Cache performance in Java virtual machines: a study of constituent phases

A. S. Rajan, Shiwen Hu, J. Rubio
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引用次数: 8

Abstract

This paper studies the level 1 cache performance of Java programs by analyzing memory reference traces of the SPECjvm98 applications executed by the Latte Java virtual machine. We study in detail Java programs' cache performance of different access types in three JVM phases, under two execution modes, using three cache configurations and two application data sets. We observe that the poor data cache performance in the JIT execution mode is caused by code installation, when the data write miss rate in the execution engine can be as high as 70%. In addition, code installation also deteriorates instruction cache performance during execution of translated code. High cache miss rate in garbage collection is mainly caused by large working set and pointer chasing of the garbage collector. A larger data cache works better on eliminating data cache read misses than write misses, and is more efficient on improving cache performance in the execution engine than in the garbage collection. As application data set increases in the JIT execution mode, instruction cache and data cache write miss rates of the execution engine decrease, while data cache read miss rate of the execution engine increases. On the other hand, impact of varying data set on cache performance is not as pronounced in the interpreted mode as in the JIT mode.
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Java虚拟机中的缓存性能:组成阶段的研究
本文通过分析由Latte Java虚拟机执行的SPECjvm98应用程序的内存引用轨迹,研究Java程序的一级缓存性能。我们使用三种缓存配置和两种应用程序数据集,在三个JVM阶段、两种执行模式下,详细研究了不同访问类型的Java程序的缓存性能。我们观察到,JIT执行模式下的数据缓存性能差是由代码安装引起的,此时执行引擎中的数据写缺失率高达70%。此外,代码安装还会在执行翻译后的代码期间降低指令缓存性能。垃圾回收中缓存缺失率高的主要原因是由于垃圾回收器的工作集大、指针追逐等。更大的数据缓存在消除数据缓存读失误方面比写失误更有效,并且在提高执行引擎中的缓存性能方面比在垃圾收集方面更有效。在JIT执行模式下,随着应用数据集的增加,执行引擎的指令缓存和数据缓存写丢失率降低,而数据缓存读丢失率增加。另一方面,不同数据集对缓存性能的影响在解释模式下不像在JIT模式下那么明显。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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