• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>Proceedings of the ACM SIGPLAN workshop on Dynamic and adaptive compilation and optimization >Probabilistic data flow system with two-edge profiling
【24h】

Probabilistic data flow system with two-edge profiling

机译：具有两边分析的概率数据流系统

获取原文
获取原文并翻译 | 示例
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Traditionally optimization is done statistically independent of actual execution environments. For generating highly optimized code, however, runtime information can be used to adapt a program to different environments. In probabilistic data flow systems runtime information on representative input data is exploited to compute the probability with what data flow facts may hold. Probabilistic data flow analysis can guide sophisticated optimizing transformations resulting in better performance. In comparison classical data flow analysis does not take runtime information into account. All paths are equally weighted irrespectively whether they are never, heavily, or rarely executed.>In this paper we present the best solution what we can theoretically obtain for probabilistic data flow problems and compare it with the state-of-the-art one-edge approach. We show that the differences can be considerable and improvements are crucial. However, the theoretically best solution is too expensive in general and feasible approaches are required. In the sequel we develop an efficient approach which employs two-edge profiling and classical data flow analysis. We show that the results of the two-edge approach are significantly better than the state-of-the-art one-edge approach.
机译：传统上，优化是在统计上独立于实际执行环境进行的。但是，为了生成高度优化的代码，可以使用运行时信息使程序适应不同的环境。在概率数据流系统中，利用代表输入数据上的运行时信息来计算数据流事实可能具有的概率。概率数据流分析可以指导复杂的优化转换，从而提高性能。相比之下，经典数据流分析未考虑运行时信息。无论它们是永不执行，不执行还是很少执行，所有路径的权重均相等。

在本文中，我们提出了最佳解决方案，我们可以从理论上获得概率数据流问题的解决方案，并将其与最新的单边方法。我们表明，差异可能很大，改进至关重要。但是，理论上最好的解决方案通常太昂贵，因此需要可行的方法。在后续文章中，我们开发了一种有效的方法，该方法采用了两边分析和经典数据流分析。我们显示，两边缘方法的结果明显优于最新的一边缘方法。

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