Contention-Aware Energy Management Scheme for NoC-Based Multicore Real-Time Systems
Contention-Aware Energy Management Scheme for NoC-Based Multicore Real-Time Systems
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DOI：
10.1109/tpds.2014.2307866
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发表时间：
2015-03
影响因子：
5.3
通讯作者：
Jianjun Han;Man Lin;Dakai Zhu;L. Yang
中科院分区：
文献类型：
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作者：
Jianjun Han;Man Lin;Dakai Zhu;L. Yang
片上网络（NoC）已成为最先进的多/多核心架构中的互连范例。电压和频率岛（VFI）是近年来大规模多核芯片设计中采用的一种有效的能量管理技术。针对具有动态电压频率缩放（DVFS）功能的基于noc和vfi的多/多核心实时系统，研究了具有优先关系和共同截止日期的任务集的静态和动态竞争感知能量管理方案。首先，我们的静态方案利用两种具有争用意识的方法来获得任务到核心的映射以及NoC上的通信调度以最小化makespan，因此可以在满足及时性的同时降低核心和链路的均匀缩放频率。其次，与其他现有方案不同的是，我们的动态竞争感知能源管理方案通过将网络拥塞导致的延迟纳入分析，在不受VFI共同电压和频率限制以及任务集时间约束的情况下，同时向任务和通信分配可行的空闲时间，以进一步节约能源。通过广泛的模拟和案例研究的结果表明，与基于启发式和基于inlp的任务映射解决方案（对通信争用进行悲观估计）相比，我们的静态方案可以获得更好的节能（例如，多25%）。结果还表明，在截止日期保证下，我们的动态方案比静态方案节能高达45%，而忽略NoC交通拥堵的在线方案可能导致严重的截止日期违规，通常会导致更多的能源消耗（例如多15%）。
Network-on-Chip (NoC) has emerged as interconnect paradigm in state-of-the-art multi/many core architectures. Voltage and frequency island (VFI) was recently adopted as an effective energy management technique for large scale multicore chip designs. Focusing on NoCand VFI-based multi/many core real-time systems with Dynamic Voltage and Frequency Scaling (DVFS) capability, we study both static and dynamic contention-aware energy management schemes for task set with precedence relationships and a common deadline. First, our static schemes utilize two approaches with contention awareness to obtain the mapping of tasks to cores together with scheduling of communications on NoC for minimizing makespan, and thus can potentially lower uniform scaled frequency for cores and links while meeting the timeliness. Next, different from other existing schemes, by incorporating the latency due to network congestions into the analysis, our dynamic contention-aware energy management schemes perform the allocation of feasible slack to tasks and communications simultaneously for further energy savings, subject to common voltage and frequency limitations of VFI and timing constraints of task set. The results through extensive simulations and case studies show that, compared to heuristicbased and INLP-based task mapping solutions (with pessimistic estimation of communication contention), our static scheme can obtain better energy savings (e.g., 25 percent more). The results also show that our dynamic scheme can save up to 45 percent more energy compared to our static scheme under deadline guarantee, while the online scheme ignoring the traffic congestions in NoC can result in serious deadline violation and usually more energy consumption (e.g., 15 percent more).