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Polyhedral optimisation, a methodology that views nested loops as polyhedraand searches for their optimal transformation regarding specific objectives(parallelism, locality, etc.), sounds promising for mitigating difficulties inautomatically optimising hardware designs described by high-level synthesis(HLS), which are typically software programs with nested loops. Nevertheless,existing polyhedral tools cannot meet the requirements from HLS developers forplatform-specific customisation and software/hardware co-optimisation. Thispaper proposes $\phi_{sm}$ (phism), a polyhedral HLS framework built on MLIR,to address these challenges through progressive lowering multi-levelintermediate representations (IRs) from polyhedra to HLS designs.

Phism: Polyhedral High-Level Synthesis in MLIR