Skip to navigation

Prerequisites

View as Markdown
docker run --rm --runtime=nvidia --gpus all ubuntu nvidia-smi

Example output:

+-----------------------------------------------------------------------------+
| NVIDIA-SMI 525.78.01    Driver Version: 525.78.01    CUDA Version: 12.0     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|                               |                      |               MIG M. |
|===============================+======================+======================|
|   0  NVIDIA GeForce ...  Off  | 00000000:01:00.0 Off |                  N/A |
| 41%   30C    P8     1W / 260W |   2244MiB / 11264MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|=============================================================================|
+-----------------------------------------------------------------------------+

For more information on enumerating multi-GPU systems, refer to the NVIDIA Container Toolkit GPU enumeration topic.

Supported Hardware

These configurations are the supported hardware for this NIM. Runtime expectations are in Performance.

The AlphaFold2 NIM is configured to run on a single GPU. The minimum GPU memory requirement for the AlphaFold2 NIM is 32 GB. The AlphaFold2 NIM should run on any NVIDIA GPU that meets this minimum hardware requirement and has compute capability 8.0 or higher. The AlphaFold2 NIM also requires at least 1250 GB of free SSD space.

In summary, users looking to successfully run the AlphaFold2 NIM for small sequences should have a system with:

  • One NVIDIA GPU with at least 32 GB of VRAM and Compute Capability 8.0 or higher
  • At least 64 GB of RAM
  • A CPU with at least 24 available cores
  • At least 1,250 GB of free SSD drive space.

For optimum performance, use a system with:

  • At least one NVIDIA GPU with 80 GB of VRAM (for example, A100 80GB)
  • At least 128 GB of RAM
  • A CPU with at least 36 available cores
  • At least 1,250 GB of free fast NVMe SSD drive space.

NGC (NVIDIA GPU Cloud) Account

  1. Create an account on NGC
  2. Generate an API Key
  3. Docker log in with your NGC API key using docker login nvcr.io --username='$oauthtoken' --password=${NGC_API_KEY}

NGC CLI Tool

  1. Download the NGC CLI tool for your OS.

Use NGC CLI version 3.41.1 or newer. Here is the command to install this on AMD64 Linux in your home directory:

wget --content-disposition https://api.ngc.nvidia.com/v2/resources/nvidia/ngc-apps/ngc_cli/versions/3.41.3/files/ngccli_linux.zip -O ~/ngccli_linux.zip && \
unzip ~/ngccli_linux.zip -d ~/ngc && \
chmod u+x ~/ngc/ngc-cli/ngc && \
echo "export PATH=\"\$PATH:~/ngc/ngc-cli\"" >> ~/.bash_profile && source ~/.bash_profile
  1. Set up your NGC CLI tool locally (you will need your API key for this):
ngc config set

After you enter your API key, you might see multiple options for the org and team. Select as desired or press Enter to accept the default.

  1. Log in to NGC

You will need to log in to NGC with Docker and set the NGC_API_KEY environment variable to pull images:

docker login nvcr.io
Username: $oauthtoken
Password: <Enter your NGC key here>

Then, set the relevant environment variables in your shell. You will need to set the NGC_API_KEY variable:

export NGC_API_KEY=<Enter your NGC key here>
  1. Set up your NIM cache

The NIM cache allows you to download models and store previously-downloaded models so that you do not need to download them again later when you run the NIM again. The NIM cache must be readable and writable by the NIM, so in addition to creating the directory, the permissions on this directory need to be set to globally readable writable. The NIM cache directory can be set up as follows:

## Create the NIM cache directory
mkdir -p ~/.cache/nim
## Set the NIM cache directory permissions to the correct values
chmod -R 777 ~/.cache/nim

Now, you should be able to pull the container and download the model using the environment variables. To get started, refer to the Quickstart Guide.