Job operations are not parallelizable

Bắt đầu bằng cách chạy ví dụ multiprocessing.Pool được báo cáo với exec_job, sau đó lần theo các điểm vào solver.submit() và job.get_results() được SimulatedBifurcationMachine sử dụng. So sánh các dấu thời gian của cả hai worker và xác định nơi việc gửi hoặc truy xuất kết quả trở nên tuần tự. Được coi là hoàn tất khi các job độc lập có thể được gửi và xử lý đồng thời mà không gặp độ trễ vài phút đã quan sát.

I'm trying to submit and process results of multiple jobs in parallel but I'm noticing that, in many cases, jobs are submitted sequentially.

import datetime
import imp
from multiprocessing import Pool
from azure.quantum import Workspace
from azure.quantum.optimization import Problem, ProblemType, Term
from azure.quantum.target.toshiba import SimulatedBifurcationMachine
import logging


def create_problem():
    problem = Problem('Test_Problem', problem_type=ProblemType.pubo)
    problem.add_terms([
        Term(c=1, indices=[]),
        Term(c=2, indices=[1, 2]),
        Term(c=-3, indices=[1, 2]),
        Term(c=1, indices=[0, 2])
    ])
    return problem


def exec_job(no):
    workspace = Workspace (
        resource_id = "<workspace-id>",
        location= "<location>"
    )

    problem = create_problem()
    solver = SimulatedBifurcationMachine(workspace, loops=0, timeout=10)
    print(str(datetime.datetime.utcnow()), "\t[%d] solver.submit() start" % no)
    job = solver.submit(problem)
    print(str(datetime.datetime.utcnow()), "\t[%d] job.id=%s" % (no, str(job.id)))

    print(str(datetime.datetime.utcnow()), "\t[%d] job.get_results() start" % no)
    result = job.get_results()
    print(str(datetime.datetime.utcnow()), "\t[%d] job.details=%s" % (no, str(job.details)))


if __name__ == '__main__':
    logging.basicConfig(level=logging.DEBUG)

    njobs = 2
    with Pool(processes=njobs) as pool:
        pool.map(func=exec_job, iterable=range(njobs))

For the above, output is:
2022-04-21 18:40:23.466530 [0] solver.submit() start
2022-04-21 18:40:23.542727 [1] solver.submit() start
2022-04-21 18:40:28.752803 [1] job.id=810bc3bb-c1a2-11ec-baa1-b831b575aea6
2022-04-21 18:40:28.752803 [1] job.get_results() start
..........2022-04-21 18:40:52.826348 [1] job.details={..........}
2022-04-21 18:44:19.108243 [0] job.id=81018a8e-c1a2-11ec-adf4-b831b575aea6
2022-04-21 18:44:19.109211 [0] job.get_results() start
..........2022-04-21 18:44:42.799796 [0] job.details={..............}

You can see that job 1 was submitted and awaited while job 0 hasn't been submitted at the same time and was done 4 mins after the first job.