Selective Lambda Lifting

TL;DR

This paper revisits selective lambda lifting as an optimization in modern functional language compilers, proposing heuristics and static analysis to identify beneficial lifting opportunities, resulting in modest speedups in Haskell benchmarks.

Contribution

It introduces heuristics and static analysis for selective lambda lifting in modern compilers, enhancing code optimization strategies.

Findings

Modest speedups observed in Haskell benchmarks.

Heuristics effectively identify beneficial lifting opportunities.

Static analysis estimates impact on heap allocations.

Abstract

Lambda lifting is a well-known transformation, traditionally employed for compiling functional programs to supercombinators. However, more recent abstract machines for functional languages like OCaml and Haskell tend to do closure conversion instead for direct access to the environment, so lambda lifting is no longer necessary to generate machine code. We propose to revisit selective lambda lifting in this context as an optimising code generation strategy and conceive heuristics to identify beneficial lifting opportunities. We give a static analysis for estimating impact on heap allocations of a lifting decision. Performance measurements of our implementation within the Glasgow Haskell Compiler on a large corpus of Haskell benchmarks suggest modest speedups.