RADAR: Runtime-assisted dead region management for last-level caches

M. Manivannan, Vassilis D. Papaefstathiou, M. Pericàs, P. Stenström
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引用次数: 18

Abstract

Last-level caches (LLCs) bridge the processor/memory speed gap and reduce energy consumed per access. Unfortunately, LLCs are poorly utilized because of the relatively large occurrence of dead blocks. We propose RADAR, a hybrid static/dynamic dead-block management technique that can accurately predict and evict dead blocks in LLCs. RADAR does dead-block prediction and eviction at the granularity of address regions supported in many of today's task-parallel programming models. The runtime system utilizes static control-flow information about future region accesses in conjunction with past region access patterns to make accurate predictions about dead regions. The runtime system instructs the cache to demote and eventually evict blocks belonging to such dead regions. This paper considers three RADAR schemes to predict dead regions: a scheme that uses control-flow information provided by the programming model (Look-ahead), a history-based scheme (Look-back) and a combined scheme (Look-ahead and Look-back). Our evaluation shows that, on average, all RADAR schemes outperform state-of-the-art hardware dead-block prediction techniques, whereas the combined scheme always performs best.
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雷达:最后一级缓存的运行时辅助死区管理
最后一级缓存(llc)弥合了处理器/内存速度的差距,并减少了每次访问所消耗的能量。不幸的是,有限责任公司很少被利用,因为死块的发生相对较多。我们提出了RADAR,这是一种静态/动态的死块管理技术,可以准确地预测和清除有限责任公司中的死块。RADAR在当前许多任务并行编程模型所支持的地址区域粒度上进行死块预测和清除。运行时系统利用关于未来区域访问的静态控制流信息,结合过去的区域访问模式,对死亡区域做出准确的预测。运行时系统指示缓存降级并最终驱逐属于此类死区的块。本文考虑了三种雷达死区预测方案:一种是利用规划模型提供的控制流信息的方案(前视),一种是基于历史的方案(后视),一种是前视和后视相结合的方案(前视和后视)。我们的评估表明,平均而言,所有RADAR方案都优于最先进的硬件死块预测技术,而组合方案总是表现最好。
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