Cluster

Check current and average GPU usage (internal only)

Running GPU example codes with htcondor

•  ssh to a GPU server
•  Run the command git clone https://github.com/CHTC/templates-GPUs.git
•   cd templates-GPUs/test
•  Run the “submit.sub” job with the command condor_submit submit.sub
•  Monitor job status with  condor_q
•  Review the job output files when completed

Links

• CHTC info on Jobs That Use GPUs
• CHTC example GPU Job Templates
• CHTC R example
• Docker registry (Internal only)
• Docker/Condor usage (Internal only)

• Connecting: ssh REDLRADADM23589.ad.medctr.ucla.edu
• Using the NGC Catalog
  • Choose container by clicking on the down arrow in any of the panels. This copies it to your clipboard
  • ssh to the DGX-1 and paste the command you obtained from the catalog to pull
• Running with htcondor
  • See the “Getting Started” tab for examples and modify the submit file.
    • For example:
      • For templates – GPUs/docker/tensorflow_python/test_tensorflow.sub
      • Change: Requirements = (Target.CUDADriverVersion >= 10.1)
      • To: Requirements = ((Target.CUDADriverVersion >= 10.1) && (Machine == “REDLRADADM23589.ad.medctr.ucla.edu”))
• Users can store up to 200GB in their /raid/username directory
• There are currently no GPU usage policies enforced, so users are asked not to monopolize GPUs interactively. Over time we’ll put policies in place as users condorize their applications for batch execution

Check current Disk usage (internal only) GPU servers have the following filesystems available for use:

VM Info (internal only)