Installation Requirements

• Any NVIDIA GPU that supports CUDA architecture 75, 80, 86, 89, 90, 100 or 120 and has at least 16GB of GPU RAM. NVIDIA Parabricks has been tested on the following NVIDIA GPUs:

  • T4

  • A10, A30, A40, A100, A6000

  • L4, L40

  • H100, H200

  • Grace Hopper Superchip

  • B200

• All tools require at least 16 GB of GPU memory per GPU. The following tools have defaults which require more than 16 GB but have options to lower the device memory usage to fit on devices with 16 GB of GPU memory.

  • fq2bam (BWA-MEM + GATK): Default configuration requires at least 40 GB of GPU memory per GPU. To use a 16 GB GPU, use the --low-memory option. More details on tuning the configuration for GPUs with various memory sizes can be found in fq2bam -- Useful Options for Performance.

  • fq2bam_meth: Default configuration requires at least 48 GB of GPU memory per GPU. To use a 16 GB GPU, use the --low-memory option. More details on tuning the configuration for GPUs with various memory sizes can be found in fq2bam_meth -- Useful Options for Performance.

  • giraffe (vg giraffe + GATK): Default configuration requires at least 40 GB of GPU memory per GPU. To use a 16 GB GPU, use the --low-memory option. More details on tuning the configuration for GPUs with various memory sizes can be found in giraffe -- Useful Options for Performance.

  • haplotypecaller and mutectcaller: Default configurations require at least 18 GB of GPU memory per GPU. To use a 16 GB GPU, use the --htvc-low-memory and --mutect-low-memory options, respectively.

  • minimap2 (Beta): Default configuration requires at least 18 GB of GPU memory per GPU. To use a 16 GB GPU, use the --low-memory option.

  • rna_fq2bam: Default configuration requires at least 24 GB of GPU memory per GPU. To use a GPU with less device memory, use the --low-memory option.

• System Requirements:

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

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

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

The following are software requirements for running Parabricks.

• Any NVIDIA driver that is compatible with CUDA 12.8 (535, 550, 570 or similar). Please check here for more details on forward compatibility.

• Any Linux Operating System that supports nvidia-docker2 Docker version 20.10 (or higher)

Please see these pages for more information on supported driver configurations:

• CUDA Toolkit, Driver and Architecture Matrix

• CUDA Compatibility

Checking available NVIDIA hardware and driver

To check your NVIDIA hardware and driver version, use the nvidia-smi command:

            

            
 $ nvidia-smi
 +-----------------------------------------------------------------------------------------+
 | NVIDIA-SMI         570.86.15      Driver Version: 570.86.15    CUDA Version: 12.8.0     |
 |-----------------------------------------+------------------------+----------------------+
 | 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 RTX 6000 Ada Gene...    Off |   00000000:17:00.0 Off |                  Off |
 | 30%   28C    P8             10W /  300W |      16MiB /  49140MiB |      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             |
 +-----------------------------------------------------------------------------------------+
        

This shows the following important information:

• The NVIDIA driver version is 570.86.15.

• The supported CUDA driver API is 12.8.0.

• The GPU has 48 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:

            

            
# 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:

            

            
 $ docker run --rm --gpus all nvidia/cuda:12.8.0-base-ubuntu22.04 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:

            

            
$ python3 --version
        

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