自动调优Java虚拟机

Sanath Jayasena, Milinda Fernando, Tharindu Rusira Patabandi, Chalitha Perera, C. Philips
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引用次数: 16

摘要

我们解决了使用运行时标志(参数)调优Java虚拟机(JVM)性能的问题。我们在研究中使用了hotspot JVM。由于hotspot JVM有超过600个标志可供选择,因此手动选择一个子集来最大化性能是不可行的。在之前的工作中,由于只调优了可调标志的一个子集,潜在的性能改进受到了限制。我们采用了一种不同的方法,并提出了hotspot Auto-tuner,它考虑了整个JVM和所有标志的影响。据我们所知,我们的自动调优器是第一个优化JVM整体性能的自动调优器。通过构建一个标志层次结构,我们将JVM标志组织成一个树状结构,这有助于我们解决对JVM各方面的依赖,如垃圾收集器算法和JIT编译,并有助于减少配置搜索空间。对SPECjvm2008和DaCapo基准测试的实验表明,我们可以优化hotspot JVM并获得显著的加速,16个SPECjvm2008启动程序平均提高了19%,其中三个程序在每个程序的最大调优时间为200分钟内显著提高了63%、51%和32%。基于200分钟的最小调优时间,13个DaCapo基准程序的平均性能改进为26%,最大改进为42%。
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Auto-Tuning the Java Virtual Machine
We address the problem of tuning the performance of the Java Virtual Machine (JVM) with run-time flags (parameters). We use the Hot Spot JVM in our study. As the Hot Spot JVM comes with over 600 flags to choose from, selecting a subset manually to maximize performance is infeasible. In prior work, the potential performance improvement is limited by the fact that only a subset of the tunable flags are tuned. We adopt a different approach and present the Hot Spot Auto-tuner which considers the entire JVM and the effect of all the flags. To the best of our knowledge, ours is the first auto-tuner for optimizing the performance of the JVM as a whole. We organize the JVM flags into a tree structure by building a flag-hierarchy, which helps us to resolve dependencies on aspects of the JVM such as garbage collector algorithms and JIT compilation, and helps to reduce the configuration search-space. Experiments with the SPECjvm2008 and DaCapo benchmarks show that we could optimize the Hot Spot JVM with significant speedup, 16 SPECjvm2008 startup programs were improved by an average of 19% with three of them improved dramatically by 63%, 51% and 32% within a maximum tuning time of 200 minutes for each. Based on a minimum tuning time of 200 minutes, average performance improvement for 13 DaCapo benchmark programs is 26% with 42% being the maximum improvement.
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