oneDNN
UXL FoundationoneDNN is a cross-platform performance library of deep-learning building blocks - convolutions, matrix multiplications, normalizations and fused primitives - implementing the oneAPI specification for the component. It is optimized for x86-64, AMD64 and 64-bit Arm CPUs and for Intel GPUs, and frameworks call it as their CPU kernel layer. The UXL Foundation hosts the project.
Verified 2026-08-18 via the GitHub API and the LICENSE body.
Openness
5 high confidence- license
- Apache-2.0(OSI)
- source
- public
- core-gated
- ungated
Apache-2.0 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.
- https://github.com/uxlfoundation/oneDNN/blob/main/LICENSE recorded 2026-08-18
LICENSE file is the verbatim Apache-2.0 text
- https://api.github.com/repos/uxlfoundation/oneDNN recorded 2026-08-18
Repo metadata - license spdx_id Apache-2.0, private false, archived false, default branch main - for uxlfoundation/oneDNN.
- https://github.com/uxlfoundation/oneDNN/blob/main/README.md recorded 2026-08-18
README describes a cross-platform performance library of deep-learning building blocks implementing the oneAPI specification, optimized for Intel 64, AMD64 and 64-bit Arm processors and Intel GPUs, with no paid tier, enterprise edition or license-key-gated build beside it.
Adoption
2 low confidence4,036 GitHub stars, which lands in the 1K-10K stars band of the stars scale, level 2. oneDNN is consumed as a C++ library vendored into frameworks rather than as a package, so no download channel measures it and the stars scale applies with its cap of 3.
- https://api.github.com/repos/uxlfoundation/oneDNN recorded 2026-08-18
Repo metadata - stargazers_count = 4,036 - for uxlfoundation/oneDNN.
Capability
3 medium confidenceBanded on the category feature matrix as performance-critical kernel and operator library. Placed two bands below the apache-tvm anchor, on a matrix that bands on how much of the model-to-hardware transformation pipeline a product performs, over how many inputs and targets.
- https://github.com/uxlfoundation/oneDNN/blob/main/README.md recorded 2026-08-18
README still documents a cross-platform performance library of deep-learning building blocks implementing the oneAPI specification, optimized for Intel 64, AMD64 and 64-bit Arm processors and Intel GPUs.
Verified 2026-08-18