首页> 外文会议>9th ACM SIGSOFT-SIGPLAN workshop on program analysis for software tools and engineering 2010 >Interprocedural Induction Variable Analysis based on Interprocedural SSA Form IR
【24h】

Interprocedural Induction Variable Analysis based on Interprocedural SSA Form IR

机译:基于过程间SSA形式IR的过程间归纳变量分析

获取原文
获取原文并翻译 | 示例

摘要

The induction variable analysis is a fundamental component of loop optimizations in compilers. Algorithms in literature and implementations in free-source compilers such as GCC and LLVM rely on SSA form IR. However, only the uses of scalar stack variables whose address is not taken are replaced with a single definition in the SSA form IR. In this paper, we describe how Interprocedural SSA (ISSA) form IR can be leveraged to extend the induction variable analysis interprocedurally to: globals, singleton heap variables, record elements, and files. We implemented our induction variable analysis and compared it against the LLVM infrastructure for a set of MediaBench and SPEC2K benchmarks. We observed an average increase of 8.1% and 58.4% in the number of polynomial and monotonic induction variables, respectively. Furthermore, due to ISSA form IR and our induction variable analysis we computed 1.02 times more constant tripcounts and 2.06 times more loop invariant tripcounts.
机译:归纳变量分析是编译器中循环优化的基本组成部分。文献中的算法和诸如GCC和LLVM之类的免费源编译器中的实现均依赖于IR的SSA。但是,仅将未使用地址的标量堆栈变量的使用替换为SSA形式IR中的单个定义。在本文中,我们描述了如何利用过程间SSA(ISSA)形式的IR将过程间的归纳变量分析扩展到:全局变量,单例堆变量,记录元素和文件。我们实施了归纳变量分析,并将其与LLVM基础结构进行了比较,以得出一组MediaBench和SPEC2K基准测试。我们观察到多项式和单调归纳变量的数量分别平均增加了8.1%和58.4%。此外,由于是ISSA形式的IR和我们的归纳变量分析,我们计算出的恒定行程数要多1.02倍,循环不变行程数要多2.06倍。

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