Using inter-procedural side-effect information in JIT optimizations

Side-effect analysis gives information about the set of locations that a statement may read or modify. This analysis can provide information useful in a compiler for performing aggressive optimizations. The impact of the use of side-effect analysis in compiler optimizations has been studied for programming languages such as Modula-3 and C, but no thorough investigation for Java has been done. We present a study of whether side-effect information improves performance in Java just-in-time (JIT) compilers, and if so, what level of analysis precision is needed. We also analyze the optimizations and benchmarks that benefit most from side-effect analysis.We used SPARK, the inter-procedural analysis component of the SOOT Java analysis and optimization framework, to compute side-effect information and encode it in class files. We modified Jikes RVM, a research JIT, to make use of side-effect analysis in various local and global analyses and optimizations such as local common sub-expression elimination, heap SSA, redundant load elimination and loop-invariant code motion. On the SpecJVM98 benchmarks, we measured the static number of memory operations removed, the dynamic counts of memory reads eliminated, and the execution time.Our results show that the use of side-effect analysis increases the number of static opportunities for load elimination by up to 98%, and reduces dynamic field read instructions by up to 27%. Side-effect information enabled speedups of up to 20% for some benchmarks. The main cause of the speedups is the use of side-effect information in load elimination. Finally, among the different levels of precision of side-effect information, a simple side-effect analysis is usually sufficient to obtain most of these speedups