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Polygeist: Raising C to Polyhedral MLIR

William S. Moses
Lorenzo Chelini
Ruizhe Zhao
Oleksandr Zinenko
International Conference on Parallel Architectures and Compilation Techniques (PACT 2021), IEEE Computer Society (2021), pp. 45-59


We present Polygeist, a new compilation flow that connects MLIR infrastructure to cutting edge polyhedral optimization tools. It consists of a C and C++ frontend capable of converting a broad range of existing codes into MLIR suitable for polyhedral transformation and a bi-directional conversion between MLIR and OpenScop exchange format. The Polygeist/MLIR intermediate representation featuring high-level (affine) loop constructs and n-D arrays embedded into a single static assignment (SSA) substrate enables an unprecedented combination of SSA-based and polyhedral optimizations. We illustrate this by proposing and implementing two extra transformations: statement splitting and reduction parallelization. Our evaluation demonstrates that Polygeist outperforms on average both an LLVM IR-level optimizer (Polly) and a source-to-source state-of-the-art polyhedral compiler (Pluto) when exercised on Polybench/C benchmark suite in sequential (2.53× vs 1.41×, 2.34×) and parallel mode (9.47× vs 3.26×, 7.54×) thanks to the new representation and transformations.

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