DL workspace is an open source toolkit that allows you to setup a cluster that can run deep learning training job, interactive exploration job, and evaluation service. The cluster also support big data analytic toolkit such as Hadoop/Spark.
DL Workspace is still in pre-release alpha stage. If you encounter issues in either deployment and/or usage, please open an issue at Github, or contact the DL Workspace team.
Please setup the dev environment of DL workspace as this.
DL workspace cluster can be deployed to either public cloud (e.g., Azure), or to on-prem cluster. The deployment to public cloud is more straightforward, as the environment is more uniform. The deployment instruction are as follows:
We give instruction on the deployment of DL Workspace to an on-prem cluster as well. Please note that because each on-prem cluster is different in hardware (and maybe software) configuration, the deployment procedure is more tricky. The basic deployment step is as follows.
Additional information on general deployment can be found at here.