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A Multi-Agent Framework for Thermal Aware Task Migration in Many-Core Systems

机译:用于多核系统中的热感知任务迁移的多代理框架

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摘要

In deep submicrometer era, thermal hot spots, and large temperature gradients significantly impact system reliability, performance, cost, and leakage power. As the system complexity increases, it is more and more difficult to perform thermal management in a centralized manner because of state explosion and the overhead of monitoring the entire chip. In this paper, we propose a framework for distributed thermal management in many-core systems where balanced thermal profile can be achieved by proactive task migration among neighboring cores. The framework has a low cost agent residing in each core that observes the local workload and temperature and communicates with its nearest neighbor for task migration and exchange. By choosing only those migration requests that will result in balanced workload without generating thermal emergency, the proposed framework maintains workload balance across the system and avoids unnecessary migration. Experimental results show that, our distributed management policy achieves almost the same performance as a global management policy when the tasks are initially randomly distributed. Compared with existing proactive task migration technique, our approach generates less hotspot, less migration overhead with negligible performance overhead.
机译:在深亚微米时代,热点和较大的温度梯度会严重影响系统的可靠性,性能,成本和泄漏功率。随着系统复杂度的增加,由于状态爆炸和监视整个芯片的开销,以集中方式执行热管理越来越困难。在本文中,我们为多核系统中的分布式热管理提出了一个框架,在该系统中,可以通过主动地在相邻核之间迁移任务来实现平衡的热量分布。该框架在每个内核中都有一个低成本代理,该代理观察本地工作负载和温度,并与其最近的邻居进行通信以进行任务迁移和交换。通过仅选择那些将导致工作负载平衡而不会产生热紧急情况的迁移请求,建议的框架可保持整个系统的工作负载平衡并避免不必要的迁移。实验结果表明,当任务最初随机分布时,我们的分布式管理策略可达到与全局管理策略几乎相同的性能。与现有的主动任务迁移技术相比,我们的方法产生的热点更少,迁移开销更少,而性能开销却可以忽略不计。

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