Nowadays, real-time applications need more and more hardware performance. This increasing performance demands the use of deterministic performance enhancement features such as static branch prediction. In this paper we propose a new technique which aims to use static branch prediction for worst-case execution time (WCET) reduction that can be applied on any processor that supports this type of prediction. The only requirement is the support of a WCET tool. This paper also describes how to estimate the maximum WCET reduction that can be obtained with static approaches. We show that our technique produces a slightly better result than a similar approach from the literature. We also compare WCET-centered techniques against standard compiler techniques not directly oriented to WCET reduction. We show that a very small or even no gain can be obtained with new techniques targeted to WCET reduction considering static branch prediction. That means the techniques considered in this paper are close to an optimal result. As a secondary contribution, we show that non WCET-aware techniques can also be used in real-time environments because they present good results and low complexity. We evaluate the prediction techniques using a set of examples from the Mälardalen WCET benchmarks.

中文翻译：

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关于使用静态分支预测来减少实时应用程序的最坏情况执行时间

如今，实时应用程序需要越来越多的硬件性能。这种不断提高的性能需要使用确定性的性能增强功能，例如静态分支预测。在本文中，我们提出了一种新技术，旨在使用静态分支预测来减少最坏情况执行时间 (WCET)，该技术可应用于支持此类预测的任何处理器。唯一的要求是支持 WCET 工具。本文还描述了如何估计可以通过静态方法获得的最大 WCET 减少量。我们表明，我们的技术产生的结果比文献中的类似方法略好。我们还将以 WCET 为中心的技术与不直接面向 WCET 缩减的标准编译器技术进行比较。我们表明，考虑到静态分支预测，使用针对 WCET 减少的新技术可以获得非常小甚至没有增益。这意味着本文中考虑的技术接近最佳结果。作为次要贡献，我们展示了非 WCET 感知技术也可以用于实时环境，因为它们具有良好的结果和低复杂性。我们使用来自 Mälardalen WCET 基准的一组示例来评估预测技术。