The MLIR Transform Dialect

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.

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Publication Details

Published
2025-02-22
DOI
https://doi.org/10.1145/3696443.3708922
Citations
6
Primary Topic
Natural Language Processing Techniques
Type
article
Field-Weighted Citation Impact
14.89
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article

The MLIR Transform Dialect

Michel Steuwer, Oleksandr Zinenko, Albert Cohen, William S. Moses et al.
6 citations
Natural Language Processing Techniques
14.89
article

The MLIR Transform Dialect

Michel Steuwer, Oleksandr Zinenko, Albert Cohen, William S. Moses, Martin Paul Lücke
article en
6 citations

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.

Google (United States) (US), University of Illinois Urbana-Champaign (US), Technische Universität Berlin (DE), University of Edinburgh (GB)
Openalex Percentile: Top 1%
Natural Language Processing Techniques
14.89
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The MLIR Transform Dialect — Michel Steuwer, Oleksandr Zinenko, et al. · (2025) | TGRS Research Map | TGRS