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首页> 外文期刊>IEEE Transactions on Parallel and Distributed Systems >TLB-Based Temporality-Aware Classification in CMPs with Multilevel TLBs
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TLB-Based Temporality-Aware Classification in CMPs with Multilevel TLBs

机译：具有多级TLB的CMP中基于TLB的时间感知分类

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摘要

Recent proposals are based on classifying memory accesses into private or shared in order to process private accesses more efficiently and reduce coherence overhead. The classification mechanisms previously proposed are either not able to adapt to the dynamic sharing behavior of the applications or require frequent broadcast messages. Additionally, most of these classification approaches assume single-level translation lookaside buffers (TLBs). However, deeper and more efficient TLB hierarchies, such as the ones implemented in current commodity processors, have not been appropriately explored. This paper analyzes accurate classification mechanisms in multilevel TLB hierarchies. In particular, we propose an efficient data classification strategy for systems with distributed shared last-level TLBs. Our approach classifies data accounting for temporal private accesses and constrains TLB-related traffic by issuing unicast messages on first-level TLB misses. When our classification is employed to deactivate coherence for private data in directory-based protocols, it improves the directory efficiency and, consequently, reduces coherence traffic to merely 53.0 percent, on average. Additionally, it avoids some of the overheads of previous classification approaches for purely private TLBs, improving average execution time by nearly 9 percent for large-scale systems.
机译：最近的提议基于将存储器访问分为私有访问或共享访问，以便更有效地处理私有访问并减少一致性开销。先前提出的分类机制要么无法适应应用程序的动态共享行为，要么需要频繁广播消息。此外，大多数这些分类方法都采用单级转换后备缓冲区（TLB）。但是，还没有适当地探索更深，更有效的TLB层次结构，例如在当前商品处理器中实现的层次结构。本文分析了多层TLB层次结构中的准确分类机制。特别是，我们为具有分布式共享末级TLB的系统提出了一种有效的数据分类策略。我们的方法通过对第一级TLB未命中发出单播消息，对临时私有访问的数据计费进行分类，并限制与TLB相关的流量。当使用我们的分类来停用基于目录的协议中的私有数据的一致性时，它可以提高目录效率，因此平均将一致性流量降低到仅53.0％。另外，它避免了纯私有TLB先前分类方法的一些开销，从而将大型系统的平均执行时间缩短了近9％。

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