Speculative execution via address prediction and data prefetching
Speculative execution via address prediction and data prefetching
复制标题
通过地址预测和数据预取进行推测执行
DOI：
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发表时间：
1997
期刊：
影响因子：
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通讯作者：
Antonio González
中科院分区：
文献类型：
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作者：
José González;Antonio González
数据依赖已经成为当前超标量处理器的主要瓶颈之一。数据推测作为一种避免数据依赖带来的排序的机制正变得越来越流行。加载和存储是非常好的数据推测候选对象，因为它们的有效地址具有规则的行为，而且它们具有高度的可预测性。在本文中，我们提出了一种称为地址预测和数据预取的机制，它允许加载指令在解码阶段获得它们的数据。此外，还对加载和存储指令的有效地址进行了预测。这些指令和那些依赖于它们的指令是推测性执行的。这项技术已经在具有真实配置的无序处理器上进行了评估。性能提升平均约为19%，某些基准测试的性能提升幅度要高得多(高达35%)。
Data dependencies have become one of the main bottlenecks of current superscalar processors. Data speculation is gaining popularity as a mechanism to avoid the ordering imposed by data dependencies. Loads and stores are very good candidates for data speculation since their effective address has a regular behavior and then, they are highly predictable. In this paper we propose a mechanism called Address Prediction and Data Prefetching that allows load instructions to obtain their data at the decode stage. Besides, the effective address of load and store instructions is also predicted. These instructions and those dependent on them are speculatively executed. The technique has been evaluated for an out-of-order processor with a realistic configuration. The performance gain is about 19% in average and it is much higher for some benchmarks (up to 35%).