Polygeist: Raising C to Polyhedral MLIR
Polygeist: Raising C to Polyhedral MLIR
复制标题
Polygeist：将 C 提升为多面体 MLIR
DOI：
--
复制
发表时间：
2021
期刊：
影响因子：
--
通讯作者：
O. Zinenko
中科院分区：
文献类型：
--
作者：
William S. Moses;Lorenzo Chelini;Ruizhe Zhao;O. Zinenko
我们提出了Polygeist，这是一种新的编译流程，它将MLIR编译器基础设施与尖端的多面体优化工具连接起来。它由一个C和C++前端组成，能够将广泛的现有代码转换为适合多面体转换的MLIR，并在MLIR和OpenScope交换格式之间进行双向转换。Polygeist/MLIR中间表示具有高级(仿射)环路构造和嵌入到单个静态赋值(SSA)基板中的n-D数组，实现了基于SSA和多面体优化的前所未有的组合。我们通过提出并实现两个额外的转换来说明这一点：语句拆分和约简并行。我们的评估表明，由于采用了新的表示和转换，Polygeist的性能在顺序(2.53x vs 1.41x，2.34x)和并行模式(9.47x vs 3.26x，7.54x)下以顺序(2.53x vs 1.41x，2.34x)运行时，平均表现优于LLVMIR级优化器(Polly)和源代码到源代码最先进的多面体编译器(Pluto)。
We present Polygeist, a new compilation flow that connects the MLIR compiler 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 the Polybench/C benchmark suite in sequential (2.53x vs 1.41x, 2.34x) and parallel mode (9.47x vs 3.26x, 7.54x) thanks to the new representation and transformations.