# SYCL-based Algorithm for Tree Construction This plugin adds support of SYCL programming model for prediction algorithms to XGBoost. ## Usage Specify the 'device' parameter as described in the table below to offload model training and inference on SYCL device. ### Algorithms | device | Description | | --- | --- | sycl | use default sycl device | sycl:gpu | use default sycl gpu | sycl:cpu | use default sycl cpu | sycl:gpu:N | use sycl gpu number N | sycl:cpu:N | use sycl cpu number N | Python example: ```python param['device'] = 'sycl:gpu:0' ``` Note: 'sycl:cpu' devices have full functional support but can't provide good enough performance. We recommend use 'sycl:cpu' devices only for test purposes. Note: if device is specified to be 'sycl', device type will be automatically chosen. In case the system has both sycl GPU and sycl CPU, GPU will on use. ## Dependencies To build and use the plugin, install [Intel® oneAPI DPC++/C++ Compiler](https://www.intel.com/content/www/us/en/developer/tools/oneapi/dpc-compiler.html). See also [Intel® oneAPI Programming Guide](https://www.intel.com/content/www/us/en/docs/oneapi/programming-guide/2024-0/overview.html). ## Build From the ``xgboost`` directory, run: ```bash $ mkdir build $ cd build $ cmake .. -DPLUGIN_SYCL=ON $ make -j ```