{ "cells": [ { "metadata": {}, "cell_type": "markdown", "source": "### 2 maszyny - bez skalowania", "id": "434259c70359c18f" }, { "metadata": { "ExecuteTime": { "end_time": "2024-12-21T07:45:52.828283Z", "start_time": "2024-12-21T07:44:27.547304Z" } }, "cell_type": "code", "source": [ "import requests\n", "import random\n", "import math\n", "import time\n", "import threading\n", "import logging\n", "logging.getLogger().setLevel(logging.INFO)\n", "\n", "API_URL=\"http://s464863-lb-13561059.us-east-1.elb.amazonaws.com:8080/\"\n", "\n", "UNIT = 5.0 # secs\n", "\n", "# Pre generated primes\n", "first_primes_list = [2, 3, 5, 7, 11, 13, 17, 19, 23, 29,\n", " 31, 37, 41, 43, 47, 53, 59, 61, 67,\n", " 71, 73, 79, 83, 89, 97, 101, 103,\n", " 107, 109, 113, 127, 131, 137, 139,\n", " 149, 151, 157, 163, 167, 173, 179,\n", " 181, 191, 193, 197, 199, 211, 223,\n", " 227, 229, 233, 239, 241, 251, 257,\n", " 263, 269, 271, 277, 281, 283, 293,\n", " 307, 311, 313, 317, 331, 337, 347, 349]\n", "\n", "\n", "def nBitRandom(n):\n", " return random.randrange(2**(n-1)+1, 2**n - 1)\n", " \n", "def getLowLevelPrime(n):\n", " '''Generate a prime candidate divisible\n", " by first primes'''\n", " while True:\n", " # Obtain a random number\n", " pc = nBitRandom(n)\n", " \n", " # Test divisibility by pre-generated\n", " # primes\n", " for divisor in first_primes_list:\n", " if pc % divisor == 0 and divisor**2 <= pc:\n", " break\n", " else: return pc\n", " \n", "def isMillerRabinPassed(mrc):\n", " '''Run 20 iterations of Rabin Miller Primality test'''\n", " maxDivisionsByTwo = 0\n", " ec = mrc-1\n", " while ec % 2 == 0:\n", " ec >>= 1\n", " maxDivisionsByTwo += 1\n", " assert(2**maxDivisionsByTwo * ec == mrc-1)\n", " \n", " def trialComposite(round_tester):\n", " if pow(round_tester, ec, mrc) == 1:\n", " return False\n", " for i in range(maxDivisionsByTwo):\n", " if pow(round_tester, 2**i * ec, mrc) == mrc-1:\n", " return False\n", " return True\n", " \n", " # Set number of trials here\n", " numberOfRabinTrials = 20\n", " for i in range(numberOfRabinTrials):\n", " round_tester = random.randrange(2, mrc)\n", " if trialComposite(round_tester):\n", " return False\n", " return True\n", " \n", "def random_large_prime(bits):\n", " while True:\n", " prime_candidate = getLowLevelPrime(bits)\n", " if not isMillerRabinPassed(prime_candidate):\n", " continue\n", " else:\n", " return prime_candidate\n", "\n", "def thread_function(i, fast, timeout):\n", " start = time.time()\n", "\n", " c = 5 # bits: 20: 200ms; 21: 350ms; 22: 700ms 23: 1.5s; 25: 6s; 26: 10s; 27: 24s\n", " bits = 19 if fast else 23\n", " last_report = time.time()\n", " processing_time = 0.0\n", " reqs = 0\n", " while True:\n", " iter_start = time.time()\n", " if iter_start - start > timeout:\n", " logging.info(\"Thread: %d\\treqs: %d\\tmean time: %.3fs\\t%s\"%(i, reqs, processing_time/reqs if reqs>0 else 0.0, \"fast\\t\" if fast else \"\"))\n", " results[i][iter_start] = processing_time/reqs if reqs>0 else 0.0\n", " return\n", " if iter_start - last_report > UNIT/2:\n", " if len(results[i])%2 == 0:\n", " logging.info(\"Thread: %d\\treqs: %d\\tmean time: %.3fs\\t%s\"%(i, reqs, processing_time/reqs if reqs>0 else 0.0, \"fast\\t\" if fast else \"\"))\n", " results[i][iter_start] = processing_time/reqs if reqs>0 else 0.0\n", " processing_time = 0.0\n", " reqs = 0\n", " last_report=iter_start\n", "\n", " factors = [random_large_prime(bits) for i in range(c)]\n", " factors.sort()\n", " n=math.prod(factors)\n", "\n", " r = requests.get(API_URL+'/factors/%d'%(n))\n", " if r.status_code != 200:\n", " logging.error(\"wrong status code from webservice\")\n", " else:\n", " result = r.json()\n", " if result != factors:\n", " logging.error(\"Wrong factors\")\n", "\n", " processing_time+=time.time() - iter_start\n", " reqs+=1\n", " time.sleep(0.5)\n", "\n", "START = time.time()\n", "slow_threads = 4\n", "\n", "results = [ {} for i in range(slow_threads+1)]\n", "\n", "t0 = threading.Thread(target=thread_function, args=(0, True, (5 + slow_threads*3) * UNIT))\n", "t0.start()\n", "time.sleep(2 * UNIT)\n", "for i in range(slow_threads):\n", " t = threading.Thread(target=thread_function, args=(i+1, False, (slow_threads-i) * 3 * UNIT))\n", " t.start()\n", " time.sleep(2 * UNIT)\n", "\n", "t0.join()" ], "id": "666144f984e22119", "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "INFO:root:Thread: 0\treqs: 3\tmean time: 0.384s\tfast\t\n", "INFO:root:Thread: 0\treqs: 3\tmean time: 0.379s\tfast\t\n", "INFO:root:Thread: 0\treqs: 3\tmean time: 0.382s\tfast\t\n", "INFO:root:Thread: 1\treqs: 2\tmean time: 1.348s\t\n", "INFO:root:Thread: 0\treqs: 3\tmean time: 0.371s\tfast\t\n", "INFO:root:Thread: 1\treqs: 2\tmean time: 1.383s\t\n", "INFO:root:Thread: 0\treqs: 3\tmean time: 0.380s\tfast\t\n", "INFO:root:Thread: 2\treqs: 2\tmean time: 1.450s\t\n", "INFO:root:Thread: 1\treqs: 2\tmean time: 1.403s\t\n", "INFO:root:Thread: 0\treqs: 3\tmean time: 0.397s\tfast\t\n", "INFO:root:Thread: 2\treqs: 2\tmean time: 1.522s\t\n", "INFO:root:Thread: 3\treqs: 2\tmean time: 1.761s\t\n", "INFO:root:Thread: 1\treqs: 1\tmean time: 2.168s\t\n", "INFO:root:Thread: 0\treqs: 3\tmean time: 0.681s\tfast\t\n", "INFO:root:Thread: 2\treqs: 2\tmean time: 1.294s\t\n", "INFO:root:Thread: 3\treqs: 1\tmean time: 2.006s\t\n", "INFO:root:Thread: 0\treqs: 2\tmean time: 0.751s\tfast\t\n", "INFO:root:Thread: 1\treqs: 2\tmean time: 2.080s\t\n", "INFO:root:Thread: 4\treqs: 2\tmean time: 2.193s\t\n", "INFO:root:Thread: 2\treqs: 1\tmean time: 2.307s\t\n", "INFO:root:Thread: 3\treqs: 2\tmean time: 1.567s\t\n", "INFO:root:Thread: 0\treqs: 2\tmean time: 1.124s\tfast\t\n", "INFO:root:Thread: 4\treqs: 1\tmean time: 2.090s\t\n", "INFO:root:Thread: 1\treqs: 2\tmean time: 2.061s\t\n", "INFO:root:Thread: 2\treqs: 2\tmean time: 1.488s\t\n", "INFO:root:Thread: 4\treqs: 2\tmean time: 1.430s\t\n", "INFO:root:Thread: 0\treqs: 2\tmean time: 1.017s\tfast\t\n", "INFO:root:Thread: 3\treqs: 2\tmean time: 1.454s\t\n", "INFO:root:Thread: 3\treqs: 1\tmean time: 1.419s\t\n", "INFO:root:Thread: 1\treqs: 2\tmean time: 1.411s\t\n", "INFO:root:Thread: 2\treqs: 2\tmean time: 1.315s\t\n", "INFO:root:Thread: 0\treqs: 2\tmean time: 0.887s\tfast\t\n", "INFO:root:Thread: 2\treqs: 2\tmean time: 1.469s\t\n", "INFO:root:Thread: 0\treqs: 3\tmean time: 0.351s\tfast\t\n", "INFO:root:Thread: 1\treqs: 2\tmean time: 1.454s\t\n", "INFO:root:Thread: 1\treqs: 1\tmean time: 1.375s\t\n", "INFO:root:Thread: 0\treqs: 3\tmean time: 0.377s\tfast\t\n", "INFO:root:Thread: 0\treqs: 3\tmean time: 0.378s\tfast\t\n", "INFO:root:Thread: 0\treqs: 3\tmean time: 0.392s\tfast\t\n", "INFO:root:Thread: 0\treqs: 1\tmean time: 0.363s\tfast\t\n" ] } ], "execution_count": 5 }, { "metadata": { "ExecuteTime": { "end_time": "2024-12-21T07:46:10.757734Z", "start_time": "2024-12-21T07:46:10.661303Z" } }, "cell_type": "code", "source": [ "import numpy as np\n", "import matplotlib.pyplot as plt\n", "import scipy.stats as stats\n", "mu = 0\n", "std = 1\n", "for i, result in enumerate(results):\n", " x = [(x - START)/UNIT for x in result.keys()]\n", " y = result.values()\n", " plt.plot(x, y, label=\"t%d\"%(i,))\n", "\n", "plt.legend()\n", "plt.show()" ], "id": "e3e72d6479cc9ba7", "outputs": [ { "data": { "text/plain": [ "
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" 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