A modular memory optimization for synchronous data-flow languages

The generation of efficient sequential code for synchronous data-flow languages raises two intertwined issues: control and memory optimization. While the former has been extensively studied, for instance in the compilation of Lustre and Signal, the latter has only been addressed in a restricted manner. Yet, memory optimization becomes a pressing issue when arrays are added to such languages. This article presents a two-level solution to the memory optimization problem. It combines a compile-time optimization algorithm, reminiscent of register allocation, paired with language annotations on the source given by the designer. Annotations express in-place modifications and control where allocation is performed. Moreover, they allow external functions performing in-place modifications to be safely imported. Soundness of annotations is guaranteed by a semilinear type system and additional scheduling constraints. A key feature is that annotations for well-typed programs do not change the semantics of the language: removing them may lead to less efficient code but will not alter the semantics. The method has been implemented in a new compiler for a LUSTRE-like synchronous language extended with hierarchical automata and arrays. Experiments show that the proposed approach removes most of the unnecessary array copies, resulting in faster code that uses less memory.