Cloud-Agnostic Deployment of Distributed TensorFlow

In this poster we will see how to deploy the required infrastructure to create a TensorFlow cluster, and then provision the software to train the model. For doing this, we will use the Infrastructure Manager (http://www.grycap.upv.es/im/index.php) that supports API’s from different virtual platforms, making user applications Cloud-agnostic. In addition, it integrates a contextualization system, based on Ansible, to enable the installation and configuration of all the required applications providing a fully functional Deep Learning infrastructure on the Cloud provider that we need.

Outline:

• Distributed TensorFlow: Basic approach and architecture.
• Deploying the infrastructure with the Infrastructure Manager.
• Ansible Roles.
• Training the model.