Installation Requirements

3.7.0
  • Access to the internet.

  • Any NVIDIA GPU that supports CUDA architecture 60, 70, 75 or 80 and has at least 12GB of GPU RAM. Parabricks has been tested on NVIDIA V100, NVIDIA A100 and NVIDIA T4 GPUs.

  • System Requirements:

    • A 2 GPU server should have at least 100GB CPU RAM and at least 24 CPU threads.

    • A 4 GPU server should have at least 196GB CPU RAM and at least 32 CPU threads.

    • A 8 GPU server should have at least 392GB CPU RAM and at least 48 CPU threads.

Please note that Clara Parabricks is not supported on virtual (vGPU) or MIG (Multi-Instance) GPUs.

The following are software requirements for running Clara Parabricks.

  • An NVIDIA driver that supports cuda-10.1 or higher. If you're using an Ampere GPU, support for cuda-11.0 or higher is required.

  • Any Linux Operating System that supports one of the following:

  • Python 3

Checking available Nvidia hardware and driver

To check what Nvidia hardware and driver version you have, use the nvidia-smi command:

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$ nvidia-smi +-----------------------------------------------------------------------------+ | NVIDIA-SMI 450.119.04 Driver Version: 450.119.04 CUDA Version: 11.0 | |-------------------------------+----------------------+----------------------+ | 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 Tesla V100-DGXS... On | 00000000:07:00.0 Off | 0 | | N/A 44C P0 38W / 300W | 74MiB / 16155MiB | 0% Default | | | | N/A | +-------------------------------+----------------------+----------------------+ | 1 Tesla V100-DGXS... On | 00000000:08:00.0 Off | 0 | | N/A 44C P0 37W / 300W | 6MiB / 16158MiB | 0% Default | | | | N/A | +-------------------------------+----------------------+----------------------+ | 2 Tesla V100-DGXS... On | 00000000:0E:00.0 Off | 0 | | N/A 44C P0 39W / 300W | 6MiB / 16158MiB | 0% Default | | | | N/A | +-------------------------------+----------------------+----------------------+ | 3 Tesla V100-DGXS... On | 00000000:0F:00.0 Off | 0 | | N/A 44C P0 38W / 300W | 6MiB / 16158MiB | 0% Default | | | | N/A | +-------------------------------+----------------------+----------------------+ +-----------------------------------------------------------------------------+ | Processes: | | GPU GI CI PID Type Process name GPU Memory | | ID ID Usage | |=============================================================================| | 0 N/A N/A 3019 G /usr/lib/xorg/Xorg 56MiB | | 0 N/A N/A 3350 G /usr/bin/gnome-shell 16MiB | | 1 N/A N/A 3019 G /usr/lib/xorg/Xorg 4MiB | | 2 N/A N/A 3019 G /usr/lib/xorg/Xorg 4MiB | | 3 N/A N/A 3019 G /usr/lib/xorg/Xorg 4MiB | +-----------------------------------------------------------------------------+

This shows the following important information:

  • The NVIDIA driver version is 450.119.04.

  • The CUDA version is 11.0.

  • There are four Tesla V100 GPUs.

  • Each GPU has 16 GB of memory.

Checking available CPU RAM and threads

To see how much RAM and CPU threads in your machine, you can run the following:

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#To check available memory $ cat /proc/meminfo | grep MemTotal #To check available number of threads $ cat /proc/cpuinfo | grep processor | wc -l


Checking nvidia-docker2 installation

To make sure you have nvidia-docker2 installed run this command:

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$ docker run --rm --gpus all nvidia/cuda:11.0-base nvidia-smi

When it finishes downloading the container it will run the nvidia-smi command and show you the same output as above.

Checking python version

To see which version of Python you have, enter the following command:

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$ python3 --version

Make sure it's at least version 3 (3.6.9, 3.7, etc).

There are two types of Parabricks installation licenses:

  • Node Locked: licenses are tied to a specific set of GPUs on a server.

  • Flexera based: licenses allow for a set amount of GPUs to be used at once using a license server. This will use the Nvidia License Server. You can read more about it here (optional).

The software can be installed and run in 3 ways:

  • Docker container

  • Singularity container

  • Bare-metal Debian package (.deb)

© Copyright 2022, Nvidia. Last updated on Jun 28, 2023.