Energy Discounted Computing on Multicore Smartphones
Energy Discounted Computing on Multicore Smartphones
复制标题
多核智能手机上的能源折扣计算
DOI：
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
Kai Shen
中科院分区：
文献类型：
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作者：
Meng Zhu;Kai Shen
多核处理器不是能量成比例的：激活共享资源的第一个运行的CPU内核比每个额外的内核产生更高的功耗成本。另一方面，典型的智能手机应用程序表现出很少的并行性，因此，当一个核心被交互式应用程序激活时，其他核心的计算资源可以以极低的能量折扣获得。通过非节省工作的调度，我们利用能源折扣的共同运行机会来处理不涉及直接用户交互的智能手机任务（例如，云备份的数据压缩/加密、后台感知和离线字节码编译）。我们表明，对于最优的协同运行能量折扣，尽最大努力的处理必须不提高整个系统的电源状态（具体来说，不减少多核CPU空闲状态，不增加核心频率，不影响系统挂起时间）。此外，我们使用可用的ARM性能计数器来识别多核处理器上的共同运行资源争用，并在干扰交互性时限制最佳努力任务。在多核智能手机上的实验结果表明，我们可以在最努力的任务处理中达到高达63%的能量折扣，并且对交互式应用程序的性能影响很小。
Multicore processors are not energy proportional: the first running CPU core that activates shared resources incurs much higher power cost than each additional core does. On the other hand, typical smartphone applications exhibit little parallelism and therefore when one core is activated by an interactive application, computing resources at other cores are available at a deep energy discount. By non-work-conserving scheduling, we exploit energy-discounted co-run opportunities to process best-effort smartphone tasks that involve no direct user interaction (e.g., data compression / encryption for cloud backup, background sensing, and offline bytecode compilation). We show that, for optimal co-run energy discount, the best-effort processing must not elevate the overall system power state (specifically, no reduction of the multicore CPU idle state, no increase of the core frequency, and no impact on the system suspension period). In addition, we use available ARM performance counters to identify co-run resource contention on the multicore processor and throttle best-effort task when it interferes with interactivity. Experimental results on a multicore smartphone show that we can reach up to 63% energy discount in the best-effort task processing with little performance impact on the interactive applications.