CAP:多核实时应用程序的颜色感知任务划分

G. Gracioli, A. A. Fröhlich
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引用次数: 5

摘要

现代多核平台的特点是在处理器和主存之间放置了多层高速缓存,以隐藏普通存储系统的延迟。这个缓存层次结构的主要目标是提高平均执行时间(以可预测性为代价)。实时任务对缓存层次结构的不受控制的使用可能会影响对其最坏情况执行时间(WCET)的估计。通过页面着色进行软件缓存分区被认为是一种很有前途的方法,可以隔离任务工作负载,从而改进WCET估计。但是,当实时任务由于false或true共享而共享缓存分区时,由于缓存一致性协议导致的核间延迟可能会导致deadline丢失。在本文中,我们提出了一种颜色感知任务分区(CAP)算法,该算法根据内核对缓存分区(即颜色)的使用情况将任务分配给内核。共享一种或多种颜色的任务被分组在一起,整个组被分配给同一个处理器。因此,可以避免核间干扰。我们比较了用CAP算法和最差拟合递减启发式算法划分的几个生成任务集的最后期限缺失率。我们使用实时操作系统在具有共享l3缓存的现代8核处理器中执行分区任务集。结果表明,一种颜色感知任务划分算法可以避免在共享缓存的多核处理器中错过截止日期。
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CAP: Color-aware task partitioning for multicore real-time applications
Modern multicore platforms feature multiple levels of cache memory placed between the processor and main memory to hide the latency of ordinary memory systems. The primary goal of this cache hierarchy is to improve average execution time (at the cost of predictability). The uncontrolled use of the cache hierarchy by real-time tasks may impact the estimation of their worst-case execution times (WCET). Software cache partitioning through page coloring has been considered a promising approach to isolate task workloads and thus improve WCET estimation. However, when real-time tasks share cache partitions due to false or true sharing, the inter-core delay caused by the cache coherence protocol may cause deadline losses. In this paper, we propose a Color-Aware task Partitioning (CAP) algorithm that assigns tasks to cores respecting their usage of cache partitions (i.e., colors). Tasks that share one or more colors are grouped together and the whole group is assigned to the same processor. Thus, it is possible to avoid inter-core interference. We compared the deadline miss ratio of several generated task sets partitioned by the CAP algorithm and by the worst-fit decreasing heuristic. We executed the partitioned task sets in a modern 8-core processor with shared L3-cache using a real-time operating system. Our results indicate that a color-aware task partitioning algorithm can avoid deadline misses in a multicore processor with shared cache.
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