Asymmetric multicore processors (AMP) offer multiple types of cores under the same programming interface. Extracting the full potential of AMPs requires intelligent scheduling decisions, matching each thread with the right kind of core, the core that will maximize performance or minimize wasted energy for this thread. Existing OS schedulers are not up to this task. While they may handle certain aspects of asymmetry in the system, none can handle all runtime factors affecting AMPs for the general case of multi-threaded multi-programmed workloads. We address this problem by introducing COLAB, a general purpose asymmetry-aware scheduler targeting multi-threaded multi-programmed workloads. It estimates the performance and power of each thread on each type of core and identifies communication patterns and bottleneck threads. With this information, the scheduler makes coordinated core assignment and thread selection decisions that still provide each application its fair share of the processor’s time. We evaluate our approach using both the GEM5 simulator on four distinct big.LITTLE configurations and a development board with ARM Cortex-A73/A53 processors and mixed workloads composed of PARSEC and SPLASH2 benchmarks. Compared to the state-of-the art Linux CFS and AMP-aware schedulers, we demonstrate performance gains of up to 25 and 5 to 15 percent on average, together with an average 5 percent energy saving depending on the hardware setup.

中文翻译：

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用于非对称多核处理器的协作式异构感知操作系统调度程序

非对称多核处理器（AMP）在同一编程接口下提供多种类型的核。提取AMP的全部潜力需要智能的调度决策，将每个线程与正确的内核相匹配，该内核将使该线程的性能最大化或能量浪费最小。现有的OS调度程序无法完成此任务。尽管它们可以处理系统中某些方面的不对称性，但是对于多线程多程序工作负载的一般情况，它们都无法处理影响AMP的所有运行时因素。我们通过引入COLAB（一种针对多线程多程序工作负载的通用不对称感知调度程序）来解决此问题。它估计每种类型的内核上每个线程的性能和功能，并确定通信模式和瓶颈线程。有了这些信息，调度程序做出协调的内核分配和线程选择决策，这些决策仍为每个应用程序提供处理器时间的合理份额。我们在四个不同的big.LITTLE配置上使用GEM5仿真器，并在开发板上使用ARM Cortex-A73 / A53处理器以及由PARSEC和SPLASH2基准组成的混合工作负载，来评估我们的方法。与最先进的Linux CFS和AMP感知调度程序相比，我们展示了平均25％的性能提升以及5％至15％的性能提升，并且根据硬件设置平均可节省5％的能耗。LITTLE配置和带有ARM Cortex-A73 / A53处理器以及由PARSEC和SPLASH2基准组成的混合工作负载的开发板。与最先进的Linux CFS和AMP感知调度程序相比，我们展示了平均25％的性能提升以及5％至15％的性能提升，并且根据硬件设置平均可节省5％的能耗。LITTLE配置和带有ARM Cortex-A73 / A53处理器以及由PARSEC和SPLASH2基准组成的混合工作负载的开发板。与最先进的Linux CFS和AMP感知调度程序相比，我们展示了平均25％的性能提升以及5％至15％的性能提升，并且根据硬件设置平均可节省5％的能耗。