def opentuner_ga(
env: ClientServiceCompilerEnv,
optimization_target: OptimizationTarget,
search_time_seconds: int,
seed: int,
max_copies_of_pass: int = 4,
population: int = 200,
tournament: int = 5,
mutate: int = 2,
sharing: int = 1,
**kwargs,
) -> None:
"""Optimize an environment using opentuner.
OpenTuner is an extensible framework for program autotuning:
https://opentuner.org/
"""
cache_dir = transient_cache_path("llvm_autotuning")
cache_dir.mkdir(exist_ok=True, parents=True)
with tempfile.TemporaryDirectory(dir=cache_dir,
prefix="opentuner-") as tmpdir:
argparser = ot.default_argparser()
args = argparser.parse_args(args=[
f"--stop-after={search_time_seconds}",
f"--database={tmpdir}/opentuner.db",
"--no-dups",
"--technique=custom",
f"--seed={seed}",
"--parallelism=1",
])
ot.search.technique.register(
BinaryGA(
population=population,
tournament=tournament,
mutate=mutate,
sharing=sharing,
name="custom",
))
manipulator = LlvmOptFlagsTuner(
args,
target=optimization_target,
benchmark=env.benchmark,
max_copies_of_pass=max_copies_of_pass,
)
tuner = TuningRunMain(manipulator, args)
tuner.main()
class DesiredResult:
def __init__(self, configuration) -> None:
self.configuration = configuration
class Configuration:
def __init__(self, data) -> None:
self.data = data
wrapped = DesiredResult(Configuration(manipulator.best_config))
manipulator.run(wrapped, None, None)
env.reset()
env.multistep(manipulator.serialize_actions(manipulator.best_config))
def main(args, cfg, ss):
logging.basicConfig(level=logging.INFO)
manipulator = ConfigurationManipulator()
params = cfg.getAllParameters()
print "\nFeature variables...."
for key in params.keys():
print "\t", key
manipulator.add_parameter(cfg.getParameter(key))
mi = StreamJitMI(args, ss, manipulator, FixedInputManager(),
MinimizeTime())
m = TuningRunMain(mi, args)
m.main()
def main(args, cfg, jvmOptions):
logging.basicConfig(level=logging.INFO)
manipulator = ConfigurationManipulator()
params = dict(cfg.items() + jvmOptions.items())
#print "\nFeature variables...."
for key in params.keys():
#print "\t", key
manipulator.add_parameter(params.get(key))
mi = StreamJitMI(args, jvmOptions, manipulator, FixedInputManager(),
MinimizeTime())
m = TuningRunMain(mi, args)
m.main()
def main(args, cfg, jvmOptions):
logging.basicConfig(level=logging.INFO)
manipulator = ConfigurationManipulator()
params = dict(cfg.items() + jvmOptions.items())
#print "\nFeature variables...."
for key in params.keys():
#print "\t", key
manipulator.add_parameter(params.get(key))
mi = StreamJitMI(args,jvmOptions, manipulator, FixedInputManager(),
MinimizeTime())
m = TuningRunMain(mi, args)
m.main()
def main(args, cfg, ss):
logging.basicConfig(level=logging.INFO)
manipulator = ConfigurationManipulator()
params = cfg.getAllParameters()
print "\nFeature variables...."
for key in params.keys():
print "\t", key
manipulator.add_parameter(cfg.getParameter(key))
mi = StreamJitMI(args, ss, manipulator, FixedInputManager(),
MinimizeTime())
m = TuningRunMain(mi, args)
m.main()
def run(self):
"""Starts the main OpenTuner loop."""
log.info("tuning thread '%s' starting (%d total threads now).", \
self.name, threading.active_count())
arg_parser = argparse.ArgumentParser(parents=opentuner.argparsers())
config_args = CONFIG.get("opentuner", "args").split()
tuner_args = arg_parser.parse_args(config_args)
interface = CtreeMeasurementInterface(self._ctree_driver,
*self._ot_args,
**self._ot_kwargs)
TuningRunMain(interface, tuner_args).main()
log.info("tuning thread '%s' terminating.", self.name)
def main(cls, envs, args, *pargs, **kwargs):
from opentuner.tuningrunmain import TuningRunMain
main = TuningRunMain(cls(envs, args, *pargs, **kwargs), args).main()
return (self.min_cycles, self.passes, self.sample_size, main)
def main(cls, args, *pargs, **kwargs):
from opentuner.tuningrunmain import TuningRunMain
return TuningRunMain(cls(args, *pargs, **kwargs), args).main()
for m in seed_multipliers: seed_config = manipulator.seed_config() for p in cfg.getAllParameters().values() + jvm_options.values(): if isinstance(p, sjparameters.sjCompositionParameter): p.equal_division(seed_config) elif isinstance(p, sjparameters.sjPermutationParameter): pass #p.set_value(config, p.seed_value()) else: seed_config[p.name] = p.value seed_config['multiplier'] = m seed_configs.append(seed_config) # The default bandit, plus our custom techniques. from opentuner.search import technique, bandittechniques, differentialevolution, evolutionarytechniques, simplextechniques technique.register(bandittechniques.AUCBanditMetaTechnique([ sjtechniques.FixedTechnique(seed_configs), differentialevolution.DifferentialEvolutionAlt(), evolutionarytechniques.UniformGreedyMutation(), evolutionarytechniques.NormalGreedyMutation(mutation_rate=0.3), simplextechniques.RandomNelderMead(), sjtechniques.ForceRemove(), sjtechniques.ForceFuse(), sjtechniques.ForceUnbox(), sjtechniques.ForceEqualDivision(), sjtechniques.CrossSocketBeforeHyperthreadingAffinity(), ], name = "StreamJITBandit")) mi = StreamJITMI(args, cfg, jvm_options, manipulator, FixedInputManager(), MinimizeTime()) m = TuningRunMain(mi, args) m.main()
def main(cls, args, *pargs, **kwargs):
from opentuner.tuningrunmain import TuningRunMain
return TuningRunMain(cls(args, *pargs, **kwargs), args,
measurement_driver = MeasurementClient).main()
if isinstance(p, sjparameters.sjCompositionParameter):
p.equal_division(seed_config)
elif isinstance(p, sjparameters.sjPermutationParameter):
pass #p.set_value(config, p.seed_value())
else:
seed_config[p.name] = p.value
seed_config['multiplier'] = m
seed_configs.append(seed_config)
# The default bandit, plus our custom techniques.
from opentuner.search import technique, bandittechniques, differentialevolution, evolutionarytechniques, simplextechniques
technique.register(
bandittechniques.AUCBanditMetaTechnique([
sjtechniques.FixedTechnique(seed_configs),
differentialevolution.DifferentialEvolutionAlt(),
evolutionarytechniques.UniformGreedyMutation(),
evolutionarytechniques.NormalGreedyMutation(mutation_rate=0.3),
simplextechniques.RandomNelderMead(),
sjtechniques.ForceRemove(),
sjtechniques.ForceFuse(),
sjtechniques.ForceUnbox(),
sjtechniques.ForceEqualDivision(),
sjtechniques.CrossSocketBeforeHyperthreadingAffinity(),
],
name="StreamJITBandit"))
mi = StreamJITMI(args, cfg, jvm_options, manipulator, FixedInputManager(),
MinimizeTime())
m = TuningRunMain(mi, args)
m.main()