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CRQ-based Fair Scheduling on Composable Multicore Architectures

机译:可组合多核架构上基于CRQ的公平调度

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As different workloads require different processor resources for better execution efficiency, recent work has proposed composable chip multiprocessors (CCMPs), which provide the capability to configure different number and types of processing cores at system runtime. However, such composable architecture poses a new significant challenge to system scheduler, that is, how to ensure priority-based performance for each task (i.e. fairness), while exploiting the benefits of composability by dynamically changing the hardware configurations to match the parallelism requirements in running tasks (i.e. resource allocation). Current multicore schedulers fail to address this problem, as they traditionally assume fixed number and types of cores. In this work, we introduce centralized ran queue (CRQ) and propose an efficiency-based algorithm to address the fair scheduling problem on CCMP. Firstly, instead of using distributed per-core mn queues, this paper employs CRQ to simplify the scheduling and resource allocation decisions on CCMP, and proposes a pipeline-like scheduling mechanism to hide the large scheduling decision overhead on the centralized queue. Secondly, an efficiency-based dynamic priority (EDP) algorithm is proposed to keep fair scheduling on CCMP, which can not only provide homogenous tasks with performance proportional to their priorities, but also ensure equal-priority heterogeneous tasks to get equivalent performance slowdowns when running simultaneously. To evaluate our design, experimental studies are carried out to compare EDP on CCMP with several state-of-art fair schedulers on symmetric and asymmetric CMPs. Our simulation results demonstrate that, while providing good fairness, EDP on CCMP outperforms the best performing fair scheduler on fixed symmetric and asymmetric CMPs by as much as 11.8% in user-oriented performance, and by 12.5% in system throughput.
机译:由于不同的工作负载需要不同的处理器资源以提高执行效率,因此最近的工作提出了可组合芯片多处理器(CCMP),该处理器可在系统运行时配置不同数量和类型的处理内核。但是,这种可组合的体系结构对系统调度程序提出了新的重大挑战,即如何确保每个任务的基于优先级的性能(即公平性),同时通过动态更改硬件配置以匹配并行性要求来利用可组合性的好处。正在运行的任务(即资源分配)。当前的多核调度程序无法解决此问题,因为它们传统上都假定固定数量和类型的核。在这项工作中,我们介绍了集中式运行队列(CRQ),并提出了一种基于效率的算法来解决CCMP上的公平调度问题。首先,本文采用CRQ简化了CCMP上的调度和资源分配决策,而不是使用分布式的每核mn队列,并提出了一种类似于管道的调度机制来隐藏集中式队列上的大量调度决策开销。其次,提出了一种基于效率的动态优先级(EDP)算法,以在CCMP上保持公平的调度,该算法不仅可以为同质任务提供与它们的优先级成比例的性能,而且还可以确保同等优先级的异构任务在运行时得到等效的性能下降同时。为了评估我们的设计,进行了实验研究,以比较CCMP上的EDP和几种对称和非对称CMP上最新的公平调度程序。我们的仿真结果表明,在提供良好公平性的同时,CCMP上的EDP在固定对称和非对称CMP上的性能优于性能最佳的公平调度程序,其面向用户的性能提高了11.8%,系统吞吐量提高了12.5%。

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