Auto-Tuning the Java Virtual Machine

Abstract

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.