Skip to content

Instantly share code, notes, and snippets.

@djw8605
Last active August 29, 2015 14:02
Show Gist options
  • Star 0 You must be signed in to star a gist
  • Fork 0 You must be signed in to fork a gist
  • Save djw8605/56bba483c0b15461a589 to your computer and use it in GitHub Desktop.
Save djw8605/56bba483c0b15461a589 to your computer and use it in GitHub Desktop.
Submission for CUDA 5.0 to Tusker

In order to submit a previous version of CUDA to Tusker's GPU nodes, you need to bring along the CUDA library. Additionally, you need to append the LD_LIBRARY_PATH to include the current directory. In order to accomplish this, we used a wrapper script, run.sh, which sets the environment and runs the cuda code.

run.sh is set as the executable. The transfer input files includes the library (from the system path), and the main CUDA executable.

transfer_input_files = /util/opt/cuda/5.0/lib64/libcudart.so.5.0, main

The argument to run.sh is simply the executable to run, main.

NOTE: You will need to modify the transfer_input_files line to point to the location of the libcudart.so.5.0 on your system.

universe = grid
grid_resource = condor tusker-gw1.unl.edu tusker-gw1.unl.edu:9619
executable = run.sh
arguments = ./main
transfer_input_files = /util/opt/cuda/5.0/lib64/libcudart.so.5.0, main
output = jm.out.condorc
error = jm.err.condorc
log = jm.log
WhenToTransferOutput = ON_EXIT
x509userproxy = x509up_u1384
# Request the gpu
Request_GPUs = 1
queue
#!/bin/sh
LD_LIBRARY_PATH=$LD_LIBRARY_PATH:`pwd`
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:`pwd`
exec "$@"
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment