Phase-based adaptive recompilation in a JVM

Modern JIT compilers often employ multi-level recompila-tion strategies as a means of ensuring the most used code is also the most highly optimized, balancing optimization costs and expected future performance. Accurate selection of code to compile and level of optimization to apply is thus impor-tant to performance. In this paper we investigate the effect of an improved recompilation strategy for a Java virtual ma-chine. Our design makes use of a lightweight, low-level pro-filing mechanism to detect high-level, variable length phases in program execution. Phases are then used to guide adap-tive recompilation choices, improving performance. We de-velop both an offline implementation based on trace data and a self-contained online version. Our offline study shows an average speedup of 8.5 % and up to 21%, and our online sys-tem achieves an average speedup of 4.5%, up to 18%. We subject our results to extensive analysis and show that our design achieves good overall performance with high consis-tency despite the existence of many complex and interacting factors in such an environment