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Toward Inductive Synthesis of Compiler Heuristics: A Case Study with Register Allocation

DescriptionThere have been significant advances in machine learning-driven performance modeling in recent years. One key limitation of such approaches is that their success depends, to a large degree, on the formulation of the outcome or objective, which is typically done by human experts. In this paper, we propose a novel approach of automatically generating new optimization heuristics using inductive program synthesis. To explore the feasibility of this approach, we investigated the graph-coloring register allocation heuristic used in the state-of-the-art compilers today. In particular, we focused on the task of live range splitting. The results show that when using a Genetic Algorithm, we can obtain splitting heuristics that are within 10% of the optimal split after 202 generations.

Authors

Mohammad Ali

Texas State University