This Intel® Python XGBoost Performance sample illustrates how to analyze the performance benefit from using Intel optimizations upstreamed by Intel to latest XGBoost compared to un-optimized XGBoost 0.81. It demonstrates how to use software products that can be found in the Intel® AI Analytics Toolkit (AI Kit).

XGBoost is a widely used gradient boosting library in the classical machine learning (ML) area. Designed for flexibility, performance, and portability, XGBoost includes optimized distributed gradient boosting frameworks and implements Machine Learning algorithms underneath.

In this sample, you will use a XGBoost model and prediction using Intel optimizations upstreamed by Intel to the latest XGBoost package and the un-optimized XGBoost 0.81 for comparison.

This XGBoost sample code is implemented for the CPU using the Python language. The example assumes you XGBoost installed inside a conda environment, similar to what is delivered with the installation of the Intel® Distribution for Python* as part of the Intel® AI Analytics Toolkit. It also assumes you have set up an additional XGBoost 0.81 conda environment, with details on how to do so explained within the sample and this README.

When working with the command-line interface (CLI), you should configure the oneAPI toolkits using environment variables. Set up your CLI environment by sourcing the setvars script every time you open a new terminal window. This practice ensures that your compiler, libraries, and tools are ready for development.

Note: If you have not already done so, set up your CLI environment by sourcing the setvars script in the root of your oneAPI installation.

Linux*:

• For system wide installations: . /opt/intel/oneapi/setvars.sh
• For private installations: . ~/intel/oneapi/setvars.sh
• For non-POSIX shells, like csh, use the following command: bash -c 'source <install-dir>/setvars.sh ; exec csh'

For more information on configuring environment variables, see Use the setvars Script with Linux* or macOS*.

XGBoost is ready for use once you finish the Intel® AI Analytics Toolkit installation and have run the post installation script.

You can refer to the oneAPI main page for toolkit installation and the Toolkit Getting Started Guide for Linux for post-installation steps and scripts.

By default, the AI Kit is installed in the /opt/intel/oneapi folder and requires root privileges to manage it. However, if you activated another environment, you can return with the following command.

source activate base

You can choose to activate Conda environment without root access. To bypass root access to manage your Conda environment, clone and activate your desired Conda environment using the following commands similar to the following.

conda create --name usr_intelpython --clone base
source activate usr_intelpython

conda install jupyter nb_conda_kernels

To see the performance comparison to the latest XGBoost with Intel optimizations and un-optimized XGBoost 0.81, you must run this sample in a second conda environment with XGBoost 0.81 installed.

See the information in the Jupyter Notebook on how to set up and run the different conda environments.

Note: This distributed sample cannot be executed from the Jupyter Notebook, but you can read the description and follow the program flow in the Notebook.

Note: This distributed sample cannot be executed from the Jupyter Notebook, but you can read the description and follow the program flow in the Notebook.

1. Change to the sample directory.
2. Launch Jupyter Notebook.

   jupyter notebook
   

3. Locate and select the Notebook.

   IntelPython_XGBoost_Performance.ipynb
   

4. Click the Run button to move through the cells in sequence.

1. Change to the sample directory.
2. Locate and run the script.

   python IntelPython_XGBoost_Performance.py
   

If you receive an error message, troubleshoot the problem using the Diagnostics Utility for Intel® oneAPI Toolkits. The diagnostic utility provides configuration and system checks to help find missing dependencies, permissions errors, and other issues. See the Diagnostics Utility for Intel® oneAPI Toolkits User Guide for more information on using the utility.

[CODE_SAMPLE_COMPLETED_SUCCESFULLY]

Code samples are licensed under the MIT license. See License.txt for details.

Third-party program Licenses can be found here: third-party-programs.txt.