Phism：MLIR中的多面体高级综合
Phism: Polyhedral High-Level Synthesis in MLIR
摘要：
多面体优化，一种将嵌套循环视为多面体并搜索其关于特定目标（并行性，局部性等）的最佳转换的方法，听起来很有希望减轻自动优化高级综合（HLS）描述的硬件设计的困难，HLS通常是具有嵌套循环的软件程序。然而，现有的多面体工具无法满足HLS开发人员对平台特定定制和软件/硬件协同优化的要求。本文提出了$ϕ_{sm}$（phism），一个多面体HLS框架建立在MLIR，以解决这些挑战，通过逐步降低多层次的中间表示（IR）从多面体HLS设计。
英文摘要：
Polyhedral optimisation, a methodology that views nested loops as polyhedra and searches for their optimal transformation regarding specific objectives (parallelism, locality, etc.), sounds promising for mitigating difficulties in automatically 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 for platform-specific customisation and software/hardware co-optimisation. This paper proposes $ϕ_{sm}$ (phism), a polyhedral HLS framework built on MLIR, to address these challenges through progressive lowering multi-level intermediate representations (IRs) from polyhedra to HLS designs.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
