microsoft/ltp-platform

microsoft/ltp-platform

Description: LTP: component platform

Language: Python

License: MIT

Stars: 10

Forks: 4

Open issues: 7

Created: 2025-06-02T05:30:41Z

Pushed: 2026-06-10T08:10:58Z

Default branch: main

Fork: no

Archived: no

README:

Open Platform for AI (OpenPAI) ![alt text][logo]

[logo]: ./pailogo.jpg "OpenPAI"

 

After the release of [v1.8.1](./RELEASE_NOTE.md#Dec-2021-version-181) , OpenPAI has entered stable mode with no major feature release planned. In order to save maintenance efforts, we changed the repo to read only mode. For collaboration, please contact repo admin directly.

With the release of v1.0, OpenPAI is switching to a more robust, more powerful and lightweight architecture. OpenPAI is also becoming more and more modular so that the platform can be easily customized and expanded to suit new needs. OpenPAI also provides many AI user-friendly features, making it easier for end users and administrators to complete daily AI tasks.

Table of Contents

• [When to consider OpenPAI](#when-to-consider-openpai)
• [Why choose OpenPAI](#why-choose-openpai)
• [Support on-premises and easy to deploy](#support-on-premises-and-easy-to-deploy)
• [Support popular AI frameworks and heterogeneous hardware](#support-popular-ai-frameworks-and-heterogeneous-hardware)
• [Most complete solution and easy to extend](#most-complete-solution-and-easy-to-extend)
• [Get started](#get-started)
• [For cluster administrators](#for-cluster-administrators)
• [For cluster users](#for-cluster-users)
• [Standalone Components](#standalone-components)
• [Reference](#reference)
• [Related Projects](#related-projects)
• [Get involved](#get-involved)
• [How to contribute](#how-to-contribute)
• [Contributor License Agreement](#contributor-license-agreement)
• [Call for contribution](#call-for-contribution)
• [Who should consider contributing to OpenPAI](#who-should-consider-contributing-to-openpai)
• [Contributors](#contributors)

When to consider OpenPAI

1. When your organization needs to share powerful AI computing resources (GPU/FPGA farm, etc.) among teams. 2. When your organization needs to share and reuse common AI assets like Model, Data, Environment, etc. 3. When your organization needs an easy IT ops platform for AI. 4. When you want to run a complete training pipeline in one place.

Why choose OpenPAI

The platform incorporates the mature design that has a proven track record in Microsoft's large-scale production environment.

Support on-premises and easy to deploy

OpenPAI is a full stack solution. OpenPAI not only supports on-premises, hybrid, or public Cloud deployment but also supports single-box deployment for trial users.

Support popular AI frameworks and heterogeneous hardware

Pre-built docker for popular AI frameworks. Easy to include heterogeneous hardware. Support Distributed training, such as distributed TensorFlow.

Most complete solution and easy to extend

OpenPAI is a most complete solution for deep learning, support virtual cluster, compatible with Kubernetes eco-system, complete training pipeline at one cluster etc. OpenPAI is architected in a modular way: different module can be plugged in as appropriate. [Here](./docs/system_architecture.md) is the architecture of OpenPAI, highlighting technical innovations of the platform.

Get started

OpenPAI manages computing resources and is optimized for deep learning. Through docker technology, the computing hardware are decoupled with software, so that it's easy to run distributed jobs, switch with different deep learning frameworks, or run other kinds of jobs on consistent environments.

As OpenPAI is a platform, there are typically two different roles:

• Cluster users are the consumers of the cluster's computing resources. According to the deployment scenarios, cluster users could be researchers of Machine Learning and Deep Learning, data scientists, lab teachers, students and so on.
• Cluster administrators are the owners and maintainers of computing resources. The administrators are responsible for the deployment and availability of the cluster.

OpenPAI provides end-to-end manuals for both cluster users and administrators.

For cluster administrators

The admin manual is a comprehensive guide for cluster administrators, it covers (but not limited to) the following contents:

• Installation and upgrade. The installation is based on Kubespray, and here is the system requirements. OpenPAI provides an installation guide to facilitate the installation.

If you are considering upgrade from older version to the latest v1.0.0, please refer to the table below for a brief comparison between v0.14.0 and the v1.0.0. More detail about the upgrade considerations can be found upgrade guide.

| | v0.14.0 | v1.0.0 | | ----------------- | ------------------------ | ----------------------- | | Architecture | Kubernetes + Hadoop YARN | Kubernetes | | Scheduler | YARN Scheduler | HiveD / K8S default | | Job Orchestrating | YARN Framework Launcher | Framework Controller | | RESTful API | v1 + v2 | pure v2 | | Storage | Team-wise storage plugin | PV/PVC storage sharing | | Marketplace | Marketplace v2 | openpaimarketplace | | SDK | Python | JavaScript / TypeScript |

_If there is any question during deployment, please check installation FAQs and troubleshooting first. If it is not covered yet, refer to [here](#get-involved) to ask question or submit an issue._

• Basic cluster management. Through the Web-portal and a command-line tool paictl, administrators could complete [cluster…