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You may deploy DLWorkspace using ARM template by clicking on the following button ("Deploy to Azure"), or using the "az" command line tool with a parameter file. To generate a parameter file, you can create a JSON file using an editor, or click on the following button, and then click "Edit parameters". You can then download a parameter file to be used by the "az" tool.
Also, you may change "Cluster Name Desired" to be the same as the resource group name if it is unique name (instead of using an arbitrarily generated cluster name).
If a cluster name is not explictly specified, the name can be retrieved from the outputs of the template deployment.
After deployment, the dev machine created will be available via SSH, and will be named "<clustername>-dev.<clusterlocation>.cloudapp.azure.com".
After deployment, the webportal will be available via http, and will be available at "http://<clustername>-infra01.<clusterlocation>.cloudapp.azure.com".
Apulis AI Platform (DLWorkspace) is an open source toolkit that allows AI scientists to spin up an AI cluster in turn-key fashion. This template will spin up a DLWorkspace cluster in Azure. Once setup, the DLWorkspace cluster in Azure provides web UI and/or restful API that allows AI scientist to run job (interactive exploration, training, inferencing, data analystics) on the cluster with resource allocated by DL Workspace cluster for each job (e.g., a single node job with a couple of GPUs with GPU Direct connection, or a distributed job with multiple GPUs per node). DLWorkspace also provides unified job template and operating environment that allows AI scientists to easily share their job and setting among themselves and with outside community. DLWorkspace out-of-box supports all major deep learning toolkits (TensorFlow, CNTK, Caffe, MxNet, etc..).
For more information about the DLWorkspace toolkit, visit https://github.com/Microsoft/DLWorkspace/tree/master
依瞳人工智能平台旨在为不同行业的用户提供基于深度学习的端到端解决方案,使用户可以用最快的速度、最少的时间开始高性能的深度学习工作,从而大幅节省研究成本、提高研发效率,同时可为中小企业解决私有云难建成、成本高等问题。 平台融合了Tensorflow、PyTorch、MindSpore等开源深度学习框架,提供了模型训练、超参调优、集群状态监控等开发环境,方便AI开发者快速搭建人工智能开发环境,开展AI开发应用。在监控模块基础上搭建预警模块,自动将平台异常通知管理员,提升平台的预警效率及安全性能。
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Dear OpenI User
Thank you for your continuous support to the Openl Qizhi Community AI Collaboration Platform. In order to protect your usage rights and ensure network security, we updated the Openl Qizhi Community AI Collaboration Platform Usage Agreement in January 2024. The updated agreement specifies that users are prohibited from using intranet penetration tools. After you click "Agree and continue", you can continue to use our services. Thank you for your cooperation and understanding.
For more agreement content, please refer to the《Openl Qizhi Community AI Collaboration Platform Usage Agreement》