@inproceedings{162b6f78186e4379b5522c003fadd7d6,
title = "The MLIR Transform Dialect Your Compiler Is More Powerful Than You Think",
abstract = "To take full advantage of a specific hardware target, performance engineers need to gain control on compilers in order to leverage their domain knowledge about the program and hardware. Yet, modern compilers are poorly controlled, usually by configuring a sequence of coarse-grained monolithic black-box passes, or by means of predefined compiler annotations/pragmas. These can be effective, but often do not let users precisely optimize their varying compute loads. As a consequence, performance engineers have to resort to implementing custom passes for a specific optimization heuristic, requiring compiler engineering expert knowledge. In this paper, we present a technique that provides fine-grained control of general-purpose compilers by introducing the Transform dialect, a controllable IR-based transformation system implemented in MLIR. The Transform dialect empowers performance engineers to optimize their various compute loads by composing and reusing existing—but currently hidden—compiler features without the need to implement new passes or even rebuilding the compiler. We demonstrate in five case studies that the Transform dialect enables precise, safe composition of compiler transformations and allows for straightforward integration with state-of-the-art search methods.",
keywords = "Controllable Compiler, MLIR, Transform Dialect, Transform Scripts",
author = "L{\"u}cke, {Martin Paul} and Oleksandr Zinenko and Moses, {William S.} and Michel Steuwer and Albert Cohen",
note = "This material is based upon work supported by the National Science Foundation under Grant No. 2346519. This work is also supported by the Alan Turing Institute.; 23rd ACM/IEEE International Symposium on Code Generation and Optimization, CGO 2025 ; Conference date: 01-03-2025 Through 05-03-2025",
year = "2025",
month = mar,
day = "1",
doi = "10.1145/3696443.3708922",
language = "English (US)",
series = "CGO 2025 - Proceedings of the 23rd ACM/IEEE International Symposium on Code Generation and Optimization",
publisher = "Association for Computing Machinery",
pages = "241--254",
editor = "Johannes Doerfert and Tobias Grosser and Hugh Leather and P.. Sadayappan",
booktitle = "CGO 2025 - Proceedings of the 23rd ACM/IEEE International Symposium on Code Generation and Optimization",
address = "United States",
}