bitnami-containers/bitnami/xgboost-intel

XGBoost for Intel packaged by Bitnami

What is XGBoost for Intel?

XGBoost is a distributed boosting library built to solve data science problems. Intel has been training and inference optimizations to the XGBoost package for superior performance on Intel CPUs.

Overview of XGBoost for Intel

Trademarks: This software listing is packaged by Bitnami. The respective trademarks mentioned in the offering are owned by the respective companies, and use of them does not imply any affiliation or endorsement.

TL;DR

$ docker run -it --name xgboost-intel bitnami/xgboost-intel

Docker Compose

$ curl -sSL https://raw.githubusercontent.com/bitnami/containers/main/bitnami/xgboost-intel/docker-compose.yml > docker-compose.yml
$ docker-compose up -d

Why use Intel optimized containers

New instructions, coupled with algorithmic and software innovations, deliver breakthrough performance for the industry's most widely deployed cryptographic ciphers. Encryption is becoming pervasive with most organizations increasingly adopting encryption for application execution, data in flight, and data storage. 3rd gen Intel(R) Xeon(R) Scalable Processor (Ice Lake) cores and architecture, offers several new instructions for encryption acceleration.

This solution requires 3rd gen Intel Xeon Scalable Processor (Ice Lake) to get a breakthrough performance improvement.

Why use Bitnami Images?

• Bitnami closely tracks upstream source changes and promptly publishes new versions of this image using our automated systems.
• With Bitnami images the latest bug fixes and features are available as soon as possible.
• Bitnami containers, virtual machines and cloud images use the same components and configuration approach - making it easy to switch between formats based on your project needs.
• All our images are based on minideb a minimalist Debian based container image which gives you a small base container image and the familiarity of a leading Linux distribution.
• All Bitnami images available in Docker Hub are signed with Docker Content Trust (DCT). You can use DOCKER_CONTENT_TRUST=1 to verify the integrity of the images.
• Bitnami container images are released on a regular basis with the latest distribution packages available.

This CVE scan report contains a security report with all open CVEs. To get the list of actionable security issues, find the "latest" tag, click the vulnerability report link under the corresponding "Security scan" field and then select the "Only show fixable" filter on the next page.

Why use a non-root container?

Non-root container images add an extra layer of security and are generally recommended for production environments. However, because they run as a non-root user, privileged tasks are typically off-limits. Learn more about non-root containers in our docs.

Supported tags and respective Dockerfile links

Learn more about the Bitnami tagging policy and the difference between rolling tags and immutable tags in our documentation page.

You can see the equivalence between the different tags by taking a look at the tags-info.yaml file present in the branch folder, i.e bitnami/ASSET/BRANCH/DISTRO/tags-info.yaml.

Subscribe to project updates by watching the bitnami/containers GitHub repo.

Get this image

The recommended way to get the Bitnami xgboost-intel Docker Image is to pull the prebuilt image from the Docker Hub Registry.

$ docker pull bitnami/xgboost-intel:latest

To use a specific version, you can pull a versioned tag. You can view the list of available versions in the Docker Hub Registry.

$ docker pull bitnami/xgboost-intel:[TAG]

If you wish, you can also build the image yourself by cloning the repository, changing to the directory containing the Dockerfile and executing the docker build command. Remember to replace the APP, VERSION and OPERATING-SYSTEM path placeholders in the example command below with the correct values.

$ git clone https://github.com/bitnami/containers.git
$ cd bitnami/APP/VERSION/OPERATING-SYSTEM
$ docker build -t bitnami/APP:latest .

Entering the REPL

By default, running this image will drop you into the Python REPL, where you can interactively test and try things out with XGBoost for Intel in Python.

$ docker run -it --name xgboost-intel bitnami/xgboost-intel

Configuration

Running your XGBoost for Intel app

The default work directory for the XGBoost for Intel image is /app. You can mount a folder from your host here that includes your XGBoost for Intel script, and run it normally using the python command.

$ docker run -it --name xgboost-intel -v /path/to/app:/app bitnami/xgboost-intel \
  python script.py

Running a XGBoost for Intel app with package dependencies

If your XGBoost for Intel app has a requirements.txt defining your app's dependencies, you can install the dependencies before running your app.

$ docker run -it --name xgboost-intel -v /path/to/app:/app bitnami/xgboost-intel \
  sh -c "pip install -r requirements.txt && python script.py"

Further Reading:

• XGBoost documentation

Maintenance

Upgrade this image

Bitnami provides up-to-date versions of XGBoost for Intel, including security patches, soon after they are made upstream. We recommend that you follow these steps to upgrade your container.

Step 1: Get the updated image

$ docker pull bitnami/xgboost-intel:latest

or if you're using Docker Compose, update the value of the image property to bitnami/xgboost-intel:latest.

Step 2: Remove the currently running container

$ docker rm -v xgboost-intel

or using Docker Compose:

$ docker-compose rm -v xgboost-intel

Step 3: Run the new image

Re-create your container from the new image.

$ docker run --name xgboost-intel bitnami/xgboost-intel:latest

or using Docker Compose:

$ docker-compose up xgboost-intel

Contributing

We'd love for you to contribute to this Docker image. You can request new features by creating an issue or submitting a pull request with your contribution.

Issues

If you encountered a problem running this container, you can file an issue. For us to provide better support, be sure to fill the issue template.

License

Copyright © 2022 Bitnami

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.