Inlining-Benefit Prediction with Interprocedural Partial Escape Analysis

Abstract

Inlining is the primary facilitating mechanism for intraprocedural Partial Escape Analysis (PEA), which allows for the removal of object allocations on a branch-by-branch basis and is critical for performance in object-oriented languages. Prior work used interprocedural Escape Analysis to make inlining decisions, but it discarded control-flow-sensitivity when crossing procedure boundaries, and did not weigh other metrics to model the cost-benefit of inlining, resulting in unpredictable inlining decisions and suboptimal performance. Our work addresses these issues and introduces a novel Interprocedural Partial Escape Analysis algorithm (IPEA) to predict the inlining benefits, and improve the cost-benefit model of an existing optimization-driven inliner. We evaluate the implementation of IPEA in GraalVM Native Image, on industry-standard benchmark suites Dacapo, ScalaBench, and Renaissance. Out of 36 benchmarks with a geometric mean runtime improvement of 1.79%, 6 benchmarks achieve an improvement of over 5% with a geomean of 9.10% and up to 24.62%, while also reducing code size and compilation times compared to existing approaches.