Containers on the Parallelization of General-Purpose Java Programs

Abstract

Static parallelization of general-purpose programs is still impossible, in general, due to their common use of pointers, irregular data structures, and complex control-flows. One promising strategy is to exploit parallelism at runtime. Runtime parallelization schemes, particularly data speculations, alleviate the need to statically prove independent computations at compile-time. However, studies show that many real-world applications exhibit limited speculative parallelism to offset the overhead and penalty of speculation schemes. This paper addresses this issue by using compiler analyses to compensate for speculative parallelizations. We focus on general-purpose Java programs with extensive use of Java container classes. In our scheme, compilers serve as a guideline of where to speculate by “lazily” detecting dependences that are mostly static, while leaving those that are more dynamic to runtime. We also propose techniques to enhance speculative parallelism in the programs. The experimental results show that, after eliminating static dependences, the four applications we study exhibit significant parallelism that can be gainfully exploited by a speculative parallelization system.