Abstract

Inlining is an important optimization for programs that use procedural abstraction. Because inlining trades code size for execution speed, the effectiveness of an inlining algorithm is determined not only by its ability to recognize inlining opportunities but also by its discretion in exercising those opportunities. This paper presents a new inlining algorithm for higher-order languages that combines simple analysis techniques with demand-driven online transformation to achieve consistent and often dramatic performance gains in fast linear time. Benchmark results reported here demonstrate that this inlining algorithm is as effective as and significantly faster than offline, analysis-intensive algorithms recently described in the literature.

Citations