Parallel Pointer Analysis with CFL-Reachability

This paper presents the first parallel implementation of pointer analysis with Context-Free Language (CFL) reachability, an important foundation for supporting demand queries in compiler optimisation and software engineering. Formulated as a graph traversal problem (often with context- and field-sensitivity for desired precision) and driven by queries (issued often in batch mode), this analysis is non-trivial to parallelise. We introduce a parallel solution to the CFL-reachability-based pointer analysis, with context- and field-sensitivity. We exploit its inherent parallelism by avoiding redundant graph traversals with two novel techniques, data sharing and query scheduling. With data sharing, paths discovered in answering a query are recorded as shortcuts so that subsequent queries will take the shortcuts instead of re-traversing its associated paths. With query scheduling, queries are prioritised according to their statically estimated dependences so that more redundant traversals can be further avoided. Evaluated using a set of 20 Java programs, our parallel implementation of CFL-reachability-based pointer analysis achieves an average speedup of 16.2X over a state-of-the-art sequential implementation on 16 CPU cores.