Structured Combinators for Efficient Graph Reduction

Combinators have a long history in mathematics, logic and computer science, as simple primitive symbols with which complex relationships can be described. In practice, this simplicity comes with a cost, impacting the performance of combinator-based languages and computers. We propose a generalized representation for combinators, not as primitives, but as self-contained definitions, where the structure of their graph-reduction semantics is explicit. For a sample of 798 unique lambda-terms from common benchmark programs, we show that
structured
combinators can improve the quality of compiled code, generating smaller and more efficient graphs, while translating seamlessly to a machine-friendly encoding, as part of the open-source
fun
instruction-set architecture.