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walac/load_balancer.ipynb

Created August 24, 2022 16:29
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load_balancer.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 2,
"id": "b56da36a",
"metadata": {},
"outputs": [],
"source": [
"# load the data from json files\n",
"\n",
"import json\n",
"import numpy as np\n",
"import os.path as path\n",
"import glob\n",
"from collections import defaultdict\n",
"\n",
"data = defaultdict(dict)\n",
"for fname in glob.glob('*.json', root_dir='data'):\n",
" with open(path.join('data', fname), 'r') as f:\n",
" d = json.load(f)\n",
" times = np.array(d['loadBalanceTimes']) / 1000\n",
" data[d['kernel'].split()[0]][d['cpuCores']] = times"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "3fbb7a29",
"metadata": {},
"outputs": [],
"source": [
"import yaml\n",
"\n",
"# get an ordered list of rt and stock kernel versions plus the list\n",
"# of number of cpus in which they were tested\n",
"\n",
"def is_rt(kernel):\n",
" return '-rt' in kernel\n",
"\n",
"def kernel_version(kernel):\n",
" major, minor, patch = tuple(map(lambda x: int(x), kernel.split('-')[0].split('.')))\n",
" return major * 10000 + minor * 100 + patch\n",
"\n",
"rt = list(filter(is_rt, data.keys()))\n",
"stock = list(filter(lambda x: not is_rt(x), data.keys()))\n",
"rt.sort(key=kernel_version)\n",
"stock.sort(key=kernel_version)\n",
"kconf = yaml.load(open('kconf.yml', 'r'), yaml.SafeLoader)\n",
"cpus = kconf['num_cpus']\n",
"cpus.sort()\n",
"\n",
"all_kernels = rt+stock"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "23135c99",
"metadata": {
"scrolled": true
},
"outputs": [],
"source": [
"# calculate the average and max times for all kernels\n",
"import pandas as pd\n",
"\n",
"means = [[data[k][c].mean() for c in cpus] for k in all_kernels]\n",
"means = pd.DataFrame(means, index=all_kernels, columns=cpus)\n",
"\n",
"max_values = [[data[k][c].max() for c in cpus] for k in all_kernels]\n",
"max_values = pd.DataFrame(max_values, index=all_kernels, columns=cpus)\n",
"\n",
"stds = [[data[k][c].std() for c in cpus] for k in all_kernels]\n",
"stds = pd.DataFrame(stds, index=all_kernels, columns=cpus)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "aacf5179",
"metadata": {},
"outputs": [],
"source": [
"import matplotlib.pyplot as plt\n",
"\n",
"colors = ['r', 'g', 'b', 'c', 'm', 'y', 'r', 'g', 'b']\n",
"\n",
"# Plot a bar graph for all kernels listed\n",
"def plot(data, kernels, title):\n",
" plt.figure(figsize=[30, 12])\n",
" wd = 0.1\n",
" x_pos = np.arange(1, 2*len(kernels), 2)\n",
" for i, (cpu, color) in enumerate(zip(cpus, colors)):\n",
" plt.bar(x_pos+wd*i, data[cpu][kernels].values, color=color, width=wd, label=f'{cpu} cpus')\n",
" plt.xticks(x_pos+wd, kernels, fontsize=15)\n",
" plt.yticks(fontsize=15)\n",
" plt.title(title, fontsize=20)\n",
" plt.xlabel('Kernels', fontsize=17)\n",
" plt.ylabel('Time (us)', fontsize=17)\n",
"\n",
" plt.legend(loc='upper right', fontsize=15)\n",
" plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "659ce9ca",
"metadata": {},
"outputs": [
{
"data": {
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"text/plain": [
"<Figure size 2160x864 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plot(means, stock, 'Average times (stock)')"
]
},
{
"cell_type": "markdown",
"id": "6832e051",
"metadata": {},
"source": [
"## Guilty patch\n",
"\n",
"```diff\n",
"commit c5b0a7eefc70150caf23e37bc9d639c68c87a097\n",
"Author: Vincent Guittot <vincent.guittot@linaro.org>\n",
"Date: Tue Oct 19 14:35:36 2021 +0200\n",
"\n",
" sched/fair: Remove sysctl_sched_migration_cost condition\n",
" \n",
" With a default value of 500us, sysctl_sched_migration_cost is\n",
" significanlty higher than the cost of load_balance. Remove the\n",
" condition and rely on the sd->max_newidle_lb_cost to abort\n",
" newidle_balance.\n",
" \n",
" Suggested-by: Peter Zijlstra (Intel) <peterz@infradead.org>\n",
" Signed-off-by: Vincent Guittot <vincent.guittot@linaro.org>\n",
" Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org>\n",
" Reviewed-by: Dietmar Eggemann <dietmar.eggemann@arm.com>\n",
" Acked-by: Mel Gorman <mgorman@suse.de>\n",
" Link: https://lore.kernel.org/r/20211019123537.17146-5-vincent.guittot@linaro.org\n",
"\n",
"diff --git a/kernel/sched/fair.c b/kernel/sched/fair.c\n",
"index e50fd751e1df..57eae0ebc492 100644\n",
"--- a/kernel/sched/fair.c\n",
"+++ b/kernel/sched/fair.c\n",
"@@ -10895,8 +10895,7 @@ static int newidle_balance(struct rq *this_rq, struct rq_flags *rf)\n",
" rcu_read_lock();\n",
" sd = rcu_dereference_check_sched_domain(this_rq->sd);\n",
" \n",
"- if (this_rq->avg_idle < sysctl_sched_migration_cost ||\n",
"- !READ_ONCE(this_rq->rd->overload) ||\n",
"+ if (!READ_ONCE(this_rq->rd->overload) ||\n",
" (sd && this_rq->avg_idle < sd->max_newidle_lb_cost)) {\n",
" \n",
" if (sd)\n",
"```"
]
},
{
"cell_type": "markdown",
"id": "523f7b73",
"metadata": {},
"source": [
"## Results\n",
"\n",
"Max latency for RT kernels. All values are in microseconds.\n",
"\n",
"#### Hyperthreads disabled\n",
"\n",
"| | with c5b0a | revert c5b0a |\n",
"|---|---|---|\n",
"| RHEL 9.1 | 220 | 172 |\n",
"| 5.19-rt | 183 | 71 |\n",
"\n",
"#### Hyperthreads enabled\n",
"\n",
"| | with c5b0a | revert c5b0a |\n",
"|---|---|---|\n",
"| RHEL 9.1 | | |\n",
"| 5.19-rt | 756 | 772 |"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "ccb89e77",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 2160x864 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
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"text/plain": [
"<Figure size 2160x864 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
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"text/plain": [
"<Figure size 2160x864 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"\n",
"plot(means, rt[:-4], 'Average times (rt)')\n",
"plot(means, rt[:-2], 'Average times (rt)')\n",
"plot(means, rt[-4:], 'Average times (rt)')"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "f25f9ca3",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
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" <th></th>\n",
" <th>10</th>\n",
" <th>20</th>\n",
" <th>40</th>\n",
" <th>60</th>\n",
" <th>80</th>\n",
" <th>100</th>\n",
" <th>120</th>\n",
" <th>140</th>\n",
" <th>160</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>5.10.0-ktest</th>\n",
" <td>9.796156</td>\n",
" <td>11.641393</td>\n",
" <td>12.534812</td>\n",
" <td>8.697206</td>\n",
" <td>11.824197</td>\n",
" <td>13.080062</td>\n",
" <td>16.069259</td>\n",
" <td>17.245967</td>\n",
" <td>22.368068</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5.11.0-ktest</th>\n",
" <td>9.987513</td>\n",
" <td>12.174893</td>\n",
" <td>13.214828</td>\n",
" <td>9.357904</td>\n",
" <td>12.282240</td>\n",
" <td>13.254661</td>\n",
" <td>16.226996</td>\n",
" <td>19.557279</td>\n",
" <td>22.628984</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5.12.0-ktest</th>\n",
" <td>9.872534</td>\n",
" <td>11.609691</td>\n",
" <td>13.453011</td>\n",
" <td>11.007255</td>\n",
" <td>12.007578</td>\n",
" <td>13.897064</td>\n",
" <td>15.607033</td>\n",
" <td>18.520705</td>\n",
" <td>21.577019</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5.13.0-ktest</th>\n",
" <td>10.583872</td>\n",
" <td>11.896129</td>\n",
" <td>13.558999</td>\n",
" <td>9.455872</td>\n",
" <td>12.218016</td>\n",
" <td>14.033772</td>\n",
" <td>15.982749</td>\n",
" <td>18.311325</td>\n",
" <td>21.097525</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5.14.0-ktest</th>\n",
" <td>9.957747</td>\n",
" <td>12.314362</td>\n",
" <td>13.795096</td>\n",
" <td>11.174933</td>\n",
" <td>12.102504</td>\n",
" <td>13.955532</td>\n",
" <td>15.568684</td>\n",
" <td>19.246415</td>\n",
" <td>21.436320</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5.15.0-ktest</th>\n",
" <td>10.449335</td>\n",
" <td>12.518478</td>\n",
" <td>13.471987</td>\n",
" <td>10.523062</td>\n",
" <td>12.560469</td>\n",
" <td>13.577170</td>\n",
" <td>15.198178</td>\n",
" <td>19.075755</td>\n",
" <td>20.952068</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5.16.0</th>\n",
" <td>13.827413</td>\n",
" <td>14.818815</td>\n",
" <td>74.375504</td>\n",
" <td>81.465400</td>\n",
" <td>80.635558</td>\n",
" <td>64.758540</td>\n",
" <td>40.718223</td>\n",
" <td>33.717376</td>\n",
" <td>36.447582</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5.17.0</th>\n",
" <td>11.693248</td>\n",
" <td>15.726820</td>\n",
" <td>80.848902</td>\n",
" <td>81.295429</td>\n",
" <td>82.162155</td>\n",
" <td>62.266276</td>\n",
" <td>39.209805</td>\n",
" <td>35.716142</td>\n",
" <td>35.964888</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5.18.0</th>\n",
" <td>10.841829</td>\n",
" <td>18.829552</td>\n",
" <td>79.551678</td>\n",
" <td>81.767706</td>\n",
" <td>80.222010</td>\n",
" <td>64.404079</td>\n",
" <td>43.195470</td>\n",
" <td>32.230191</td>\n",
" <td>32.233826</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5.19.0-rc5</th>\n",
" <td>10.527800</td>\n",
" <td>16.407641</td>\n",
" <td>80.357915</td>\n",
" <td>80.737142</td>\n",
" <td>82.082389</td>\n",
" <td>63.527779</td>\n",
" <td>42.379839</td>\n",
" <td>33.585124</td>\n",
" <td>40.258227</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" 10 20 40 60 80 \\\n",
"5.10.0-ktest 9.796156 11.641393 12.534812 8.697206 11.824197 \n",
"5.11.0-ktest 9.987513 12.174893 13.214828 9.357904 12.282240 \n",
"5.12.0-ktest 9.872534 11.609691 13.453011 11.007255 12.007578 \n",
"5.13.0-ktest 10.583872 11.896129 13.558999 9.455872 12.218016 \n",
"5.14.0-ktest 9.957747 12.314362 13.795096 11.174933 12.102504 \n",
"5.15.0-ktest 10.449335 12.518478 13.471987 10.523062 12.560469 \n",
"5.16.0 13.827413 14.818815 74.375504 81.465400 80.635558 \n",
"5.17.0 11.693248 15.726820 80.848902 81.295429 82.162155 \n",
"5.18.0 10.841829 18.829552 79.551678 81.767706 80.222010 \n",
"5.19.0-rc5 10.527800 16.407641 80.357915 80.737142 82.082389 \n",
"\n",
" 100 120 140 160 \n",
"5.10.0-ktest 13.080062 16.069259 17.245967 22.368068 \n",
"5.11.0-ktest 13.254661 16.226996 19.557279 22.628984 \n",
"5.12.0-ktest 13.897064 15.607033 18.520705 21.577019 \n",
"5.13.0-ktest 14.033772 15.982749 18.311325 21.097525 \n",
"5.14.0-ktest 13.955532 15.568684 19.246415 21.436320 \n",
"5.15.0-ktest 13.577170 15.198178 19.075755 20.952068 \n",
"5.16.0 64.758540 40.718223 33.717376 36.447582 \n",
"5.17.0 62.266276 39.209805 35.716142 35.964888 \n",
"5.18.0 64.404079 43.195470 32.230191 32.233826 \n",
"5.19.0-rc5 63.527779 42.379839 33.585124 40.258227 "
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"means.loc[stock]"
]
}
],
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