kernelfoundry 0.1.2

A Python package for kernel testing

KernelFoundry

KernelFoundry is a Python package for defining and evaluating GPU kernel tasks.

This repository provides the task-side test harness used in kernel generation workflows:

• A base task interface (kernelfoundry.custom_test.CustomTest) for implementing task-specific build and pytest test logic.
• Build helpers for compiling candidate kernels into PyTorch extensions (via Torch or icpx).
• Pytest fixtures for correctness/performance runs and collecting runtime data.
• Validation helpers (assert_allclose, cosine similarity, and related utilities).
• Runtime and machine-info helpers for benchmarking and metadata capture.

In other words, this package is what you use to author tasks and evaluate generated kernels. The external orchestration layers (for example, UI/services that generate candidates) are separate from this repo.

Typical workflow

1. Create a task test class by deriving from kernelfoundry.custom_test.CustomTest.
2. Implement build logic (optional) and correctness/performance tests.
3. Compile candidate kernel code with compile_torch_extension(...).
4. Run pytest to validate correctness and collect benchmark timings.

KernelFoundry supports SYCL, OpenCL and CUDA kernels.

Installation

Install the package and basic dependencies with

pip install .

The package requires Python 3.10+ (we commonly use Python 3.12). Install into a virtual environment if desired.

The kernelfoundry package has minimal core dependencies. Depending on your task, you may also need framework/toolchain dependencies (for example PyTorch and GPU toolchains) to compile and test kernels locally.

To run PyTorch-based tasks, install torch appropriate for your hardware:

# on Intel hardware:
pip install torch==2.9.0 --index-url https://download.pytorch.org/whl/xpu
# on NVIDIA hardware:
pip install torch==2.9.0 --index-url https://download.pytorch.org/whl/cu129

Documentation

API documentation is available and can be built using Sphinx. To build the documentation:

pip install .[docs]
cd docs
make html

The generated documentation will be in docs/_build/html/. See the docs/README.md for more information.