Ways To Run DIGITS

You can run DIGITS in the following ways:
  1. Running DIGITS
  2. Running DIGITS from Developer Zone
  3. Docker®. For more information, see DIGITS on GitHub.

Running DIGITS

Before you can run an NGC deep learning framework container, your Docker environment must support NVIDIA GPUs. To run a container, issue the appropriate command as explained in the Running A Container chapter in the NVIDIA Containers And Frameworks User Guide and specify the registry, repository, and tags.

On a system with GPU support for NGC containers, the following occurs when running a container:
  • The Docker engine loads the image into a container which runs the software.
  • You define the runtime resources of the container by including additional flags and settings that are used with the command. These flags and settings are described in Running A Container.
  • The GPUs are explicitly defined for the Docker container (defaults to all GPUs, can be specified using NV_GPU environment variable).

The method implemented in your system depends on the DGX OS version installed (for DGX systems), the specific NGC Cloud Image provided by a Cloud Service Provider, or the software that you have installed in preparation for running NGC containers on TITAN PCs, Quadro PCs, or vGPUs.

  1. Issue the command for the applicable release of the container that you want. The following command assumes you want to pull the latest container.
    docker pull nvcr.io/nvidia/digits:19.10-caffe
    Or
    docker pull nvcr.io/nvidia/digits:19.10-tensorflow
  2. Open a command prompt and paste the pull command. The pulling of the container image begins. Ensure the pull completes successfully before proceeding to the next step.
  3. Run the application. A typical command to launch the application is:
    docker run --gpus all -it --rm –v local_dir:container_dir 
    nvcr.io/nvidia/digits:<xx.xx>-<framework>
    1. To run the server as a daemon and expose port 5000 in the container to port 8888 on your host:
      docker run --gpus all --name digits -d -p 8888:5000 	
      nvcr.io/nvidia/digits:<xx.xx>-<framework>
      Note:DIGITS 6.0 uses port 5000 by default.
    2. To mount one local directory containing your data (read-only), and another for writing your DIGITS jobs:
      docker run --gpus all --name digits -d -p 8888:5000 -v 	
      /home/username/data:/data -v /home/username/digits-	
      jobs:/workspace/jobs nvcr.io/nvidia/digits:<xx.xx>-<framework>
      Note: In order to share data between ranks, NVIDIA® Collective Communications Library ™ (NCCL) may require shared system memory for IPC and pinned (page-locked) system memory resources. The operating system’s limits on these resources may need to be increased accordingly. Refer to your system’s documentation for details.
      In particular, Docker containers default to limited shared and pinned memory resources. When using NCCL inside a container, it is recommended that you increase these resources by issuing:
      --shm-size=1g --ulimit memlock=-1
      in the command line to:
      docker run --gpus all

Running DIGITS from Developer Zone

For more information about downloading, running, and using DIGITS, see: NVIDIA DIGITS: Interactive Deep Learning GPU Training System.