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Infrastructure / Compilers & Model Optimization

CUDA Tile IR

NVIDIA

CUDA Tile IR is NVIDIA's MLIR-based intermediate representation and compiler infrastructure for CUDA kernel optimization, providing a tile dialect, Python bindings and a bytecode format for expressing and lowering tile-based tensor computations that target NVIDIA tensor core units.

Verified 2026-09-02 via the GitHub API and the LICENSE body.

Openness

5 high confidence
5.0
license
Apache-2.0-WITH-LLVM-exception(OSI)
source
public
core-gated
ungated

Apache-2.0-WITH-LLVM-exception license body confirmed. The repository is public and unarchived and builds the whole product, and the README describes no paid tier, enterprise edition or license-gated build beside it, so source is public and the core ungated.

Adoption

2 low confidence
2.0

1,021 GitHub stars, which lands in the 1K-10K stars band of the stars scale, level 2. The `cuda-tile` package on PyPI (about 3.7M downloads a month) is cuTile Python, published from the separate nvidia/cutile-python repository and pulled in as a dependency of the CUDA Python stack, so it measures a different project's installs rather than this compiler, which the README builds from source with CMake against an LLVM install. No package channel of its own is published, which leaves the stars scale and its cap of 3.

Capability

4 medium confidence
4.0

One band below the apache-tvm anchor: a full compiler infrastructure - IR, bindings, lowering and conformance testing - narrowed to one vendor's targets (NVIDIA GPUs) rather than apache-tvm's multi-vendor retargetability.

  • https://github.com/NVIDIA/cuda-tile/blob/main/README.md recorded 2026-09-02

    README describes CUDA Tile IR as an MLIR-based IR and compiler infrastructure for CUDA kernel optimization, aligned with the CUDA Toolkit 13.1 release, with no paid tier, enterprise edition or license-gated build beside the published source.

Verified 2026-09-02