Despite decades of research, conditional branch mispredictions still pose a significant problem for performance. Moreover, limit studies on infinite size predictors show that many of the remaining branches are impossible to predict by current strategies. Our work focuses on mitigating performance loss in the face of impossible to predict branches. This paper presents a dynamic merge point predictor, which uses instructions fetched on the wrong path of the branch to dynamically detect the merge point. Our predictor locates the merge point with an accuracy of 95%, even when faced with branches whose direction is impossible to predict. Furthermore, we introduce a novel confidence-cost system, which identifies costly hard-to-predict branches. Our complete system replaces 58% of all branch mispredictions with a correct merge point prediction, effectively reducing MPKI by 43%. This result demonstrates the potential for dynamic merge point prediction to significantly improve performance.

中文翻译：

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动态合并点预测

尽管进行了数十年的研究，但条件分支错误预测仍然对性能构成重大问题。此外，对无限大小预测器的限制研究表明，目前的策略无法预测许多剩余的分支。我们的工作重点是在面对无法预测的分支时减轻性能损失。本文提出了一种动态合并点预测器，它使用在分支的错误路径上获取的指令来动态检测合并点。我们的预测器以 95% 的准确率定位合并点，即使面对方向无法预测的分支也是如此。此外，我们引入了一种新颖的置信成本系统，它可以识别成本高昂的难以预测的分支。我们的完整系统用正确的合并点预测替换了所有分支错误预测的 58%，有效地将 MPKI 降低了 43%。该结果表明动态合并点预测具有显着提高性能的潜力。