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Application behavior aware re-reference interval prediction for shared LLC

机译:应用程序行为意识到共享LLC的重新参考间隔预测

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In modern CMPs, Last Level Cache (LLC) is shared among cores for better utilization. Interference among data, mapped from multiple cores, increases conflict misses in shared LLCs. Such interference is highly dependent on cache behavior of applications and access rate difference among them. We observe that interference among applications is not eliminated completely even using existing state-of-the-art mechanism for applications having high cache access rate difference and different memory characteristic. Applications with highly diverse cache behavior can be observed in homogeneous as well as heterogeneous multicore processors. Streaming applications, having high access rate, can still interfere with cache friendly applications having low access rate. We propose Application behavior aware replacement policy that predicts re-reference interval of the block based on block locality as well as application behavior. By providing more priority to application behavior over cache block locality, we reduce interference between streaming applications and cache friendly applications. Our evaluation on set of SPEC CPU2006 workloads running on CMP with shared LLC shows that proposed replacement policy outperforms the state-of-the-art replacement policy, on throughput metric. We achieve performance gain up to 16.2% over SRRIP for application mixes of cache-friendly and streaming applications. Our replacement policy achieves maximum of 59.9% reduction in number of misses as compared to SRRIP with average misses per kilo instructions (mpki) reduction of 5.9% over SRRIP.
机译:在现代CMP中,最后一级缓存(LLC)是共享核心,以便更好地利用。从多个核心映射的数据之间的干扰会增加共享LLC中的冲突未命中。这种干扰高度依赖于应用程序的缓存行为和它们之间的访问率差异。我们观察到,即使使用具有高高速缓存访​​问率差和不同存储器特性的应用程序,也不会完全消除应用之间的干扰。可以在同质化以及异构多核处理器中观察到具有高度多样化的缓存行为的应用。具有高访问率的流式应用程序仍然可以干扰具有低接入率的缓存友好应用。我们提出了应用程序行为意识到替换策略,该替换策略基于块局部性以及应用程序行为预测块的重新参考间隔。通过在高速缓存块位置提供更多优先级应用程序行为,我们减少了流媒体应用程序和缓存友好应用程序之间的干扰。我们对带有共享LLC的CMP上运行的规范CPU2006工作负载的评估显示,提出的替代政策优于吞吐量度量的最先进的替换政策。我们在SRRIP达到高达16.2%的业绩,适用于缓存友好和流媒体应用的应用混合物。与SRRIP相比,我们的替代政策最多达到了未命中的次数减少了59.9%,平均每公斤指令(MPKI)减少了5.9%的SRRIP。

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