{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Análisis de la etapa de generación de medios" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import pandas as pd\n", "import matplotlib.pyplot as plt\n", "import numpy as np \n", "import plotly.express as px" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Armado del dataset\n", "\n", "En este paso parsearemos los archivos para obtener estadísticas sobre el tiempo que tarda cada ejecución de una función, sobre la memoria usada, el uso de CPU. Con esto buscamos identificar:\n", "- Qué funciones son las que consumen mayor cantidad de memoria\n", "- Qué funciones son las que tienen un mayor tiempo de procesamiento\n", "- Qué funciones son las que son invocadas una mayor cantidad de veces\n", "\n", "Una vez identificados estos puntos de análisis podemos proponer soluciones para mejorar estas estadísticas." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "def get_function_name(function_name):\n", " return function_name[10:].rsplit(\".c\")[0]" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "relations = {\n", " \"Py_kgeneration\": ['generate', 'fftma2'],\n", " \"generate\": [\"gasdev\"],\n", " \"gasdev\": [\"ran2\"],\n", " \"fftma2\": [\"covariance\", \"fourt\", \"prebuild_gwn\"]\n", "}" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "def get_data(file_name):\n", " data = []\n", " row = {}\n", "\n", " with open(file_name) as log_file:\n", " lines = log_file.readlines()\n", " for line in lines:\n", " split_line = line.split()\n", " \n", " if \"USED\" not in split_line and \"ELAPSED\" not in split_line and \"CPU\" not in split_line: continue\n", " \n", " if \"CPU\" in split_line:\n", " idx_cpu = split_line.index(\"CPU\") + 1\n", " idx_per = idx_cpu + 1\n", " row[\"cpu\"] = row.get('CPU', [])\n", " row[\"cpu\"].append(float(split_line[idx_per].rsplit(\"%\")[0]))\n", " continue\n", " \n", " idx_used_mem = split_line.index(\"USED\") + 4\n", " idx_elapsed = split_line.index(\"ELAPSED\") + 2\n", " \n", " function_name = get_function_name(split_line[2])\n", " \n", " used_virtual_mem = float(split_line[idx_used_mem])\n", " elapsed = float(split_line[idx_elapsed].rsplit(\",\")[0])\n", "\n", " row[\"function\"] = function_name\n", " row[\"memory\"] = used_virtual_mem \n", " row[\"time\"] = elapsed\n", " row[\"cpu\"] = sum(row[\"cpu\"]) / len(row[\"cpu\"])\n", " data.append(row)\n", " row = {}\n", " \n", " return data" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "def create_df(file_name):\n", " data = get_data(file_name)\n", " df = pd.DataFrame(data)\n", " return df.groupby(['function']).agg({'time': ['min', 'max', 'mean', 'sum', 'count'], 'memory': ['min', 'max', 'median'], 'cpu': ['min', 'max', 'mean']})" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "def analyze(file_name):\n", " df_grouped = create_df(file_name)\n", " return df_grouped.sort_values(by=('time', 'sum'), ascending=False) " ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "def merge_dfs(dfs):\n", " functions = ['Py_kgeneration', 'generate', 'fftma2', 'covariance', 'gasdev', 'fourt', 'cov_value', 'ran2', 'build_real', 'prebuild_gwn', 'clean_real', 'cgrid', 'length', 'maxfactor']\n", " df_final = pd.concat(dfs, join='inner').sort_values(by=('time', 'sum'), ascending=False) \n", "\n", " memory_min, memory_max, memory_median = [], [], []\n", " time_min, time_max, time_mean, time_sum, time_count = [], [], [], [], []\n", " cpu_min, cpu_max, cpu_mean = [], [], []\n", "\n", " for function in functions:\n", " memory_min.append(df_final.loc[function, ('memory', 'min')].min())\n", " time_min.append(df_final.loc[function, ('time', 'min')].min())\n", " cpu_min.append(df_final.loc[function, ('cpu', 'min')].min())\n", " memory_max.append(df_final.loc[function, ('memory', 'max')].max())\n", " time_max.append(df_final.loc[function, ('time', 'max')].max())\n", " cpu_max.append(df_final.loc[function, ('cpu', 'max')].max())\n", " time_mean.append(df_final.loc[function, ('time', 'mean')].mean())\n", " cpu_mean.append(df_final.loc[function, ('time', 'mean')].mean())\n", " time_sum.append(df_final.loc[function, ('time', 'sum')].sum())\n", " time_count.append(df_final.loc[function, ('time', 'count')].sum())\n", " try:\n", " memory_median.append(df_final.loc[function, ('memory', 'median')].median())\n", " except:\n", " memory_median.append(df_final.loc[function, ('memory', 'median')])\n", " \n", " df = pd.DataFrame({('memory', 'min'): memory_min, ('memory', 'max'): memory_max, ('memory', 'median'): memory_median, ('time', 'min'): time_min, ('time', 'max'): time_max, ('time', 'mean'): time_mean, ('time', 'sum'): time_sum, ('time', 'count'): time_count, ('cpu', 'min'): cpu_min, ('cpu', 'max'): cpu_max, ('cpu', 'mean'): cpu_mean})\n", "\n", " df.index = functions\n", " df.index.name = 'function'\n", " return df" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "def analyze(file_names):\n", " if len(file_names) == 1:\n", " df_grouped = create_df(file_names[0])\n", " return df_grouped.sort_values(by=('time', 'sum'), ascending=False)\n", " else:\n", " dfs = []\n", " for file_name in file_names:\n", " print(\"Executing file {}\".format(file_name))\n", " df = create_df(file_name)\n", " dfs.append(df)\n", " return merge_dfs(dfs)" ] }, { "cell_type": "code", "execution_count": 69, "metadata": {}, "outputs": [], "source": [ "def plot_pie(df, function, plt):\n", " \n", " labels = relations[function].copy()\n", " total = df.loc[function][('time', 'sum')]\n", " sizes = []\n", " explode = []\n", "\n", " rest = total\n", "\n", " for func in labels:\n", " func_duration = df.loc[func][('time', 'sum')]\n", " rest -= func_duration\n", " value = func_duration/ total\n", " sizes.append(value)\n", " explode.append(0 if value > 0.01 else 0.1)\n", "\n", " labels.append(\"other\")\n", " sizes.append(rest/total)\n", " sizes = np.array(sizes)\n", " porcent = 100.*sizes/sizes.sum()\n", " explode.append(0 if rest/total > 0.01 else 0.1)\n", "\n", " plt.set_title(function)\n", "\n", " patches, texts = plt.pie(sizes, startangle=90, radius=1.2)\n", " labels_formated = ['{0} - {1:1.2f} %'.format(i,j) for i,j in zip(labels, porcent)]\n", "\n", " sort_legend = True\n", " if sort_legend:\n", " patches, labels_formated, dummy = zip(*sorted(zip(patches, labels_formated, sizes),\n", " key=lambda x: x[2],\n", " reverse=True))\n", "\n", " plt.legend(patches, labels_formated, loc='upper left', bbox_to_anchor=(-0.1, 1.),\n", " fontsize=8)\n", " \n", " plt.axis('equal')\n", "\n", "def plot_analysis(df):\n", " fig, axs = plt.subplots(2, 2, dpi=100, figsize=(6, 6))\n", " fig.suptitle('Time comparisons')\n", " functions = list(relations.keys())\n", " for i in range(2):\n", " for j in range(2):\n", " plot_pie(df,functions[2*i + j], axs[i, j])\n", " " ] }, { "cell_type": "code", "execution_count": 70, "metadata": {}, "outputs": [], "source": [ "parents = {\n", " \"Py_kgeneration\": \"\",\n", " \"generate\": \"Py_kgeneration\",\n", " \"gasdev\": \"generate\",\n", " \"fftma2\": \"Py_kgeneration\",\n", " \"covariance\": \"fftma2\",\n", " \"fourt\": \"fftma2\",\n", " \"prebuild_gwn\": \"fftma2\",\n", " \"ran2\": \"gasdev\",\n", " \"cov_value\": \"covariance\",\n", "}\n", "\n", "def plot_treemap(df):\n", " df[\"parent\"] = [parents.get(item, \"\") for item in df.index]\n", " df2 = df.reset_index()\n", " df2[\"time_sum\"] = df2[[(\"time\", \"sum\")]]\n", " df2 = df2[[\"function\", \"parent\", \"time_sum\"]]\n", " fig3 = px.treemap(df2, names='function', parents='parent',values='time_sum', color=\"parent\")\n", " fig3.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## N = 8" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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timememorycpu
minmaxmeansumcountminmaxmedianminmaxmean
function
Py_kgeneration0.5735090.5735090.5735090.57350911.31.31.319.61219519.61219519.612195
generate0.4322660.4322660.4322660.43226610.80.80.820.10000020.10000020.100000
gasdev0.0000800.0232940.0006200.317450512-0.50.20.00.000000100.1000000.589648
fftma20.1387530.1387530.1387530.13875310.50.50.518.85000018.85000018.850000
covariance0.1358960.1358960.1358960.13589610.50.50.513.43333313.43333313.433333
ran20.0000770.0014760.0001320.0927257020.00.20.00.000000100.1000000.142593
cov_value0.0000800.0001540.0000840.058473700-0.20.20.00.0000000.1000000.000714
cgrid0.0012180.0012180.0012180.00121810.00.00.0100.100000100.100000100.100000
length0.0002660.0002680.0002670.00080230.00.00.00.0000000.0000000.000000
fourt0.0001220.0001380.0001300.00039130.00.00.00.0000000.0000000.000000
maxfactor0.0000790.0000800.0000790.00023830.00.00.00.0000000.0000000.000000
build_real0.0001040.0001040.0001040.00010410.00.00.00.0000000.0000000.000000
prebuild_gwn0.0000840.0000840.0000840.00008410.00.00.00.0000000.0000000.000000
clean_real0.0000820.0000820.0000820.00008210.00.00.00.0000000.0000000.000000
\n", "
" ], "text/plain": [ " time memory \\\n", " min max mean sum count min max \n", "function \n", "Py_kgeneration 0.573509 0.573509 0.573509 0.573509 1 1.3 1.3 \n", "generate 0.432266 0.432266 0.432266 0.432266 1 0.8 0.8 \n", "gasdev 0.000080 0.023294 0.000620 0.317450 512 -0.5 0.2 \n", "fftma2 0.138753 0.138753 0.138753 0.138753 1 0.5 0.5 \n", "covariance 0.135896 0.135896 0.135896 0.135896 1 0.5 0.5 \n", "ran2 0.000077 0.001476 0.000132 0.092725 702 0.0 0.2 \n", "cov_value 0.000080 0.000154 0.000084 0.058473 700 -0.2 0.2 \n", "cgrid 0.001218 0.001218 0.001218 0.001218 1 0.0 0.0 \n", "length 0.000266 0.000268 0.000267 0.000802 3 0.0 0.0 \n", "fourt 0.000122 0.000138 0.000130 0.000391 3 0.0 0.0 \n", "maxfactor 0.000079 0.000080 0.000079 0.000238 3 0.0 0.0 \n", "build_real 0.000104 0.000104 0.000104 0.000104 1 0.0 0.0 \n", "prebuild_gwn 0.000084 0.000084 0.000084 0.000084 1 0.0 0.0 \n", "clean_real 0.000082 0.000082 0.000082 0.000082 1 0.0 0.0 \n", "\n", " cpu \n", " median min max mean \n", "function \n", "Py_kgeneration 1.3 19.612195 19.612195 19.612195 \n", "generate 0.8 20.100000 20.100000 20.100000 \n", "gasdev 0.0 0.000000 100.100000 0.589648 \n", "fftma2 0.5 18.850000 18.850000 18.850000 \n", "covariance 0.5 13.433333 13.433333 13.433333 \n", "ran2 0.0 0.000000 100.100000 0.142593 \n", "cov_value 0.0 0.000000 0.100000 0.000714 \n", "cgrid 0.0 100.100000 100.100000 100.100000 \n", "length 0.0 0.000000 0.000000 0.000000 \n", "fourt 0.0 0.000000 0.000000 0.000000 \n", "maxfactor 0.0 0.000000 0.000000 0.000000 \n", "build_real 0.0 0.000000 0.000000 0.000000 \n", "prebuild_gwn 0.0 0.000000 0.000000 0.000000 \n", "clean_real 0.0 0.000000 0.000000 0.000000 " ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df = analyze(['log_8-aa'])\n", "df" ] }, { "cell_type": "code", "execution_count": 68, "metadata": {}, "outputs": [ { "data": { "image/png": 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timememorycpu
minmaxmeansumcountminmaxmedianminmaxmean
function
Py_kgeneration2.6739442.6739442.6739442.6739441-3.0-3.0-3.07.4770497.4770497.477049
generate1.9869831.9869831.9869831.9869831-4.1-4.1-4.110.26949210.26949210.269492
gasdev0.0000800.0233510.0003611.4797554096-3.10.50.00.000000100.1000000.271851
fftma20.6844550.6844550.6844550.68445511.11.11.10.1000000.1000000.100000
covariance0.6808620.6808620.6808620.68086211.11.11.10.1000000.1000000.100000
ran20.0000770.0013250.0000880.4649025268-1.60.50.00.0000000.1000000.000816
cov_value0.0000800.0001450.0000820.2932023564-1.30.20.00.0000000.1000000.000898
cgrid0.0012030.0012030.0012030.00120310.00.00.00.0000000.0000000.000000
fourt0.0003280.0004410.0003710.00111230.00.00.00.0000000.0000000.000000
length0.0002660.0002680.0002670.00080230.00.00.00.0000000.0000000.000000
maxfactor0.0000800.0000800.0000800.00024030.00.00.00.0000000.0000000.000000
build_real0.0001350.0001350.0001350.00013510.00.00.00.0000000.0000000.000000
prebuild_gwn0.0001000.0001000.0001000.00010010.00.00.00.0000000.0000000.000000
clean_real0.0000830.0000830.0000830.00008310.00.00.00.0000000.0000000.000000
\n", "
" ], "text/plain": [ " time memory \\\n", " min max mean sum count min max \n", "function \n", "Py_kgeneration 2.673944 2.673944 2.673944 2.673944 1 -3.0 -3.0 \n", "generate 1.986983 1.986983 1.986983 1.986983 1 -4.1 -4.1 \n", "gasdev 0.000080 0.023351 0.000361 1.479755 4096 -3.1 0.5 \n", "fftma2 0.684455 0.684455 0.684455 0.684455 1 1.1 1.1 \n", "covariance 0.680862 0.680862 0.680862 0.680862 1 1.1 1.1 \n", "ran2 0.000077 0.001325 0.000088 0.464902 5268 -1.6 0.5 \n", "cov_value 0.000080 0.000145 0.000082 0.293202 3564 -1.3 0.2 \n", "cgrid 0.001203 0.001203 0.001203 0.001203 1 0.0 0.0 \n", "fourt 0.000328 0.000441 0.000371 0.001112 3 0.0 0.0 \n", "length 0.000266 0.000268 0.000267 0.000802 3 0.0 0.0 \n", "maxfactor 0.000080 0.000080 0.000080 0.000240 3 0.0 0.0 \n", "build_real 0.000135 0.000135 0.000135 0.000135 1 0.0 0.0 \n", "prebuild_gwn 0.000100 0.000100 0.000100 0.000100 1 0.0 0.0 \n", "clean_real 0.000083 0.000083 0.000083 0.000083 1 0.0 0.0 \n", "\n", " cpu \n", " median min max mean \n", "function \n", "Py_kgeneration -3.0 7.477049 7.477049 7.477049 \n", "generate -4.1 10.269492 10.269492 10.269492 \n", "gasdev 0.0 0.000000 100.100000 0.271851 \n", "fftma2 1.1 0.100000 0.100000 0.100000 \n", "covariance 1.1 0.100000 0.100000 0.100000 \n", "ran2 0.0 0.000000 0.100000 0.000816 \n", "cov_value 0.0 0.000000 0.100000 0.000898 \n", "cgrid 0.0 0.000000 0.000000 0.000000 \n", "fourt 0.0 0.000000 0.000000 0.000000 \n", "length 0.0 0.000000 0.000000 0.000000 \n", "maxfactor 0.0 0.000000 0.000000 0.000000 \n", "build_real 0.0 0.000000 0.000000 0.000000 \n", "prebuild_gwn 0.0 0.000000 0.000000 0.000000 \n", "clean_real 0.0 0.000000 0.000000 0.000000 " ] }, "execution_count": 59, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df = analyze(['log_16-aa'])\n", "df" ] }, { "cell_type": "code", "execution_count": 60, "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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timememorycpu
minmaxmeansumcountminmaxmedianminmaxmean
function
Py_kgeneration19.76313119.76313119.76313119.763131173.173.173.146.86185646.86185646.861856
generate14.64424814.64424814.64424814.644248131.731.731.760.99347160.99347160.993471
gasdev0.0000800.0236250.00033210.89314132768-3.12.50.00.000000100.1000001.942624
fftma25.1160145.1160145.1160145.116014141.441.441.46.2264826.2264826.226482
covariance5.1038865.1038865.1038865.103886141.041.041.06.2386146.2386146.238614
ran20.0000770.0012410.0000833.45329541552-2.41.20.00.000000100.1000000.405054
cov_value0.0000800.0002540.0000892.19537924624-2.41.70.00.000000100.1000000.017077
fourt0.0023850.0033910.0027210.00816430.00.00.00.0000000.1000000.033333
cgrid0.0015900.0015900.0015900.00159010.00.00.00.0000000.0000000.000000
length0.0002700.0004580.0003950.00118530.00.00.00.0000000.0000000.000000
build_real0.0005360.0005360.0005360.00053610.00.00.00.0000000.0000000.000000
maxfactor0.0000800.0000820.0000810.00040550.00.00.00.0000000.0000000.000000
clean_real0.0002580.0002580.0002580.00025810.00.00.00.0000000.0000000.000000
prebuild_gwn0.0002360.0002360.0002360.00023610.40.40.40.0000000.0000000.000000
\n", "
" ], "text/plain": [ " time memory \\\n", " min max mean sum count min \n", "function \n", "Py_kgeneration 19.763131 19.763131 19.763131 19.763131 1 73.1 \n", "generate 14.644248 14.644248 14.644248 14.644248 1 31.7 \n", "gasdev 0.000080 0.023625 0.000332 10.893141 32768 -3.1 \n", "fftma2 5.116014 5.116014 5.116014 5.116014 1 41.4 \n", "covariance 5.103886 5.103886 5.103886 5.103886 1 41.0 \n", "ran2 0.000077 0.001241 0.000083 3.453295 41552 -2.4 \n", "cov_value 0.000080 0.000254 0.000089 2.195379 24624 -2.4 \n", "fourt 0.002385 0.003391 0.002721 0.008164 3 0.0 \n", "cgrid 0.001590 0.001590 0.001590 0.001590 1 0.0 \n", "length 0.000270 0.000458 0.000395 0.001185 3 0.0 \n", "build_real 0.000536 0.000536 0.000536 0.000536 1 0.0 \n", "maxfactor 0.000080 0.000082 0.000081 0.000405 5 0.0 \n", "clean_real 0.000258 0.000258 0.000258 0.000258 1 0.0 \n", "prebuild_gwn 0.000236 0.000236 0.000236 0.000236 1 0.4 \n", "\n", " cpu \n", " max median min max mean \n", "function \n", "Py_kgeneration 73.1 73.1 46.861856 46.861856 46.861856 \n", "generate 31.7 31.7 60.993471 60.993471 60.993471 \n", "gasdev 2.5 0.0 0.000000 100.100000 1.942624 \n", "fftma2 41.4 41.4 6.226482 6.226482 6.226482 \n", "covariance 41.0 41.0 6.238614 6.238614 6.238614 \n", "ran2 1.2 0.0 0.000000 100.100000 0.405054 \n", "cov_value 1.7 0.0 0.000000 100.100000 0.017077 \n", "fourt 0.0 0.0 0.000000 0.100000 0.033333 \n", "cgrid 0.0 0.0 0.000000 0.000000 0.000000 \n", "length 0.0 0.0 0.000000 0.000000 0.000000 \n", "build_real 0.0 0.0 0.000000 0.000000 0.000000 \n", "maxfactor 0.0 0.0 0.000000 0.000000 0.000000 \n", "clean_real 0.0 0.0 0.000000 0.000000 0.000000 \n", "prebuild_gwn 0.4 0.4 0.000000 0.000000 0.000000 " ] }, "execution_count": 62, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df = analyze(['log_32-aa'])\n", "df" ] }, { "cell_type": "code", "execution_count": 63, "metadata": {}, "outputs": [ { "data": { "image/png": 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plot_treemap(df)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## N = 64" ] }, { "cell_type": "code", "execution_count": 65, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Executing file log_64-aa\n", "Executing file log_64-ab\n" ] }, { "data": { "text/html": [ "
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memorytimecpu
minmaxmedianminmaxmeansumcountminmaxmean
function
Py_kgeneration2781.12781.12781.1173.931290173.931290173.931290173.9312901.019.90106919.901069173.931290
generate2781.22781.22781.2137.192987137.192987137.192987137.1929871.023.48921323.489213137.192987
fftma22.62.62.636.73782836.73782836.73782836.7378281.06.4980406.49804036.737828
covariance-1.8-1.8-1.836.63897836.63897836.63897836.6389781.06.5155066.51550636.638978
gasdev-54.911.10.00.0000760.0070250.000455101.718838262144.00.000000100.1000000.000455
fourt0.02.20.00.0248830.0409130.0302750.0908263.00.1000000.1000000.030275
cov_value-7.42.00.00.0000860.0002680.00009915.471843156816.00.000000100.1000000.000099
ran2-17.03.40.00.0000750.0025920.00011231.860609333450.00.000000100.1000000.000112
build_real0.00.00.00.0031700.0031700.0031700.0031701.00.1000000.1000000.003170
prebuild_gwn2.22.22.20.0010270.0010270.0010270.0010271.00.0000000.0000000.001027
clean_real0.70.70.70.0007070.0007070.0007070.0007071.00.0000000.0000000.000707
cgrid0.00.00.00.0016410.0016410.0016410.0016411.00.0000000.0000000.001641
length0.00.00.00.0003100.0005310.0003840.0011533.00.0000000.0000000.000384
maxfactor0.00.00.00.0000920.0000940.0000930.0003724.00.0000000.0000000.000093
\n", "
" ], "text/plain": [ " memory time \\\n", " min max median min max mean \n", "function \n", "Py_kgeneration 2781.1 2781.1 2781.1 173.931290 173.931290 173.931290 \n", "generate 2781.2 2781.2 2781.2 137.192987 137.192987 137.192987 \n", "fftma2 2.6 2.6 2.6 36.737828 36.737828 36.737828 \n", "covariance -1.8 -1.8 -1.8 36.638978 36.638978 36.638978 \n", "gasdev -54.9 11.1 0.0 0.000076 0.007025 0.000455 \n", "fourt 0.0 2.2 0.0 0.024883 0.040913 0.030275 \n", "cov_value -7.4 2.0 0.0 0.000086 0.000268 0.000099 \n", "ran2 -17.0 3.4 0.0 0.000075 0.002592 0.000112 \n", "build_real 0.0 0.0 0.0 0.003170 0.003170 0.003170 \n", "prebuild_gwn 2.2 2.2 2.2 0.001027 0.001027 0.001027 \n", "clean_real 0.7 0.7 0.7 0.000707 0.000707 0.000707 \n", "cgrid 0.0 0.0 0.0 0.001641 0.001641 0.001641 \n", "length 0.0 0.0 0.0 0.000310 0.000531 0.000384 \n", "maxfactor 0.0 0.0 0.0 0.000092 0.000094 0.000093 \n", "\n", " cpu \n", " sum count min max mean \n", "function \n", "Py_kgeneration 173.931290 1.0 19.901069 19.901069 173.931290 \n", "generate 137.192987 1.0 23.489213 23.489213 137.192987 \n", "fftma2 36.737828 1.0 6.498040 6.498040 36.737828 \n", "covariance 36.638978 1.0 6.515506 6.515506 36.638978 \n", "gasdev 101.718838 262144.0 0.000000 100.100000 0.000455 \n", "fourt 0.090826 3.0 0.100000 0.100000 0.030275 \n", "cov_value 15.471843 156816.0 0.000000 100.100000 0.000099 \n", "ran2 31.860609 333450.0 0.000000 100.100000 0.000112 \n", "build_real 0.003170 1.0 0.100000 0.100000 0.003170 \n", "prebuild_gwn 0.001027 1.0 0.000000 0.000000 0.001027 \n", "clean_real 0.000707 1.0 0.000000 0.000000 0.000707 \n", "cgrid 0.001641 1.0 0.000000 0.000000 0.001641 \n", "length 0.001153 3.0 0.000000 0.000000 0.000384 \n", "maxfactor 0.000372 4.0 0.000000 0.000000 0.000093 " ] }, "execution_count": 65, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df = analyze(['log_64-aa', 'log_64-ab'])\n", "df" ] }, { "cell_type": "code", "execution_count": 66, "metadata": {}, "outputs": [ { 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plot_treemap(df)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## N = 128" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "5897863\n" ] } ], "source": [ "df = analyze(['log_128-aa', 'log_128-ab', 'log_128-ac', 'log_128-ad', 'log_128-ae', 'log_128-af', 'log_128-ag', 'log_128-ah'])\n", "df" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "plot_analysis(df)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "plot_treemap(df)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## N = 256" ] }, { "cell_type": "code", "execution_count": 94, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Executing file number 1 out of 10\n", "Executing file number 2 out of 10\n", "Executing file number 3 out of 10\n", "Executing file number 4 out of 10\n", "Executing file number 5 out of 10\n", "Executing file number 6 out of 10\n", "Executing file number 7 out of 10\n", "Executing file number 8 out of 10\n", "Executing file number 9 out of 10\n", "Executing file number 10 out of 10\n" ] } ], "source": [ "df = analyze(['log_256-aa', 'log_256-ab', 'log_256-ac'])\n", "df" ] }, { "cell_type": "code", "execution_count": 96, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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memorytime
maxmedianmincountmaxmeanminsum
function
Py_kgeneration7421.67421.67421.61.01226.8225751226.8225751226.8225751226.822575
generate6691.76691.76691.71.0959.799368959.799368959.799368959.799368
fftma2872.0872.0872.01.0267.021516267.021516267.021516267.021516
covariance870.5870.5870.51.0247.512194247.512194247.512194247.512194
gasdev8.70.0-13.516777216.00.0013580.0000330.000000564.182445
fourt11.5-1.4-16.23.08.4298296.3784545.01500619.135362
cov_value0.70.0-13.98855600.00.0004370.0000020.00000121.579349
ran20.90.0-0.821359556.00.0003810.0000020.00000045.002553
build_real-0.2-0.2-0.21.00.1519680.1519680.1519680.151968
prebuild_gwn6.56.56.51.00.1081600.1081600.1081600.108160
clean_real127.2127.2127.21.00.0952670.0952670.0952670.095267
cgrid0.00.00.01.00.0001600.0001600.0001600.000160
length0.00.00.03.00.0000430.0000340.0000210.000102
maxfactor0.00.00.05.00.0000020.0000020.0000010.000008
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" ], "text/plain": [ " memory time \\\n", " max median min count max mean \n", "function \n", "Py_kgeneration 7421.6 7421.6 7421.6 1.0 1226.822575 1226.822575 \n", "generate 6691.7 6691.7 6691.7 1.0 959.799368 959.799368 \n", "fftma2 872.0 872.0 872.0 1.0 267.021516 267.021516 \n", "covariance 870.5 870.5 870.5 1.0 247.512194 247.512194 \n", "gasdev 8.7 0.0 -13.5 16777216.0 0.001358 0.000033 \n", "fourt 11.5 -1.4 -16.2 3.0 8.429829 6.378454 \n", "cov_value 0.7 0.0 -13.9 8855600.0 0.000437 0.000002 \n", "ran2 0.9 0.0 -0.8 21359556.0 0.000381 0.000002 \n", "build_real -0.2 -0.2 -0.2 1.0 0.151968 0.151968 \n", "prebuild_gwn 6.5 6.5 6.5 1.0 0.108160 0.108160 \n", "clean_real 127.2 127.2 127.2 1.0 0.095267 0.095267 \n", "cgrid 0.0 0.0 0.0 1.0 0.000160 0.000160 \n", "length 0.0 0.0 0.0 3.0 0.000043 0.000034 \n", "maxfactor 0.0 0.0 0.0 5.0 0.000002 0.000002 \n", "\n", " \n", " min sum \n", "function \n", "Py_kgeneration 1226.822575 1226.822575 \n", "generate 959.799368 959.799368 \n", "fftma2 267.021516 267.021516 \n", "covariance 247.512194 247.512194 \n", "gasdev 0.000000 564.182445 \n", "fourt 5.015006 19.135362 \n", "cov_value 0.000001 21.579349 \n", "ran2 0.000000 45.002553 \n", "build_real 0.151968 0.151968 \n", "prebuild_gwn 0.108160 0.108160 \n", "clean_real 0.095267 0.095267 \n", "cgrid 0.000160 0.000160 \n", "length 0.000021 0.000102 \n", "maxfactor 0.000001 0.000008 " ] }, "execution_count": 96, "metadata": {}, "output_type": "execute_result" } ], "source": [ "merge_dfs(dfs)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "plot_analysis(df)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "plot_treemap(df)" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.9" } }, "nbformat": 4, "nbformat_minor": 4 }