{"title":"海报摘要:P-FRP任务的记忆感知响应时间分析","authors":"Xingliang Zou, A. Cheng","doi":"10.1109/RTAS.2016.7461349","DOIUrl":null,"url":null,"abstract":"Summary form only given. Functional Reactive Programming (FRP) is playing and potentially going to play a more important role in real-time systems. Priority-based (preemptive) FRP (P-FRP), a variant of FRP with more real-time characteristics, demands more research in its scheduling and timing analysis. In a P-FRP system, similar to a classic preemptive system, a higher priority task can preempt a lower-priority one and make the latter abort. The lower-priority task will restart after the higher priority tasks complete their execution. However, unlike the classic preemptive model, when a task aborts, all the changes made by the task are discarded (Abort and Restart). In previous studies, the value of Worst Case Execution Time (WCET) of a task is used for all its restarted tasks. However, in practice restarted tasks likely consume less time than WCET when considering the memory effect such as cache-hit in loading code and data. Here we consider a typical task life cycle without being interrupted (cold started task): (1) code is loaded from hard drive and data is loaded from main memory; (2) computation is done by processor(s); (3) results are committed to main memory. In the P-FRP model, the time spent in phase (2) and (3) is wasted when a task is aborted, however, since the existence of memory hierarchy, the time spent in phase (1) can be less when a task is restarted, for example, the task code is still in cache and does not need to be read from slow main memory again. This memory effect is not considered in previous studies of P-FRP systems. In this paper, we present our preliminary memory-aware P-FRP task response time analysis and experimental results. Our ongoing research is to present more theoretical response time analysis and priority assignment research in the memory-aware P-FRP task scheduling. And since the execution time difference is likely related to data placement/locality, we will address this difference in our multi-core P-FRP task scheduling research too.","PeriodicalId":338179,"journal":{"name":"2016 IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Poster Abstract: Memory-Aware Response Time Analysis for P-FRP Tasks\",\"authors\":\"Xingliang Zou, A. Cheng\",\"doi\":\"10.1109/RTAS.2016.7461349\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Summary form only given. Functional Reactive Programming (FRP) is playing and potentially going to play a more important role in real-time systems. Priority-based (preemptive) FRP (P-FRP), a variant of FRP with more real-time characteristics, demands more research in its scheduling and timing analysis. In a P-FRP system, similar to a classic preemptive system, a higher priority task can preempt a lower-priority one and make the latter abort. The lower-priority task will restart after the higher priority tasks complete their execution. However, unlike the classic preemptive model, when a task aborts, all the changes made by the task are discarded (Abort and Restart). In previous studies, the value of Worst Case Execution Time (WCET) of a task is used for all its restarted tasks. However, in practice restarted tasks likely consume less time than WCET when considering the memory effect such as cache-hit in loading code and data. Here we consider a typical task life cycle without being interrupted (cold started task): (1) code is loaded from hard drive and data is loaded from main memory; (2) computation is done by processor(s); (3) results are committed to main memory. In the P-FRP model, the time spent in phase (2) and (3) is wasted when a task is aborted, however, since the existence of memory hierarchy, the time spent in phase (1) can be less when a task is restarted, for example, the task code is still in cache and does not need to be read from slow main memory again. This memory effect is not considered in previous studies of P-FRP systems. In this paper, we present our preliminary memory-aware P-FRP task response time analysis and experimental results. Our ongoing research is to present more theoretical response time analysis and priority assignment research in the memory-aware P-FRP task scheduling. 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引用次数: 1
摘要
只提供摘要形式。函数式反应性编程(FRP)在实时系统中扮演着并且有可能扮演更重要的角色。基于优先级(preemptive)的FRP (P-FRP)是FRP的一种变体,具有更强的实时性,其调度和时序分析需要更多的研究。在P-FRP系统中,类似于经典的抢占系统,高优先级的任务可以抢占低优先级的任务并使后者终止。高优先级的任务执行完毕后,低优先级的任务将重新启动。然而,与经典的抢占模型不同,当任务终止时,任务所做的所有更改都将被丢弃(Abort and Restart)。在以往的研究中,一个任务的最坏情况执行时间(WCET)值用于该任务的所有重启任务。然而,考虑到加载代码和数据时的缓存命中等内存影响,在实践中,重新启动任务可能比WCET消耗更少的时间。这里我们考虑一个没有中断的典型任务生命周期(冷启动任务):(1)代码从硬盘加载,数据从主存加载;(2)计算由处理器完成;(3)结果提交到主存。在P-FRP模型中,当任务被终止时,阶段(2)和(3)所花费的时间是浪费的,然而,由于内存层次结构的存在,当任务重新启动时,阶段(1)所花费的时间可以更少,例如,任务代码仍在缓存中,不需要再次从慢速主存中读取。这种记忆效应在以前的P-FRP系统研究中没有被考虑。在本文中,我们提出了初步的记忆感知P-FRP任务响应时间分析和实验结果。我们正在进行的研究是在记忆感知的P-FRP任务调度中提供更多的理论响应时间分析和优先级分配研究。由于执行时间差异可能与数据放置/位置有关,我们也将在我们的多核P-FRP任务调度研究中解决这一差异。
Poster Abstract: Memory-Aware Response Time Analysis for P-FRP Tasks
Summary form only given. Functional Reactive Programming (FRP) is playing and potentially going to play a more important role in real-time systems. Priority-based (preemptive) FRP (P-FRP), a variant of FRP with more real-time characteristics, demands more research in its scheduling and timing analysis. In a P-FRP system, similar to a classic preemptive system, a higher priority task can preempt a lower-priority one and make the latter abort. The lower-priority task will restart after the higher priority tasks complete their execution. However, unlike the classic preemptive model, when a task aborts, all the changes made by the task are discarded (Abort and Restart). In previous studies, the value of Worst Case Execution Time (WCET) of a task is used for all its restarted tasks. However, in practice restarted tasks likely consume less time than WCET when considering the memory effect such as cache-hit in loading code and data. Here we consider a typical task life cycle without being interrupted (cold started task): (1) code is loaded from hard drive and data is loaded from main memory; (2) computation is done by processor(s); (3) results are committed to main memory. In the P-FRP model, the time spent in phase (2) and (3) is wasted when a task is aborted, however, since the existence of memory hierarchy, the time spent in phase (1) can be less when a task is restarted, for example, the task code is still in cache and does not need to be read from slow main memory again. This memory effect is not considered in previous studies of P-FRP systems. In this paper, we present our preliminary memory-aware P-FRP task response time analysis and experimental results. Our ongoing research is to present more theoretical response time analysis and priority assignment research in the memory-aware P-FRP task scheduling. And since the execution time difference is likely related to data placement/locality, we will address this difference in our multi-core P-FRP task scheduling research too.