Online feedback-directed optimization of Java
Online feedback-directed optimization of Java
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DOI：
10.1145/582419.582432
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发表时间：
2002-11
影响因子：
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通讯作者：
Matthew Arnold;M. Hind;B. Ryder
中科院分区：
文献类型：
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作者：
Matthew Arnold;M. Hind;B. Ryder
本文介绍了在线反馈指导的优化系统的实现。系统是全自动的；它不需要事先（离线）分析运行。它使用先前开发的低空仪器采样框架来收集控制流程边缘轮廓。此配置文件信息用于驱动几种传统的优化，以及用于执行反馈指导的控制流程节点拆分的新型算法。我们从经验上评估了该系统，并证明了高达17％的峰值性能的改善，同时保持间接较低，由于仪器的仪器，没有个人执行不超过2％。
This paper describes the implementation of an online feedback-directed optimization system. The system is fully automatic; it requires no prior (offline) profiling run. It uses a previously developed low-overhead instrumentation sampling framework to collect control flow graph edge profiles. This profile information is used to drive several traditional optimizations, as well as a novel algorithm for performing feedback-directed control flow graph node splitting. We empirically evaluate this system and demonstrate improvements in peak performance of up to 17% while keeping overhead low, with no individual execution being degraded by more than 2% because of instrumentation.