{"title":"基于服务器全局调度的周期DAG任务精确响应时间边界","authors":"Shareef Ahmed, James H. Anderson","doi":"10.1109/RTSS55097.2022.00045","DOIUrl":null,"url":null,"abstract":"Artificial-intelligence (AI) techniques are revolutionizing modern safety-critical real-time systems by enabling autonomous features never seen before. However, AI-based workloads are typically expressed as processing graphs that are subject to complex tradeoffs involving parallelism and dataflow dependencies. Due to such complexities, exact analysis of graph-based tasks is challenging under most (if not all) schedulers. This paper presents a periodic server-based scheduling policy for periodic graph-based task systems and provides an exact response-time analysis under this policy. This analysis entails pseudo-polynomial time complexity for pseudo-harmonic periodic graph-based tasks, which are commonly used in practice.","PeriodicalId":202402,"journal":{"name":"2022 IEEE Real-Time Systems Symposium (RTSS)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Exact Response-Time Bounds of Periodic DAG Tasks under Server-Based Global Scheduling\",\"authors\":\"Shareef Ahmed, James H. Anderson\",\"doi\":\"10.1109/RTSS55097.2022.00045\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Artificial-intelligence (AI) techniques are revolutionizing modern safety-critical real-time systems by enabling autonomous features never seen before. However, AI-based workloads are typically expressed as processing graphs that are subject to complex tradeoffs involving parallelism and dataflow dependencies. Due to such complexities, exact analysis of graph-based tasks is challenging under most (if not all) schedulers. This paper presents a periodic server-based scheduling policy for periodic graph-based task systems and provides an exact response-time analysis under this policy. This analysis entails pseudo-polynomial time complexity for pseudo-harmonic periodic graph-based tasks, which are commonly used in practice.\",\"PeriodicalId\":202402,\"journal\":{\"name\":\"2022 IEEE Real-Time Systems Symposium (RTSS)\",\"volume\":\"2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE Real-Time Systems Symposium (RTSS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/RTSS55097.2022.00045\",\"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 IEEE Real-Time Systems Symposium (RTSS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RTSS55097.2022.00045","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Exact Response-Time Bounds of Periodic DAG Tasks under Server-Based Global Scheduling
Artificial-intelligence (AI) techniques are revolutionizing modern safety-critical real-time systems by enabling autonomous features never seen before. However, AI-based workloads are typically expressed as processing graphs that are subject to complex tradeoffs involving parallelism and dataflow dependencies. Due to such complexities, exact analysis of graph-based tasks is challenging under most (if not all) schedulers. This paper presents a periodic server-based scheduling policy for periodic graph-based task systems and provides an exact response-time analysis under this policy. This analysis entails pseudo-polynomial time complexity for pseudo-harmonic periodic graph-based tasks, which are commonly used in practice.