2. Installation

2.1. Minimal System Requirements

The Clara Deploy SDK has the following system requirements:

  • Ubuntu Linux 16.04 LTS or 18.04 LTS

  • NVIDIA Driver 410.48 or higher

    • Installation of CUDA Toolkit would make both CUDA and NVIDIA Display Drivers available

  • NVIDIA GPU is Pascal or newer

  • Kubernetes >= 1.11

  • Docker >= 17.03.2 (or 1.27)

  • NVIDIA Docker >= 2.0.0+docker17.03.2-1

  • Docker configured with nvidia as the default runtime (Prerequisite of NVIDIA device plugin for k8s)

  • Helm >= 2.11.0

  • At least 30GB of available disk space

2.2. Steps to Install

Step 1 is only required if your system does not have the minimal system requirements. Otherwise, jump directly to Step 2.

  1. To install the required prerequisites:

    • Docker

    • NVIDIA Container Runtime for Docker

    • Kubernetes (including kubectl)

    • Helm


      This step can be skipped if the system already has the above components.

    Run install-prereqs.sh with the following commands:

    cd scripts
    sudo ./install-prereqs.sh


    If your system does not have NVIDIA CUDA Toolkit installed, you will be provided with a link to install it.

  2. Deploy Clara Deploy SDK with the following command. Output should be similar to the following:

    cd scripts
    sudo ./deploy.sh
    2019-06-26 22:32:01 [INFO]: Installing Clara Deploy SDK v[version]...
    2019-06-26 22:32:43 [INFO]: Clara Containers loaded successfully
    2019-06-26 22:32:43 [INFO]: Copying the included AI models to directory: /clara/common...
    2019-06-26 22:32:43 [INFO]: AI models copied successfully.
    2019-06-26 22:32:43 [INFO]: Installing Clara CLI
    2019-06-26 22:32:44 [INFO]: Clara CLI installed successfully
    2019-06-26 22:32:44 [INFO]: Starting Clara...
    NAME:   clara
    2019-06-26 22:32:46 [INFO]: Starting Result Service...
    2019-06-26 22:32:01NAME:   clara-results-service
    2019-06-26 22:32:51 [INFO]: Starting DICOM Adapter...
    NAME:   clara-dicom-adapter
    2019-06-26 22:33:09 [INFO]: Clara Deploy SDK v0.2.0 installed and started successfully.


    This script installs binaries and configuration files that are needed for Clara Deploy SDK, and so should only be used for the initial installation. To stop and restart Clara Deploy SDK after this initial installation, see Start/Stop/Restart the platform.

2.3. Verify Installation

The deploy script will automatically start the following components:

  • The Clara Platform

  • The Results Service

  • The DICOM Adapter

To verify that the installation is successful, run the following command:

helm ls

The following three helm charts should be returned:

  • clara

  • clara-dicom-adapter

  • clara-results-service

To verify that the helm charts are up and running, run the following command:

kubectl get pods

The command should return the following pods with the below prefix:

  • clara-clara-platformapiserver

  • clara-ui

  • clara-workflow-controller

  • clara-dicom-adapter

  • clara-results-service

They should be all in a Running state

2.4. Installation on a Cloud Service Provider (CSP)

Researchers and data scientists who might not have access to a GPU server can still easily get started with Clara Deploy SDK without needing to become a Docker and Kubernetes expert. The Clara Deploy SDK has been validated on:

  • Amazon Web Services (AWS)

  • Microsoft Azure Cloud Services (Azure)

  • Google Cloud Platform Services (GCP)

The following subsections describe the configuration for each CSP. Once the VM is provisioned according to the documentation, you can follow the Steps to Install section to install Clara.

2.4.1. AWS Virtual Machine Configuration

The AWS VM configuration used for testing can be found below:

  • Location : US East (Ohio)

  • Operating System : Ubuntu 18.04

  • Amazon machine image : Ubuntu Server 18.04 LTS (HVM), SSD Volume Type (64-bit)

  • Instance type : g3.4xlarge (16 vcpus, 122 GB memory, NVIDIA Tesla M60 GPU)

  • Storage: General Purpose SSD (100 GB)

  • Ports Open : SSH, HTTP, HTTPS

2.4.2. Azure Virtual Machine Configuration

The Azure VM configuration used for testing can be found below:

  • Location : West US2

  • Operating System: Ubuntu 18.04

  • Size : Standard NC6s_v2 (6 vcpus, 112 GB memory, 1 GPU-NVIDIA Tesla P100)

  • OS Disk Size : Premium SSD, 300GB (mounted on root)

  • Ports Open : SSH, HTTP, HTTPS

2.4.3. GCP Virtual Machine Configuration

The GCP VM configuration used for testing can be found below:

  • Location :

    • Region: us-central1 (Iowa)

    • Zone: us-central1-c

  • Operating System : Ubuntu 18.04 LTS

  • Machine type: 8vCPU, 32GB, 1 GPU (NVIDIA Tesla P4), Turn on display device

  • Disk Size: SSD 100GB

  • Ports Open : SSH, HTTP, HTTPS