嵌入式多核系统中Pfair实时调度程序的任务i /O协同调度

Sangsoo Park
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引用次数: 6

摘要

实时嵌入式系统通常需要强大的控制能力,因为嵌入式系统与其物理环境之间的交互是动态变化的。对于这种环境,多核芯片被认为是理想的候选硬件组件,因为它们中的每个都在单个die上携带两个或更多的内核,并且具有提供执行并行性和低成本的更好性能的潜力。另一方面,并行性要求对任务调度等计算问题进行复杂的分析,同时提高了嵌入式控制的实现。Pfair是一种可以充分利用系统中所有内核的最优调度算法,但它带来了过高的调度开销,这反过来又降低了它在嵌入式系统中的实用性。为了缓解这一问题,提出了混合分区-全局Pfair (HPGP)调度器,该调度器仅在绝对必要时执行全局调度,从而大大减少了任务迁移和全局调度点的数量,同时仍然实现了充分的处理器利用率。本文进一步扩展了HPGP调度器,以支持与物理环境交互的鲁棒性。我们的评估结果表明,在广泛的系统利用条件下,扩展的HPGP可以成功地限制由硬件中断引起的物理交互的响应时间增加。,因此适用于嵌入式实时系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Task-I/O Co-scheduling for Pfair Real-Time Scheduler in Embedded Multi-core Systems
Real-time embedded systems often require the ability of robust controls because interactions between the embedded systems and their physical environment that dynamically changes. Multi-core chips are regarded as ideal candidate hardware components for such environments, since each of them carries two or more cores on a single die, and has potential for providing execution parallelism as well as better performance at low cost. Parallelism, on the other hand, necessitates complex analysis of computation problems, such as task scheduling, while improving the realization of embedded controls. Pfair is an optimal scheduling algorithm that can fully utilize all cores in the system, but it incurs an excessive scheduling overhead which, in turn, diminishes its practicality in embedded systems. To mitigate this problem, hybrid partitioned-global Pfair (HPGP) scheduler was proposed, which significantly reduces the number of task migrations and global scheduling points by performing global scheduling only when absolutely necessary, while still achieving full processor utilization. This paper further extends the HPGP scheduler to support the robustness to interactions with the physical environment. Our evaluation results have shown that the extended HPGP can successfully limits the increase in response time caused by the hardware interrupts for physical interactions under a wide range of system utilization conditions., thus making it suitable for embedded real-time systems.
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