Demonstrating a Future for MLIR-native DSL Compilers on a NumPy-like Example
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arXiv
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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2026
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| _version_ | 1866910168313233408 |
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| author | Friebel, Karl F. A. Ohlmann, Jascha A. Castrillon, Jeronimo |
| author_facet | Friebel, Karl F. A. Ohlmann, Jascha A. Castrillon, Jeronimo |
| contents | Compilers for general-purpose languages have been shown to be at a disadvantage when it comes to specialized application domains as opposed to their Domain-Specific Language (DSL) counterparts. However, the field of DSL compilers features little consolidation in terms of compiler frameworks and adjacent software ecosystems. As a result, considerable work is duplicated, lost to maintenance issues, or remains undiscovered, and most DSLs are never considered "production-ready". One notable development is the introduction of the Multi-Level Intermediate Representation (MLIR), which promises a similar impact on DSL compilers as LLVM had on general-purpose tooling.
In this work, we present a NumPy-like DSL made for offloading numeric tensor kernels that is entirely MLIR-native. In a first for open-source, it implements all frontend actions and semantic analyses directly within MLIR. Most notably, this is made possible by our new dialect-agnostic MLIR type checker, created for the future of DSLs in MLIR. We implement a simple, yet effective, parallel-first lowering scheme that connects our language to another MLIR dataflow dialect for seamless offloading. We show that our approach performs well in real-world use cases from the domain of weather modeling and Computational Fluid Dynamics (CFD) in Fortran. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_19906 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Demonstrating a Future for MLIR-native DSL Compilers on a NumPy-like Example Friebel, Karl F. A. Ohlmann, Jascha A. Castrillon, Jeronimo Programming Languages Compilers for general-purpose languages have been shown to be at a disadvantage when it comes to specialized application domains as opposed to their Domain-Specific Language (DSL) counterparts. However, the field of DSL compilers features little consolidation in terms of compiler frameworks and adjacent software ecosystems. As a result, considerable work is duplicated, lost to maintenance issues, or remains undiscovered, and most DSLs are never considered "production-ready". One notable development is the introduction of the Multi-Level Intermediate Representation (MLIR), which promises a similar impact on DSL compilers as LLVM had on general-purpose tooling. In this work, we present a NumPy-like DSL made for offloading numeric tensor kernels that is entirely MLIR-native. In a first for open-source, it implements all frontend actions and semantic analyses directly within MLIR. Most notably, this is made possible by our new dialect-agnostic MLIR type checker, created for the future of DSLs in MLIR. We implement a simple, yet effective, parallel-first lowering scheme that connects our language to another MLIR dataflow dialect for seamless offloading. We show that our approach performs well in real-world use cases from the domain of weather modeling and Computational Fluid Dynamics (CFD) in Fortran. |
| title | Demonstrating a Future for MLIR-native DSL Compilers on a NumPy-like Example |
| topic | Programming Languages |
| url | https://arxiv.org/abs/2604.19906 |