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Shared resource aware scheduling on power-constrained tiled many-core processors

机译:功耗受限的平铺多核处理器上的共享资源感知调度

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Power management through dynamic core, cache and frequency adaptation is becoming a necessity in today's power-constrained many-core environments. Unfortunately, as core count grows, the complexity of both the adaptation hardware and the power management algorithms increases exponentially. This calls for hierarchical solutions, such as on-chip voltage regulators per-tile rather than per-core, along with multi-level power management. As power-driven adaptation of shared resources affects multiple threads at once, the efficiency in a tile-organized many-core processor architecture hinges on the ability to co-schedule compatible threads to tiles in tandem with hardware adaptations per tile and per core. In this paper, we propose a two-tier hierarchical power management methodology to exploit per-tile voltage regulators and clustered last-level caches. In addition, we include a novel thread migration layer that (ⅰ) analyzes threads running on the tiled many-core processor for shared resource sensitivity in tandem with core, cache and frequency adaptation, and (ⅱ) co-schedules threads per tile with compatible behavior. On a 256-core setup with 4 cores per tile, we show that adding sensitivity-based thread migration to a two-tier power manager improves system performance by 10% on average (and up to 20%) while using 4× less on-chip voltage regulators. It also achieves a performance advantage of 4.2% on average (and up to 12%) over existing solutions that do not take DVFS sensitivity into account.
机译:在当今功耗受限的多核环境中,通过动态内核,高速缓存和频率自适应进行电源管理已成为必需。不幸的是,随着内核数量的增加,适配硬件和电源管理算法的复杂性呈指数增长。这就要求采用分层解决方案,例如每瓦片而不是每核的片上稳压器,以及多级电源管理。由于功率驱动的共享资源适配会立即影响多个线程,因此,以图块组织的多核处理器体系结构的效率取决于能否将兼容的线程与每个图块和每个核心的硬件适配一起共同调度到图块。在本文中,我们提出了一种两层的分层电源管理方法,以利用每块电压调节器和群集的末级缓存。此外,我们还包括一个新颖的线程迁移层,该层可以分析在分片多核处理器上运行的线程,以与内核,高速缓存和频率自适应一并分析共享资源的敏感性,以及(ⅱ)通过兼容的方式对每个分片共同调度线程行为。在每瓦片4核的256核设置中,我们表明,将基于敏感度的线程迁移添加到两层电源管理器中,平均可将系统性能提高10%(最高可达20%),而将使用性能降低4倍,芯片稳压器。与不考虑DVFS敏感性的现有解决方案相比,该解决方案还具有平均4.2%(最多12%)的性能优势。

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