首页> 外文会议>Euromicro Conference on Real-Time Systems >A WCET-oriented static branch prediction scheme for real time systems
【24h】

A WCET-oriented static branch prediction scheme for real time systems

机译:用于实时系统的WCET导向的静态分支预测方案

获取原文
获取外文期刊封面目录资料

摘要

Branch prediction mechanisms are becoming commonplace within current generation processors. Dynamic branch predictors, albeit able to predict branches quite accurately in average, are becoming increasingly complex. Thus, determining their worst-case behavior, which is highly recommended for real-time applications, is getting increasingly difficult and error-prone, and may even be soon impossible for the most complex branch predictors. In contrast, static branch predictors are inherently predictable, to the detriment of a lower prediction accuracy. In this paper, we propose a WCET-oriented static branch prediction scheme. Unlike related work on compiler-directed static branch prediction, our scheme does not address program average-case performance (i.e. average-case branch misprediction rate) but addresses worst-case program performance instead (i.e. branch mispredictions which impact programs WCET estimates). Experimental results on a PowerPC 7451 architecture show that the estimated WCET can be decreased by up to 21 % (with an average improvement of 15%) as compared with the method where all branches are conservatively considered mispredicted. Our scheme, although applicable to any processor with support for static branch prediction, is specially suited to processors with complex dynamic predictors, for which safe and tight WCET estimate methods do not exist.
机译:分支预测机制在当前生成处理器内变得普遍。动态分支预测因子,尽管能够平均预测分支,但变得越来越复杂。因此,确定其最坏的行为,该行为强烈推荐用于实时应用,这越来越困难,并且易于出错,并且甚至可能很快就不可能对最复杂的分支预测值不可能。相比之下,静态分支预测器本质上可预测,损害预测精度较低。在本文中,我们提出了一种面向WCET的静态分支预测方案。与编译器定向静态分支预测的相关工作不同,我们的计划没有解决程序平均例子性能(即平均案例分支错误规定率),而是解决了最糟糕的程序性能(即,影响程序WCET估计的分支错误预测)。 PowerPC 7451架构上的实验结果表明,与所有分支保守被认为错误预测的方法相比,估计的WCET可以减少多达21%(平均提高15%)。我们的计划虽然适用于任何支持静态分支预测的处理器,但专门适用于具有复杂动态预测器的处理器,但是安全和紧密的WCET估计方法不存在。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号