Time based agent garbage collection algorithm for multicore architectures

G. Muneeswari, K. L. Shunmuganathan
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Abstract

Multicore architecture consists of large number of processors that are arranged together on the same chip uses hyper threading technology (using virtualization). The parallel processing exhibited by the large number of processor increases the challenges and design issues for the real time process (critical task) execution on the processor cores. This is a vital part from the operating system scheduling and storage compaction point of view. In this paper we combine the AMAS theory of multiagent system with the affinity based processor scheduling and this will be best suited for critical task execution on multicore platforms. This hard-soft processor affinity scheduling algorithm promises in minimizing the average waiting time of the non critical tasks in the centralized queue and avoids the context switching of critical tasks. That is we assign hard affinity for critical tasks and soft affinity for non critical tasks. The algorithm is applicable for the system that consists of both critical and non critical tasks in the ready queue. Since we use the actual round robin scheduling for non critical tasks and due to soft affinity the load balancing is done automatically for non critical tasks. The novel storage compaction (garbage collection) algorithm consists of local and global garbage collectors which efficiently identifies and removes the unwanted files or information in the distributed or multicore environment making a room for efficient scheduling. We actually modified and simulated the linux 2.6.11 kernel process scheduler to incorporate this scheduling concept. Our result shows the maximum cpu utilization for the non critical tasks and high throughput for the critical tasks.
基于时间的多核体系结构代理垃圾收集算法
多核体系结构使用超线程技术(使用虚拟化)将大量处理器排列在同一芯片上。大量处理器所表现出的并行处理增加了处理器内核上实时进程(关键任务)执行的挑战和设计问题。从操作系统调度和存储压缩的角度来看,这是一个至关重要的部分。本文将多智能体系统的AMAS理论与基于亲和度的处理器调度相结合,使之更适合多核平台上关键任务的执行。该算法既保证了集中队列中非关键任务的平均等待时间最小化,又避免了关键任务的上下文切换。也就是说,我们为关键任务分配硬亲和力,为非关键任务分配软亲和力。该算法适用于在就绪队列中同时包含关键任务和非关键任务的系统。由于我们对非关键任务使用实际的轮循调度,并且由于软亲和性,非关键任务的负载平衡是自动完成的。新的存储压缩(垃圾收集)算法由本地和全局垃圾收集器组成,可以有效地识别和删除分布式或多核环境中不需要的文件或信息,从而为高效调度提供空间。我们实际上修改并模拟了linux 2.6.11内核进程调度器,以纳入这个调度概念。我们的结果显示了非关键任务的最大cpu利用率和关键任务的高吞吐量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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