Parallel computing does not work fine for experiment. #172
Description
Parallel computing does not work fine for experiment.
Different values of max_workers (e.g., max_workers=1 and max_workers=10) consume the same computation time.
class Experiment:
def init(self, output_dir: str, jobs: List[Job], m_workers: int = 6):
"""Run an experiment to execute a list of jobs.
:param output_dir: Base directory where each job will save its results.
:param jobs: List of Jobs (from :py:mod:`jmetal.util.laboratory)`) to be executed.
:param m_workers: Maximum number of workers to execute the Jobs in parallel.
"""
self.jobs = jobs
self.m_workers = m_workers
self.output_dir = output_dir
self.job_data = []
def run(self) -> None:
with ProcessPoolExecutor(max_workers=10) as executor:
for job in self.jobs:
output_path = os.path.join(self.output_dir, job.algorithm_tag, job.problem_tag)
executor.submit(job.execute(output_path))
self.job_data.append(job.get_algorithm_data())