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Simultaneous Dynamic Voltage Scaling of Processors and Communication Links in Real-Time Distributed Embedded Systems

机译:实时分布式嵌入式系统中处理器和通信链路的同时动态电压缩放

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Dynamic voltage scaling has been widely acknowledged as a powerful technique for trading off power consumption and delay for processors. Recently, variable-frequency (and variable-voltage) parallel and serial links have also been proposed, which can save link power consumption by exploiting variations in the bandwidth requirement. This provides a new dimension for power optimization in a distributed embedded system connected by a voltage-scalable interconnection network. At the same time, it imposes new challenges for variable-voltage scheduling as well as flow control. First, the variable-voltage scheduling algorithm should be able to trade off the power consumption and delay jointly for both processors and links. Second, for the variable-frequency network, the scheduling algorithm should not only consider the real-time constraints, but should also be consistent with the underlying flow control techniques. In this paper, we address joint dynamic voltage scaling for variable-voltage processors and communication links in such systems. We propose a scheduling algorithm for real-time applications that captures both data flow and control flow information. It performs efficient routing of communication events through multihops, as well as efficient slack allocation among heterogeneous processors and communication links to maximize energy savings, while meeting all real-time constraints. Our experimental study shows that on an average, joint voltage scaling on processors and links can achieve 32% less power compared with voltage scaling on processors alone
机译:动态电压缩放已被公认为是权衡功耗和处理器延迟的强大技术。近来,还提出了可变频率(和可变电压)的并行和串行链路,其可以通过利用带宽要求的变化来节省链路功耗。这为通过电压可缩放互连网络连接的分布式嵌入式系统中的功率优化提供了新的维度。同时,它对可变电压调度和流量控制提出了新的挑战。首先,可变电压调度算法应该能够同时权衡处理器和链路的功耗和延迟。其次,对于变频网络,调度算法不仅应考虑实时约束,而且还应与基础流量控制技术保持一致。在本文中,我们讨论了此类系统中可变电压处理器和通信链路的联合动态电压缩放。我们为实时应用程序提出了一种调度算法,该算法可以捕获数据流和控制流信息。它通过多跳执行通信事件的有效路由,并在异构处理器和通信链路之间进行有效的空闲分配,以最大程度地节省能源,同时满足所有实时约束。我们的实验研究表明,与仅在处理器上进行电压缩放相比,处理器和链路上的联合电压缩放平均可以节省32%的功率

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