AI Potluck
Infrastructure / Compilers & Model Optimization

oneDNN

UXL Foundation

oneDNN 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
5.0
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.

Adoption

2 low confidence
2.0

4,036 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.

Capability

3 medium confidence
3.0

Banded 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.

Verified 2026-08-18