ABB. Issues with organising a feedback and determining adaptability for various embedded systems are investigated.\",\"PeriodicalId\":243784,\"journal\":{\"name\":\"2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS)\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-11-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICAISS55157.2022.10011023\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAISS55157.2022.10011023","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 0

摘要

本研究的重点是寻找解决方案，以嵌入式系统的功耗优化的新挑战。首先，分析了CMOS物理功耗方面的挑战，并进一步探讨了各种实时限制和负载特性。此外，还考虑了各种功耗技术，包括DMP、DVS/DFS、AVS和ABB。研究了组织反馈和确定各种嵌入式系统适应性的问题。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Artificial Intelligence System based Embedded Real-Time System Power Optimization and Adaptability

This research study focuses on finding solutions to the emerging challenges in the embedded systems' power consumption optimization. First, the challenges in physical CMOS power consumption are analyzed and further various real-time limitationsand load characteristics are explored. Further, various power consumption techniques are considered by including DMP, DVS/DFS, AVS, and ABB. Issues with organising a feedback and determining adaptability for various embedded systems are investigated.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS)

自引率

0.00%

发文量