NVIDIA Parabricks Tesla K40c hardware requirement question

I would like to run the NVIDIA Parabricks. Mostly interested in alignment, variant calling speed improvements. I can’t figure out if my GPU meets the minimum requirements. It’s Tesla K40c. Which CUDA architecture does it support?

The following are required to install Parabricks:

  • Access to the internet (yes)
  • nvidia-driver that supports cuda-9.0 or higher (yes)
  • nvidia-driver that supports cuda-10.0 or higher if you want to run deepvariant or cnnscorevariants (yes)
  • nvidia-docker or singularity version 2.6.1 or higher (yes)
  • Python 2.7 (Most Linux systems will already have this installed) (yes)
  • curl (Most Linux systems will already have this installed) (yes)

The following are the hardware requirements (?)

  • Run on any GPU that supports CUDA architecture 60, 61, 70, 75 and has 12GB GPU RAM or more. It has been tested on NVIDIA P100, NVIDIA V100, and NVIDIA T4 GPUs.
    • 1 GPU server should have 64GB CPU RAM, at least 16 CPU threads
    • 2 GPU server should have 100GB CPU RAM, at least 24 CPU threads
    • 4 GPU server should have 196GB CPU RAM, at least 32 CPU threads
    • 8 GPU server should have 392GB CPU RAM, at least 48 CPU threads

Another important point is I am running Windows 10 64-bit Enterprise.

I want to do CNV calling, run the germline pipeline from fastq to bam + vcf from whole genome sequence data. My research is in rare developmental disorders and I have trio data. My CNV calling pipeline currently runs many days to complete. I want to be able to do it in less than an hour.

Thank you

Thank you for your interest in Parabricks. K40 is the Kepler architecture and unfortunately that doesn’t meet the minimum Compute Capabiltiy (CUDA architecture) requirements. Only Pascal (ex. P100), Volta (ex. V100) and Turing (ex. T4) are supported architectures.

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do i have other options running the same tools utilizing GPU?