v3.0.1
Breaking Changes📦 xgboostView on GitHub →
⚠ 1 breaking✨ 6 features🐛 2 fixes🔧 4 symbols
Summary
This release adds GPU driver detection, deep-tree external-memory optimizations, new manylinux_2_28_x86_64 CPU wheels, Dask compatibility workarounds, and changes model output to use denormal floating-point values, along with several bug fixes.
⚠️ Breaking Changes
- Model files now store denormal floating-point values instead of NaN, which may break code that expects NaN in the output. Update downstream parsing or checks to handle denormal values.
Migration Steps
- If your workflow relies on NaN values in model output, adjust code to accept denormal floating-point numbers.
- Upgrade to the new `xgboost-cpu` manylinux_2_28_x86_64 wheel for Linux x86_64 environments.
- For R users, download the new experimental CUDA-enabled binary package if needed.
✨ New Features
- Detect NVIDIA driver version using `nvidia-smi` and gracefully handle drivers lacking virtual memory support.
- Optimized training of deep trees when using GPU external memory.
- Added support for building `xgboost-cpu` wheels targeting `manylinux_2_28_x86_64`.
- Implemented a workaround to maintain compatibility with multiple Dask versions.
- Experimental R binary packages with CUDA enabled are now available.
- Output models now use denormal floating-point representation instead of NaN.
🐛 Bug Fixes
- Fixed page concatenation issue when using external memory.
- Resolved CI failures on the aarch64 platform.