Contention-Aware Fair Scheduling for Asymmetric Single-ISA Multicore Systems
Contention-Aware Fair Scheduling for Asymmetric Single-ISA Multicore Systems
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DOI：
10.1109/tc.2018.2836418
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发表时间：
2018-12-01
影响因子：
3.7
通讯作者：
Prieto-Matias, Manuel
中科院分区：
文献类型：
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作者：
Garcia-Garcia, Adrian;Carlos Saez, Juan;Prieto-Matias, Manuel
非对称单指令集架构（ISA）多核处理器（AMPs）集成了高性能大核和低功耗小核，其每瓦特性能已被证明高于对称多核处理器。先前的研究表明，操作系统调度器在实现AMPs系统的潜力方面起着重要作用。虽然AMPs上的吞吐量优化已被广泛研究，但在这些平台上实现公平性对操作系统来说仍然是一个重大挑战。为此，调度器必须配备一种机制，能够在整个执行过程中准确跟踪工作负载中的每个应用程序在不同核心类型上运行时的进展情况。反过来，这种进展在很大程度上取决于一个应用程序在大核上相对于小核所获得的收益（或加速比），不同应用程序之间可能差异很大。虽然现有的具有公平性意识的调度器在跟踪进展时会考虑应用程序的相对加速比，但它们没有考虑到由于核心之间对共享资源（如末级缓存或内存总线）的争用而可能自然发生的性能下降。在本文中，我们提出了CAMPS，一种针对AMPs的具有争用感知的公平调度器，主要面向长时间运行的计算密集型工作负载。与其他方案不同，CAMPS不需要特殊的硬件扩展或特定于平台的加速比预测模型就能运行。我们的实验评估利用了Linux内核中的真实非对称硬件和调度器实现，结果表明，与最先进的具有公平性意识的操作系统级方案相比，CAMPS将公平性提高了多达11%，同时提供了更好的系统吞吐量。
Asymmetric single-ISA multicore processors (AMPs), which integrate high-performance big cores and low-power small cores, were shown to deliver higher performance per watt than symmetric multicores. Previous work has demonstrated that the OS scheduler plays an important role in realizing the potential of AMP systems. While throughput optimization on AMPs has been extensively studied, delivering fairness on these platforms still constitutes an important challenge to the OS. To this end, the scheduler must be equipped with a mechanism enabling to accurately track the progress that each application in the workload makes as it runs on the various core types throughout the execution. In turn, this progress largely depends on the benefit (or speedup) that an application derives on a big core relative to a small one, which may differ greatly across applications. While existing fairness-aware schedulers take application relative speedup into consideration when tracking progress, they do not cater to the performance degradation that may occur naturally due to contention on shared resources among cores, such as the last-level cache or the memory bus. In this paper, we propose CAMPS, a contention-aware fair scheduler for AMPs that primarily targets long-running compute-intensive workloads. Unlike other schemes, CAMPS does not require special hardware extensions or platform-specific speedup-prediction models to function. Our experimental evaluation, which leverages real asymmetric hardware and scheduler implementations in the Linux kernel, demonstrates that CAMPS improves fairness by up to 11 percent with respect to a state-of-the-art fairness-aware OS-level scheme, while delivering better system throughput.