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arXiv:2002.11054cs.PL

MLIR: A Compiler Infrastructure for the End of Moore's Law

Chris Lattner, Mehdi Amini, Uday Bondhugula, Albert Cohen, Andy Davis, Jacques Pienaar, River Riddle, Tatiana Shpeisman, Nicolas Vasilache, Oleksandr Zinenko

Early discovery. Linked by one identifiable commenter. This paper is outside the main ranking; a mention is not an endorsement.

Abstract

This work presents MLIR, a novel approach to building reusable and extensible compiler infrastructure. MLIR aims to address software fragmentation, improve compilation for heterogeneous hardware, significantly reduce the cost of building domain specific compilers, and aid in connecting existing compilers together. MLIR facilitates the design and implementation of code generators, translators and optimizers at different levels of abstraction and also across application domains, hardware targets and execution environments. The contribution of this work includes (1) discussion of MLIR as a research artifact, built for extension and evolution, and identifying the challenges and opportunities posed by this novel design point in design, semantics, optimization specification, system, and engineering. (2) evaluation of MLIR as a generalized infrastructure that reduces the cost of building compilers-describing diverse use-cases to show research and educational opportunities for future programming languages, compilers, execution environments, and computer architecture. The paper also presents the rationale for MLIR, its original design principles, structures and semantics.

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Journal reference
DOI
Subjects
cs.PLProgramming Languages cs.LGMachine Learning

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Linked by 1 identifiable commenter in 1 comment across 1 thread, from Apr 2020 to Apr 2020. Found in 3 HN submissions from Feb 2020 to Aug 2021. Open submission discussions.

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Discussed in comments1 thread

    • I find it fascinating this research and MLIR[1] seem to have been developed independently around the same time. Figure 1 tells the same story in both papers. The authors mention the possibility of representing their concepts in MLIR, which could be really interesting. [1]…

      mikeurbachView on HNParent context

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