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  • User documentation
    • Quickstart
      • Run a module locally
        • Run the container
        • Access the module via API
      • Train a module on DEEP Dashboard
      • Develop and share your own module
    • Overview
      • DEEP architecture
        • The Marketplace
        • The DEEPaaS API
        • The data storage resources
        • The Dashboard
      • User roles and workflows
        • The basic user
        • The intermediate user
        • The advanced user
      • DEEP Modules
        • CI /CD pipeline
      • DEEP Modules Template
        • Create your project based on the template
        • Project structure
      • DEEPaaS API
        • Integrate your model with the API
        • Running the API
      • DEEP Dashboard
        • Selecting the modules
        • Making a deployment
        • Managing the deployments
    • How-to’s
      • Use a model (basic user)
        • Perform inference locally
      • Train a model (intermediate user)
        • Train a model locally
        • Train a model remotely
        • Use rclone
      • Develop a model (advanced user)
        • Develop a model
    • Others
      • Useful Machine Learning resources
        • Tutorials
        • Datasets
        • Models
      • Video demos
  • Technical documentation
    • HowTo’s (developers)
      • Module integration workflow for external (non-deephdc) users
        • 1. Name check
        • 2. Fork creation
        • 3. Keep the forks updated
        • 4. Update <branchname> in .gitmodules
      • Develop Dashboard
      • Configure oidc-agent
      • Deployment with CLI (orchent)
        • Prepare your TOSCA file (optional)
        • Orchent submission script
        • Submit your deployment
      • Using Openstack API with OIDC tokens
        • Create file for OIDC
        • Using Openstack CLI
    • Mesos
      • Introduction
      • Testbed Setup
        • Nodes characteristics
        • Tested Components Versions
      • Prepare the agent (slave) node
        • Verify the nvidia-driver installation
        • Mesos slave configuration
        • Testing GPU support in Mesos
      • Testing Chronos patch for GPU support
        • Patch compilation
        • Testing
      • Testing GPU support in Marathon
      •  Running tensorflow docker container
      • References
      • Enabling open-id connect authentication
    • Kubernetes
      • DEEP : Installing and testing GPU Node in Kubernetes - CentOS7
        • Introduction
        • Cluster Status
        • Tests
        • Access PODs from outside the cluster
        • References
      • Installing GPU node and adding it to Kubernetes cluster
        • Step-by-step guide
    • OpenStack nova-lxd
      • OpenStack nova-lxd installation via Ansible
        • Comparison between Openstack Ansible and Juju/conjure-up
        • Installing a All-in-One Openstack site with nova-lxd via Openstack Ansible
        • Notes:
        • References
      • Deploying OpenStack environment with nova-lxd via DevStack
        • Installation steps
        • Handy commands:
        • Notes:
        • References
      • Installing nova-lxd with Juju
        • Installation
        • Notes
      • OpenStack nova-lxd testing configuration
        • Testing of nova-lxd with different software configurations
        • Working configuration
    • uDocker
      • uDocker new GPU implementation
        • Test and evaluation of new implementation
        • References
    • Miscellaneous
      • GPU sharing with MPS
        • How to use MPS service
        • Testing environment
        • Test 1. Test with CUDA native sample nbody, without nvidia-cuda-mps service
        • Test 2. Test with CUDA native sample nbody, with nvidia-cuda-mps service
        • Test 3. Test with Docker using mariojmdavid/tensorflow-1.5.0-gpu image, without nvidia-cuda-mps service
        • Test 4. Test with Docker using mariojmdavid/tensorflow-1.5.0-gpu image, with nvidia-cuda-mps service
        • Test 5. Test with Docker using vykozlov/tf-benchmarks:181004-tf180-gpu image, without and with nvidia-cuda-mps service
        • Identified reasons why Tensoflow does not work correctly with MPS
        • Final remarks:
        • References
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