#!/usr/bin/env python
from tuner import tune
if __name__ == '__main__':
tune(plotfreq=True, input_device_index=None)
def main():
try:
import argparse
except ImportError as e:
# Python 2.6 does not provide argparse in the standard library
# so load a local copy (taken from Python 2.7)
import argparseshim as argparse
parser = argparse.ArgumentParser(description='Autotune an OpenACC program')
parser.add_argument('source', type=str, nargs='?',
help='name of a source file to pass to the compile command',
metavar='filename')
parser.add_argument('-e', '--executable', type=str,
help='executable to run (default: ./a.out)',
metavar='filename')
parser.add_argument('-c', '--compile-command', type=str,
help='command line to compile an executable',
metavar='command')
parser.add_argument('-s', '--search-method', type=str,
help='search method to use when choosing test points: ' +
', '.join(sorted(tuner.METHODS.keys())),
metavar='method')
parser.add_argument('-r', '--repetitions', type=int,
help='number of times to run the executable to collect timing info',
metavar='count')
parser.add_argument('-t', '--time-regexp', type=str,
help='regular expression to identify timing information in the ' +
'output produced by the executable',
metavar='regexp')
parser.add_argument('-k', '--kernel-timing', action='store_true',
help='search the output for timing information produced when a ' +
'program is compiled with "-ta=nvidia,time" using pgcc/pgf90')
parser.add_argument('-l', '--logfile', type=str,
help='write log messages to a file',
metavar='filename.log')
parser.add_argument('--write-gnuplot', type=str,
help='generate a Gnuplot script to visualize the test results',
metavar='filename.gp')
parser.add_argument('--write-csv', type=str,
help='write timing results line by line to a CSV file',
metavar='filename.csv')
parser.add_argument('--write-spreadsheet', type=str,
help='write an Excel XML spreadsheet with results and statistics',
metavar='filename.xml')
parser.add_argument('--num-gangs-min', type=int,
help='minimum allowable value of num_gangs',
metavar='value')
parser.add_argument('--num-gangs-max', type=int,
help='maximum allowable value of num_gangs',
metavar='value')
parser.add_argument('--vector-length-min', type=int,
help='minimum allowable value of vector_length',
metavar='value')
parser.add_argument('--vector-length-max', type=int,
help='maximum allowable value of vector_length',
metavar='value')
parser.add_argument('-v', '--verbose', action='store_true',
help='display progress and diagnostic information while tuning')
parser.add_argument('-x', '--ignore-exit', action='store_true',
help='continue with autotuning even if the executable exits ' +
'with a nonzero exit code')
args = parser.parse_args()
# Sanity check args
if not args.source and not args.compile_command:
print('No source file specified. Please specify a source file or '
'a custom --compile-command. See --help for more details',
file=sys.stderr)
sys.exit(1)
if args.num_gangs_min is not None and args.num_gangs_min <= 0 or (
args.vector_length_min is not None and args.vector_length_min <= 0):
print('--num-gangs-min and --vector-length-min must be > 0',
file=sys.stderr)
sys.exit(1)
if args.repetitions is not None and args.repetitions <= 0:
print('--repetitions must be > 0', file=sys.stderr)
sys.exit(1)
# Extract provided arguments into a dictionary for easy construction
# of TuningOptions
kwargs = dict( (k, args.__dict__[k]) for k in args.__dict__
if args.__dict__[k] != None )
t = tuner.TuningOptions(**kwargs)
LOGGER.setLevel(logging.DEBUG if args.verbose else logging.INFO)
formatter = logging.Formatter('%(asctime)s %(levelname)s\t%(message)s',
'%H:%M:%S')
# Set up console logger
console = logging.StreamHandler()
console.setFormatter(formatter)
LOGGER.addHandler(console)
# Set up logfile if specified
if args.logfile:
file_log = logging.FileHandler(args.logfile)
file_log.setFormatter(formatter)
LOGGER.addHandler(file_log)
LOGGER.debug('TuningOptions: %s', t.__dict__)
# Set up output data files
with tuner.ResultWriter(tuner.ResultFiles(args.write_gnuplot,
args.write_csv,
args.write_spreadsheet)) as w:
tuner.tune(t, w)
#!/usr/bin/env python3
from __future__ import print_function, division
from tuner import tune
if __name__ == '__main__':
tune()
#tune(plotfreq=True, input_device_index=None)
def main():
try:
import argparse
except ImportError as e:
# Python 2.6 does not provide argparse in the standard library
# so load a local copy (taken from Python 2.7)
import argparseshim as argparse
parser = argparse.ArgumentParser(description='Autotune an OpenACC program')
parser.add_argument(
'source',
type=str,
nargs='?',
help='name of a source file to pass to the compile command',
metavar='filename')
parser.add_argument('-e',
'--executable',
type=str,
help='executable to run (default: ./a.out)',
metavar='filename')
parser.add_argument('-c',
'--compile-command',
type=str,
help='command line to compile an executable',
metavar='command')
parser.add_argument(
'-s',
'--search-method',
type=str,
help='search method to use when choosing test points: ' +
', '.join(sorted(tuner.METHODS.keys())),
metavar='method')
parser.add_argument(
'-r',
'--repetitions',
type=int,
help='number of times to run the executable to collect timing info',
metavar='count')
parser.add_argument(
'-t',
'--time-regexp',
type=str,
help='regular expression to identify timing information in the ' +
'output produced by the executable',
metavar='regexp')
parser.add_argument(
'-k',
'--kernel-timing',
action='store_true',
help='search the output for timing information produced when a ' +
'program is compiled with "-ta=nvidia,time" using pgcc/pgf90')
parser.add_argument('-l',
'--logfile',
type=str,
help='write log messages to a file',
metavar='filename.log')
parser.add_argument(
'--write-gnuplot',
type=str,
help='generate a Gnuplot script to visualize the test results',
metavar='filename.gp')
parser.add_argument('--write-csv',
type=str,
help='write timing results line by line to a CSV file',
metavar='filename.csv')
parser.add_argument(
'--write-spreadsheet',
type=str,
help='write an Excel XML spreadsheet with results and statistics',
metavar='filename.xml')
parser.add_argument('--num-gangs-min',
type=int,
help='minimum allowable value of num_gangs',
metavar='value')
parser.add_argument('--num-gangs-max',
type=int,
help='maximum allowable value of num_gangs',
metavar='value')
parser.add_argument('--vector-length-min',
type=int,
help='minimum allowable value of vector_length',
metavar='value')
parser.add_argument('--vector-length-max',
type=int,
help='maximum allowable value of vector_length',
metavar='value')
parser.add_argument(
'-v',
'--verbose',
action='store_true',
help='display progress and diagnostic information while tuning')
parser.add_argument(
'-x',
'--ignore-exit',
action='store_true',
help='continue with autotuning even if the executable exits ' +
'with a nonzero exit code')
args = parser.parse_args()
# Sanity check args
if not args.source and not args.compile_command:
print(
'No source file specified. Please specify a source file or '
'a custom --compile-command. See --help for more details',
file=sys.stderr)
sys.exit(1)
if args.num_gangs_min is not None and args.num_gangs_min <= 0 or (
args.vector_length_min is not None
and args.vector_length_min <= 0):
print('--num-gangs-min and --vector-length-min must be > 0',
file=sys.stderr)
sys.exit(1)
if args.repetitions is not None and args.repetitions <= 0:
print('--repetitions must be > 0', file=sys.stderr)
sys.exit(1)
# Extract provided arguments into a dictionary for easy construction
# of TuningOptions
kwargs = dict((k, args.__dict__[k]) for k in args.__dict__
if args.__dict__[k] != None)
t = tuner.TuningOptions(**kwargs)
LOGGER.setLevel(logging.DEBUG if args.verbose else logging.INFO)
formatter = logging.Formatter('%(asctime)s %(levelname)s\t%(message)s',
'%H:%M:%S')
# Set up console logger
console = logging.StreamHandler()
console.setFormatter(formatter)
LOGGER.addHandler(console)
# Set up logfile if specified
if args.logfile:
file_log = logging.FileHandler(args.logfile)
file_log.setFormatter(formatter)
LOGGER.addHandler(file_log)
# LOGGER.debug('TuningOptions: %s', t.__dict__)
# Set up output data files
with tuner.ResultWriter(
tuner.ResultFiles(args.write_gnuplot, args.write_csv,
args.write_spreadsheet)) as w:
tuner.tune(t, w)
