def jobfunc(pmemd, datadir, path, gpuid):
# path and gpuid arguments are provided by default by the localqueue class as last arguments
# AMBER automatically runs the calculation on the GPU with the
# most memory even if that GPU is already in use
# See: http://ambermd.org/gpus/#Running
# We assume the machine has the exhaustive mode setup
# So if other GPUs are being used when we launch the adaptive
# runs, jobs are only run in the free GPUs
# You set Persistence and Compute Exclusive Modes by running the following as root:
# $ nvidia-smi -pm 1
# $ nvidia-smi -c 3
# need to tell the shell script what engine we are using
with open(os.path.join(path, 'MD.sh'), 'r') as bash:
bash_file = bash.read()
bash_file = bash_file.replace('ENGINE', pmemd)
# logger.info('BASH script: {}'.format(bash))
with open(os.path.join(path, 'MD.sh'), 'w') as equil:
equil.write(bash_file)
cmd = """cd {} && bash {} > log.txt 2>&1""".format(os.path.normpath(path), 'MD.sh')
_executeMDcommand(cmd, path, datadir, 'pmemd.cuda', '*.nc')
def jobfunc(pmemd, datadir, path, gpuid):
# path and gpuid arguments are provided by default by the localqueue class as last arguments
# AMBER automatically runs the calculation on the GPU with the
# most memory even if that GPU is already in use
# See: http://ambermd.org/gpus/#Running
# We assume the machine has the exhaustive mode setup
# So if other GPUs are being used when we launch the adaptive
# runs, jobs are only run in the free GPUs
# You set Persistence and Compute Exclusive Modes by running the following as root:
# $ nvidia-smi -pm 1
# $ nvidia-smi -c 3
# need to tell the shell script what engine we are using
with open(os.path.join(path, 'MD.sh'), 'r') as bash:
bash_file = bash.read()
bash_file = bash_file.replace('ENGINE', pmemd)
# logger.info('BASH script: {}'.format(bash))
with open(os.path.join(path, 'MD.sh'), 'w') as equil:
equil.write(bash_file)
cmd = """cd {} && bash {} > log.txt 2>&1""".format(os.path.normpath(path),
'MD.sh')
_executeMDcommand(cmd, path, datadir, 'pmemd.cuda', '*.nc')
def jobfunc(acemd, datadir, inputfile, timeout, path, gpuid):
# path and gpuid arguments are provided by default by the localqueue class as last arguments
import os
timeoutstr = ''
if timeout:
timeoutstr = 'timeout {}'.format(timeout)
cmd = 'cd {}; {} {} --device {} {} > log.txt 2>&1'.format(os.path.normpath(path), timeoutstr, acemd, gpuid, inputfile)
logger.debug(cmd)
_executeMDcommand(cmd, path, datadir, 'ACEMD', '*.xtc')
def jobfunc(acemd, datadir, inputfile, timeout, path, gpuid):
# path and gpuid arguments are provided by default by the localqueue class as last arguments
import os
timeoutstr = ''
if timeout:
timeoutstr = 'timeout {}'.format(timeout)
cmd = 'cd {}; {} {} --device {} {} > log.txt 2>&1'.format(os.path.normpath(path), timeoutstr, acemd, gpuid, inputfile)
logger.debug(cmd)
_executeMDcommand(cmd, path, datadir, 'ACEMD', '*.xtc')
