Running ciw in parallel.ipynb

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   "source": [
    "import ciw\n",
    "import multiprocessing\n",
    "import numpy as np\n",
    "\n",
    "N = ciw.create_network(Arrival_distributions=[['Exponential', 0.2]],\n",
    "                       Service_distributions=[['Exponential', 0.1]],\n",
    "                       Number_of_servers=[3])\n",
    " \n",
    "def run_simulation(network, seed=0, max_time=10000):\n",
    "    ciw.seed(seed)\n",
    "    Q = ciw.Simulation(N)\n",
    "    Q.simulate_until_max_time(max_simulation_time=max_time)\n",
    "    recs = Q.get_all_records()\n",
    "    waits = [r.waiting_time for r in recs if r.arrival_date > 100 and r.arrival_date < 1540]\n",
    "    mean_wait = sum(waits) / len(waits)\n",
    "    return mean_wait"
   ]
  },
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   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
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   "outputs": [],
   "source": [
    "max_time = 500\n",
    "repetitions = 200"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1 loop, best of 3: 1.3 s per loop\n"
     ]
    }
   ],
   "source": [
    "%%timeit\n",
    "# In series\n",
    "\n",
    "average_waits = []\n",
    "for trial in range(repetitions):\n",
    "    average_waits.append(run_simulation(network=N, seed=trial, max_time=max_time))\n",
    "np.mean(average_waits)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1 loop, best of 3: 695 ms per loop\n"
     ]
    }
   ],
   "source": [
    "%%timeit\n",
    "# In parallel\n",
    "\n",
    "pool = multiprocessing.Pool(multiprocessing.cpu_count())\n",
    "args = [(N, trial, max_time) for trial in range(repetitions)]\n",
    "average_waits = pool.starmap(run_simulation, args)\n",
    "np.mean(average_waits)"
   ]
  }
 ],
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