Energy management is a critical challenge in multicore processors due to continuous technology scaling. Previous methods have mostly focused on the energy minimization of the processor cores. However, energy overhead of the off-chip voltage regulator (VR) has recently shown to be a nontrivial part of the total energy consumption and has been previously overlooked. In this paper, we propose an overall energy optimization method for the system that minimizes both per-core energy consumption and VR energy consumption using dynamic voltage frequency scaling and VR phase scaling by solving a comprehensive convex model. In order to improve the accuracy of the task latency model, a new task model considering both computation and memory access of the task is also developed. Furthermore, for better scalability and lower online overhead, we decompose our proposed convex method into two stages: 1) an offline stage and 2) an online stage. During the offline stage, we explore the convex model by assuming different numbers of active phases of the VR, various workload pressures and workload characteristics to collect the optimal frequency assignments under different scenarios. During the online stage, the specific frequency assignment for cores and optimal active phase number of the VR are selected and applied based on the actual workload pressure and its characteristics running on the cores. Experiments on real benchmarks show that when compared with the state-of-the-art approaches, which are oblivious to VR overheads and exploit slack time to achieve energy minimization, our method can achieve a significant energy saving of up to 22.4% with negligible online overhead.

中文翻译：

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使用综合凸模型通过 DVFS 和 VR 相位缩放实现多核平台的能量最小化

由于持续的技术扩展，能源管理是多核处理器中的一个关键挑战。以前的方法主要集中在处理器内核的能量最小化上。然而，片外电压调节器 (VR) 的能量开销最近被证明是总能量消耗的一个重要部分，之前一直被忽视。在本文中，我们为系统提出了一种整体能量优化方法，通过求解综合凸模型，使用动态电压频率缩放和 VR 相位缩放来最小化每核能耗和 VR 能耗。为了提高任务延迟模型的准确性，还开发了一种同时考虑任务计算和内存访问的新任务模型。此外，为了更好的可扩展性和更低的在线开销，我们将我们提出的凸方法分解为两个阶段：1）离线阶段和 2）在线阶段。在离线阶段，我们通过假设 VR 的不同活动阶段数、各种工作负载压力和工作负载特征来探索凸模型，以收集不同场景下的最佳频率分配。在在线阶段，根据实际工作负载压力及其在核心上运行的特点，选择并应用VR的特定核心频率分配和最佳活动阶段数。在真实基准上的实验表明，与忽略 VR 开销并利用松弛时间实现能源最小化的最先进方法相比，我们的方法可以实现高达 22.4% 的显着节能，而在线可忽略不计高架。