Parallel Replication-Based Points-To Analysis

Pointer analysis is one of the most important static analyses during compilation. While several enhancements have been made to scale pointer analysis, the work on parallelizing the analysis itself is still in infancy. In this article, we propose a parallel version of context-sensitive inclusion-based points-to analysis for C programs. Our analysis makes use of replication of points-to sets to improve parallelism. In comparison to the former work on parallel points-to analysis, we extract more parallelism by exploiting a key insight based on monotonicity and unordered nature of flow-insensitive points-to analysis. By taking advantage of the nature of points-to analysis and the structure of constraint graph, we devise several novel optimizations to further improve the overall speed-up. We show the effectiveness of our approach using 16 SPEC 2000 benchmarks and five large open source programs that range from 1.2 KLOC to 0.5 MLOC. Specifically, our context-sensitive analysis achieves an average speed-up of 3.4× on an 8-core machine.

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