Copy both gpu_lock.py run_on_me_or_pid_quit to a convenient directory. You'll want them on your $PYTHONPATH if you want to import gpu_lock.py as a module, or just on your $PATH if you're happy shelling gpu_lock.py as an executable. If you are a Matlab user also copy obtain_gpu_lock_id.m into the same directory and use that to get lock IDs. Personally I also make a sym-link ln -s gpu_lock.py gpu_lock which is a prettier command to call (I still need the .py file to be able to import it as a Python module though.) The other files give examples of how to shell gpu_lock.py to obtain and lock a GPU id. For more information, run gpu_lock.py with no arguments. For even more information, see: http://www.cs.toronto.edu/~murray/code/gpu_monitoring/ -------------------------------------------------------------------------------- Toronto users: alias the version in my bin directory: ~/murray/bin/gpu_lock.py Then you will automatically get bug-fixes. If you sym-link it somewhere, also create a sym-link to: ~/murray/bin/run_on_me_or_pid_quit --------------------------------------------------------------------------------
Name Last modified Size Description
run_on_me_or_pid_quit 2010-01-13 02:52 677 obtain_gpu_lock_id.m 2011-01-24 11:51 1.3K matlab_notes 2009-11-27 17:30 533 gpu_lock.py 2011-01-24 11:51 4.8K example2.py 2009-11-27 17:27 140 example.sh 2009-11-27 17:27 121 example.py 2009-11-27 17:27 177