From d326cb150a222e48beb0dea1d63f79130a5382e7 Mon Sep 17 00:00:00 2001
From: Repo Updater <noreply@mpcdf.mpg.de>
Date: Mon, 14 Nov 2022 13:44:31 +0100
Subject: [PATCH] fb3c2462 Remove Process and Queue exercise
---
exercises/Parallel_Exercise.ipynb | 52 +--------
.../Parallel_Exercise_withsolution.ipynb | 106 +-----------------
2 files changed, 4 insertions(+), 154 deletions(-)
diff --git a/exercises/Parallel_Exercise.ipynb b/exercises/Parallel_Exercise.ipynb
index 214e4b8..df02eaf 100644
--- a/exercises/Parallel_Exercise.ipynb
+++ b/exercises/Parallel_Exercise.ipynb
@@ -94,54 +94,6 @@
"* Compare timings to ensure you benefit from the parallelization"
]
},
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Processes and queues\n",
- "* Goal: Implement a work queueing system for computing the squares of numbers\n",
- "* Create one `Queue` for the input data and one `Queue` for the output data (i.e. the results)\n",
- "* Make these the arguments of the function that is the target for the `Process` objects\n",
- "* Fill input `Queue` on the root process\n",
- "* Get the results from the output `Queue` and print them\n",
- "* Compare timings to check that you benefit from the parallelization\n",
- "* Extension: add index to parameter of worker function and put that on the return queue to sort the results\n",
- "* Extension: use this scheme to implement another parallelization of the Monte-Carlo computation of $\\pi$"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 3,
- "metadata": {},
- "outputs": [],
- "source": [
- "from multiprocessing import Queue, Process\n",
- "import time\n",
- "\n",
- "def worker_function(in_queue, out_queue):\n",
- " # loop over in_queue and put function results into out_queue\n",
- " time.sleep(0.1)\n",
- " \n",
- "\n",
- "# create queues\n",
- "# create worker processes\n",
- "number_processes = 3\n",
- "ps = [Process(target=worker_function, args=('fill out here', 'bla'))\n",
- " for _ in range(number_processes)]\n",
- "# start processes\n",
- "for p in ps:\n",
- " p.start()\n",
- "# add parameters to queue\n",
- "# now get the results \n",
- "# send stop signal to stop iteration\n",
- "# stop processes\n",
- "for p in ps:\n",
- " p.join()\n",
- "\n",
- "\n",
- "# compare timings for different numbers of processes"
- ]
- },
{
"cell_type": "markdown",
"metadata": {},
@@ -158,7 +110,7 @@
],
"metadata": {
"kernelspec": {
- "display_name": "Python 3",
+ "display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
@@ -172,7 +124,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.6.5"
+ "version": "3.9.7"
}
},
"nbformat": 4,
diff --git a/exercises/_solutions/Parallel_Exercise_withsolution.ipynb b/exercises/_solutions/Parallel_Exercise_withsolution.ipynb
index 47a6fdf..6e4293e 100644
--- a/exercises/_solutions/Parallel_Exercise_withsolution.ipynb
+++ b/exercises/_solutions/Parallel_Exercise_withsolution.ipynb
@@ -165,108 +165,6 @@
"%timeit list(map(get_pi_montecarlo, chunks))"
]
},
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Processes and queues\n",
- "* Goal: Implement a work queueing system for computing the squares of numbers\n",
- "* Create one `Queue` for the input data and one `Queue` for the output data (i.e. the results)\n",
- "* Make these the arguments of the function that is the target for the `Process` objects\n",
- "* Fill input `Queue` on the root process\n",
- "* Get the results from the output `Queue` and print them\n",
- "* Compare timings to check that you benefit from the parallelization\n",
- "* Extension: use this scheme to implement another parallelization of the Monte-Carlo computation of $\\pi$"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 6,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "[0, 1, 4, 9, 16, 25, 36, 49, 64, 81]\n",
- "1.04 s ± 5.48 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n",
- "310 ms ± 5.43 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n",
- "338 ms ± 32.1 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n"
- ]
- }
- ],
- "source": [
- "from multiprocessing import Queue, Process\n",
- "import time\n",
- "\n",
- "def worker_function(function, in_queue, out_queue):\n",
- " for index, parameter in iter(in_queue.get, 'STOP'):\n",
- " result = function(parameter)\n",
- " out_queue.put((index, result))\n",
- " \n",
- "\n",
- "def get_results(function, parameters, number_processes):\n",
- " # create queues\n",
- " in_queue = Queue()\n",
- " out_queue = Queue()\n",
- "\n",
- " # create worker processes\n",
- " ps = [Process(target=worker_function, args=(function, in_queue, out_queue))\n",
- " for _ in range(number_processes)]\n",
- " # start processes\n",
- " for p in ps:\n",
- " p.start()\n",
- " # add parameters to queue\n",
- " for i, x in enumerate(parameters):\n",
- " in_queue.put((i, x))\n",
- " # now get the results with indices\n",
- " indexed_results = [out_queue.get() for _ in range(len(parameters))]\n",
- " # send stop signal to stop iteration\n",
- " for _ in range(number_processes):\n",
- " in_queue.put('STOP')\n",
- " # sort and remove indices\n",
- " results = [x[1] for x in sorted(indexed_results)]\n",
- " # stop processes\n",
- " for p in ps:\n",
- " p.join()\n",
- " return results\n",
- "\n",
- "def square(x):\n",
- " time.sleep(0.1)\n",
- " return x**2\n",
- "\n",
- "print(get_results(square, range(10**1), 5))\n",
- "\n",
- "%timeit get_results(square, range(10), 1)\n",
- "%timeit get_results(square, range(10), 5)\n",
- "%timeit get_results(square, range(10), 10)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 7,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Approximation for pi: 3.143794\n",
- "1.16 s ± 59.7 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n",
- "568 ms ± 61.5 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n",
- "571 ms ± 39.8 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n"
- ]
- }
- ],
- "source": [
- "# now use this to compute pi\n",
- "pi = np.mean(get_results(get_pi_montecarlo, [10**5]*100, 10))\n",
- "print(\"Approximation for pi: {:f}\".format(pi))\n",
- "\n",
- "for number_processes in [1, 5, 10]:\n",
- " %timeit np.mean(get_results(get_pi_montecarlo, [10**5]*100, number_processes))"
- ]
- },
{
"cell_type": "markdown",
"metadata": {},
@@ -282,7 +180,7 @@
],
"metadata": {
"kernelspec": {
- "display_name": "Python 3",
+ "display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
@@ -296,7 +194,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.6.5"
+ "version": "3.9.7"
}
},
"nbformat": 4,
--
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