def processCommandLine(self, options):
# Not processed here:
# -p, --print-num-params, --print-all-params
# --on-io-error
# Loglevel: -l
logger.logger.setLevel(logger.LOGLEVELS[options.loglevel][0])
for line in self.banner:
logger.info(line)
# Profiling: --prof
if options.profiling_enabled:
self.enableProfiling(True)
logger.info("Profiling enabled")
# Number of fftw threads: -t
if options.num_fftw_threads != 1:
self.setFFTWThreads(options.num_fftw_threads)
# GPU enable: -g, -G
if options.gpu32 and options.gpu64:
logger.warn("Ignoring -g because -G was given")
def determine_gpu_id(arg):
# 'auto'
if arg == "auto":
try:
gpus = nvidia_smi.run()
available = nvidia_smi.available(gpus)
if len(available == 0):
logger.warn("Could not find any available GPUs (out of %s detected GPUs)." % len(gpus))
return -1
return available[0]
except:
return -1
else:
# id specified by user
return int(arg)
if options.gpu64:
cuda_mode, cuda_dev = magneto.CUDA_64, determine_gpu_id(options.gpu64)
elif options.gpu32:
cuda_mode, cuda_dev = magneto.CUDA_32, determine_gpu_id(options.gpu32)
else:
cuda_mode, cuda_dev = magneto.CUDA_DISABLED, -1
if cuda_mode != magneto.CUDA_DISABLED and not self.haveCudaSupport():
logger.error("Can't enable GPU computation (-g or -G flags): CUDA libraries could not be loaded.")
logger.error("-> Falling back to CPU.")
self.enableCuda(cuda_mode, cuda_dev)
cuda_support = "yes" if self.haveCudaSupport() else "no"
logger.info("CUDA GPU support: %s", cuda_support)
logger.info("Running on host %s", socket.gethostname())
def __init__(self, run, params):
super(LocalController, self).__init__(run, params)
idx_range = getattr(cfg.options, 'prange', range(self.num_params))
for i in idx_range:
if 0 <= i < self.num_params:
continue
logger.warn("Controller: No such parameter set with index %s!" % i)
if len(idx_range) == 0:
logger.warn("Controller: No parameter sets selected!")
self.select(idx_range)
def __init__(self, run, params, env, offset=0):
super(EnvironmentVariableController, self).__init__(run, params)
try:
p_idx = int(os.environ[env]) - offset
except:
logger.error("Could not read environment variable '%s'." % env)
raise
if 0 >= p_idx < self.num_params:
self.select([p_idx])
else:
logger.warn("Controller: No such parameter set with index %s!" %
p_idx)
self.select([])
def determine_gpu_id(arg):
# 'auto'
if arg == "auto":
try:
gpus = nvidia_smi.run()
available = nvidia_smi.available(gpus)
if len(available == 0):
logger.warn("Could not find any available GPUs (out of %s detected GPUs)." % len(gpus))
return -1
return available[0]
except:
return -1
else:
# id specified by user
return int(arg)
def determine_gpu_id(arg):
# 'auto'
if arg == "auto":
try:
gpus = nvidia_smi.run()
available = nvidia_smi.available(gpus)
if len(available == 0):
logger.warn(
"Could not find any available GPUs (out of %s detected GPUs)."
% len(gpus))
return -1
return available[0]
except:
return -1
else:
# id specified by user
return int(arg)
def create_controller(run, params, *args, **kwargs):
"""
Create a controller object, depending on the environment in which
the script was executed:
TODO: Explain.
"""
# Case 1: Report to stdout, then exit, if requested by command
# line options.
print_num_params = cfg.options.print_num_params
print_all_params = cfg.options.print_all_params
if print_num_params or print_all_params:
return PrintParametersController(
run, params, print_num_params, print_all_params
)
# Case 2: Use environment variable to select parameter set
env = kwargs.pop("env", None)
env_offset = kwargs.pop("env_offset", 0)
if env:
if env in os.environ:
return EnvironmentVariableController(run, params, env, env_offset)
else:
logger.warn(
"Environment variable '%s' not found, ignoring 'env' "
"parameter in controller creation" % env
)
# Case 3: Sun grid engine controller
sge = kwargs.pop("sun_grid_engine", False)
if sge:
if "SGE_TASK_ID" in os.environ:
return SunGridEngineController(run, params)
else:
logger.warn(
"Environment variable 'SGE_TASK_ID' not found, "
"ignoring 'sun_grid_engine' parameter in controller creation"
)
# Case 4: This controller is used when the script was executed
# locally. It optionally uses the -p argument passed to
# the simulation script.
return LocalController(run, params)
def Controller(run, params, *args, **kwargs):
logger.warn(
"The 'Controller' function is deprecated, please use "
"'create_controller' instead."
)
return create_controller(run, params, *args, **kwargs)
def __init__(self, mesh, step_size):
super(RungeKutta4, self).__init__(mesh)
self.step_size = float(step_size)
logger.warn("RungeKutta4 evolver: Performance hint: Don't use me.")
def __init__(self, mesh, step_size):
super(Euler, self).__init__(mesh)
self.step_size = float(step_size)
logger.warn("Euler evolver: Performance hint: Don't use me.")
def processCommandLine(self, options):
# Not processed here:
# -p, --print-num-params, --print-all-params
# --on-io-error
# Loglevel: -l
logger.logger.setLevel(logger.LOGLEVELS[options.loglevel][0])
for line in self.banner:
logger.info(line)
# Profiling: --prof
if options.profiling_enabled:
self.enableProfiling(True)
logger.info("Profiling enabled")
# Number of fftw threads: -t
if options.num_fftw_threads != 1:
self.setFFTWThreads(options.num_fftw_threads)
# GPU enable: -g, -G
if options.gpu32 and options.gpu64:
logger.warn("Ignoring -g because -G was given")
def determine_gpu_id(arg):
# 'auto'
if arg == "auto":
try:
gpus = nvidia_smi.run()
available = nvidia_smi.available(gpus)
if len(available == 0):
logger.warn(
"Could not find any available GPUs (out of %s detected GPUs)."
% len(gpus))
return -1
return available[0]
except:
return -1
else:
# id specified by user
return int(arg)
if options.gpu64:
cuda_mode, cuda_dev = magneto.CUDA_64, determine_gpu_id(
options.gpu64)
elif options.gpu32:
cuda_mode, cuda_dev = magneto.CUDA_32, determine_gpu_id(
options.gpu32)
else:
cuda_mode, cuda_dev = magneto.CUDA_DISABLED, -1
if cuda_mode != magneto.CUDA_DISABLED and not self.haveCudaSupport():
logger.error(
"Can't enable GPU computation (-g or -G flags): CUDA libraries could not be loaded."
)
logger.error("-> Falling back to CPU.")
self.enableCuda(cuda_mode, cuda_dev)
cuda_support = "yes" if self.haveCudaSupport() else "no"
logger.info("CUDA GPU support: %s", cuda_support)
logger.info("Running on host %s", socket.gethostname())