Baseten Kernel Library
Project description
b10-kernel
Baseten Kernel Library - High-performance GPU kernels for AI inference workloads.
Installation
From PyPI
pip install b10-kernel
Requirements:
- Python >= 3.12
- CUDA-compatible GPU and drivers
- PyTorch >= 2.8.0 with CUDA support
From Source
git clone <repository>
cd mp/kernels/b10-kernel
pip install -e .
For Development
# Install with test dependencies
pip install -e .[test]
# Install with all development dependencies
pip install -e .[dev]
Development guide
- Build the library from source
make build
make rebuild
- Run unit tests
make test
- Format code
make format
Kernel Development Workflow
Steps to add a new kernel:
- Implement the kernel in
csrc - Expose the interface in
include/b10_kernel_ops.h - Create torch extension in
csrc/common_extension.cc - Update
CMakeLists.txtto include new CUDA source - Expose Python interface in
python/b10_kernel/xxx.pyandpython/b10_kernel/__init__.py - Add unit test for the kernel in
test/test_xxx.py - Add benchmark script for the kernel in
benchmark/bench_xxx.py - Format code with
make format
PyPI Release
# update to expected version
make update_version VERSION=0.1.x
make build
make rename_wheel
make upload_wheel
Project details
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