diff --git a/tools/AutoTuner/src/autotuner/utils/analysis.ipynb b/tools/AutoTuner/src/autotuner/utils/analysis.ipynb index a1c42ffaf9..0583f83c69 100644 --- a/tools/AutoTuner/src/autotuner/utils/analysis.ipynb +++ b/tools/AutoTuner/src/autotuner/utils/analysis.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 2, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -13,686 +13,104 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 22, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Stats for ray27-gcd-asap7.csv\n", - "{'count': minimum 50\n", - "time_this_iter_s 50\n", - "checkpoint_dir_name 0\n", - "dtype: int64, 'mean': minimum 43027.001480\n", - "time_this_iter_s 129.002546\n", - "checkpoint_dir_name NaN\n", - "dtype: float64, 'median': minimum 39909.185500\n", - "time_this_iter_s 126.479249\n", - "checkpoint_dir_name NaN\n", - "dtype: float64, 'mode': minimum 33020.88000\n", - "time_this_iter_s 114.58178\n", - "checkpoint_dir_name NaN\n", - "Name: 0, dtype: float64, 'range': minimum 24583.330000\n", - "time_this_iter_s 46.295713\n", - "checkpoint_dir_name NaN\n", - "dtype: float64, 'variance': minimum 6.953953e+07\n", - "time_this_iter_s 1.229625e+02\n", - "checkpoint_dir_name NaN\n", - "dtype: float64, 'std': minimum 8339.036228\n", - "time_this_iter_s 11.088847\n", - "checkpoint_dir_name NaN\n", - "dtype: float64}\n", - "Stats for ray28-gcd-asap7.csv\n", - "{'count': minimum 47\n", - "time_this_iter_s 47\n", - "dtype: int64, 'mean': minimum 47529.419626\n", - "time_this_iter_s 125.822000\n", - "dtype: float64, 'median': minimum 48573.710000\n", - "time_this_iter_s 124.566622\n", - "dtype: float64, 'mode': minimum 33001.380000\n", - "time_this_iter_s 113.097148\n", - "Name: 0, dtype: float64, 'range': minimum 26462.430000\n", - "time_this_iter_s 35.039207\n", - "dtype: float64, 'variance': minimum 5.603080e+07\n", - "time_this_iter_s 8.832202e+01\n", - "dtype: float64, 'std': minimum 7485.372431\n", - "time_this_iter_s 9.397980\n", - "dtype: float64}\n", - "Stats for ray29-gcd-asap7.csv\n", - "{'count': minimum 45\n", - "time_this_iter_s 45\n", - "dtype: int64, 'mean': minimum 43096.505353\n", - "time_this_iter_s 124.363728\n", - "dtype: float64, 'median': minimum 39854.225400\n", - "time_this_iter_s 122.287263\n", - "dtype: float64, 'mode': minimum 32160.990000\n", - "time_this_iter_s 104.342283\n", - "Name: 0, dtype: float64, 'range': minimum 24083.760000\n", - "time_this_iter_s 49.896306\n", - "dtype: float64, 'variance': minimum 5.323136e+07\n", - "time_this_iter_s 1.406109e+02\n", - "dtype: float64, 'std': minimum 7295.982553\n", - "time_this_iter_s 11.857945\n", - "dtype: float64}\n", - "Stats for ray27-gcd-sky130hd.csv\n", - "{'count': minimum 100\n", - "time_this_iter_s 100\n", - "checkpoint_dir_name 0\n", - "dtype: int64, 'mean': minimum 333.607803\n", - "time_this_iter_s 84.127418\n", - "checkpoint_dir_name NaN\n", - "dtype: float64, 'median': minimum 329.040550\n", - "time_this_iter_s 83.652841\n", - "checkpoint_dir_name NaN\n", - "dtype: float64, 'mode': minimum 312.96010\n", - "time_this_iter_s 73.13609\n", - "checkpoint_dir_name NaN\n", - "Name: 0, dtype: float64, 'range': minimum 51.472800\n", - "time_this_iter_s 25.864976\n", - "checkpoint_dir_name NaN\n", - "dtype: float64, 'variance': minimum 151.503752\n", - "time_this_iter_s 23.474365\n", - "checkpoint_dir_name NaN\n", - "dtype: float64, 'std': minimum 12.308686\n", - "time_this_iter_s 4.845035\n", - "checkpoint_dir_name NaN\n", - "dtype: float64}\n", - "Stats for ray28-gcd-sky130hd.csv\n", - "{'count': minimum 100\n", - "time_this_iter_s 100\n", - "dtype: int64, 'mean': minimum 337.795846\n", - "time_this_iter_s 84.703238\n", - "dtype: float64, 'median': minimum 333.684075\n", - "time_this_iter_s 83.578569\n", - "dtype: float64, 'mode': minimum 317.082600\n", - "time_this_iter_s 74.005778\n", - "Name: 0, dtype: float64, 'range': minimum 51.853000\n", - "time_this_iter_s 30.443296\n", - "dtype: float64, 'variance': minimum 178.783858\n", - "time_this_iter_s 36.299634\n", - "dtype: float64, 'std': minimum 13.371008\n", - "time_this_iter_s 6.024918\n", - "dtype: float64}\n", - "Stats for ray29-gcd-sky130hd.csv\n", - "{'count': minimum 100\n", - "time_this_iter_s 100\n", - "dtype: int64, 'mean': minimum 335.018666\n", - "time_this_iter_s 87.188756\n", - "dtype: float64, 'median': minimum 331.334565\n", - "time_this_iter_s 84.381221\n", - "dtype: float64, 'mode': minimum 314.676500\n", - "time_this_iter_s 74.774498\n", - "Name: 0, dtype: float64, 'range': minimum 61.700800\n", - "time_this_iter_s 162.659474\n", - "dtype: float64, 'variance': minimum 190.295493\n", - "time_this_iter_s 290.987368\n", - "dtype: float64, 'std': minimum 13.794763\n", - "time_this_iter_s 17.058352\n", - "dtype: float64}\n" + "Stats for 20240730/ray27-gcd-asap7.csv\n", + "{'count': 50, 'qor_mean': 43027.00148, 'qor_median': 39909.1855, 'qor_range': 24583.33, 'qor_variance': 69539525.20918523, 'qor_std': 8339.036227837436, 'qor_q1': 34906.445, 'time_this_iter_s_mean': 129.00254596233367, 'time_this_iter_s_median': 126.47924864292145, 'time_this_iter_s_range': 46.29571342468262, 'time_this_iter_s_variance': 122.96252032195649, 'time_this_iter_s_std': 11.088846663289942, 'time_this_iter_s_q1': 120.84304541349411}\n", + "Stats for 20240730/ray28-gcd-asap7.csv\n", + "{'count': 47, 'qor_mean': 47529.41962553191, 'qor_median': 48573.70999999999, 'qor_range': 26462.43, 'qor_variance': 56030800.4311545, 'qor_std': 7485.372431025359, 'qor_q1': 40408.8355, 'time_this_iter_s_mean': 125.82199966653864, 'time_this_iter_s_median': 124.56662249565125, 'time_this_iter_s_range': 35.039207458496094, 'time_this_iter_s_variance': 88.32201939262887, 'time_this_iter_s_std': 9.397979537785176, 'time_this_iter_s_q1': 117.59478962421417}\n", + "Stats for 20240730/ray29-gcd-asap7.csv\n", + "{'count': 45, 'qor_mean': 43096.50535333333, 'qor_median': 39854.2254, 'qor_range': 24083.76, 'qor_variance': 53231361.40965568, 'qor_std': 7295.982552724183, 'qor_q1': 37173.12, 'time_this_iter_s_mean': 124.36372783448961, 'time_this_iter_s_median': 122.28726267814636, 'time_this_iter_s_range': 49.896306276321425, 'time_this_iter_s_variance': 140.61085112320615, 'time_this_iter_s_std': 11.857944641598145, 'time_this_iter_s_q1': 115.71693086624146}\n", + "-------------------\n", + "Q1 for gcd asap7 {'ray27': 34906.445, 'ray28': 40408.8355, 'ray29': 37173.12}\n", + "Maximum Q1 value: 40408.8355\n", + "-------------------\n", + "Stats for 20240730/ray27-gcd-sky130hd.csv\n", + "{'count': 100, 'qor_mean': 333.60780336000005, 'qor_median': 329.04055, 'qor_range': 51.47280000000001, 'qor_variance': 151.50375216178034, 'qor_std': 12.308686045300707, 'qor_q1': 325.125525, 'time_this_iter_s_mean': 84.12741832494736, 'time_this_iter_s_median': 83.65284085273743, 'time_this_iter_s_range': 25.864976406097412, 'time_this_iter_s_variance': 23.474365209850927, 'time_this_iter_s_std': 4.845035109248531, 'time_this_iter_s_q1': 80.93566554784775}\n", + "Stats for 20240730/ray28-gcd-sky130hd.csv\n", + "{'count': 100, 'qor_mean': 337.79584639000007, 'qor_median': 333.684075, 'qor_range': 51.85300000000001, 'qor_variance': 178.78385830891395, 'qor_std': 13.371008126125492, 'qor_q1': 327.5811, 'time_this_iter_s_mean': 84.7032380270958, 'time_this_iter_s_median': 83.57856917381287, 'time_this_iter_s_range': 30.443295717239366, 'time_this_iter_s_variance': 36.299634139258515, 'time_this_iter_s_std': 6.024917770331684, 'time_this_iter_s_q1': 80.67235344648361}\n", + "Stats for 20240730/ray29-gcd-sky130hd.csv\n", + "{'count': 100, 'qor_mean': 335.018666099, 'qor_median': 331.334565, 'qor_range': 61.70079999999996, 'qor_variance': 190.29549259307922, 'qor_std': 13.794763230772727, 'qor_q1': 324.592925, 'time_this_iter_s_mean': 87.18875595808029, 'time_this_iter_s_median': 84.38122057914734, 'time_this_iter_s_range': 162.65947389602664, 'time_this_iter_s_variance': 290.9873684892825, 'time_this_iter_s_std': 17.058351869078166, 'time_this_iter_s_q1': 80.13077241182327}\n", + "-------------------\n", + "Q1 for gcd sky130hd {'ray27': 325.125525, 'ray28': 327.5811, 'ray29': 324.592925}\n", + "Maximum Q1 value: 327.5811\n", + "-------------------\n", + "Stats for 20240730/ray27-gcd-ihp-sg13g2.csv\n", + "{'count': 100, 'qor_mean': 267.48092019, 'qor_median': 256.95930000000004, 'qor_range': 122.9599, 'qor_variance': 974.7694521260026, 'qor_std': 31.22129805318803, 'qor_q1': 243.334975, 'time_this_iter_s_mean': 114.85475331544876, 'time_this_iter_s_median': 115.20528042316438, 'time_this_iter_s_range': 67.89155077934265, 'time_this_iter_s_variance': 248.2763736257262, 'time_this_iter_s_std': 15.75678817607593, 'time_this_iter_s_q1': 102.9160549044609}\n", + "Stats for 20240730/ray28-gcd-ihp-sg13g2.csv\n", + "{'count': 99, 'qor_mean': 270.9327165141415, 'qor_median': 260.3196, 'qor_range': 118.1676, 'qor_variance': 1130.9638686154046, 'qor_std': 33.629806253016156, 'qor_q1': 244.9645, 'time_this_iter_s_mean': 106.45020973561991, 'time_this_iter_s_median': 102.14248371124268, 'time_this_iter_s_range': 92.43899250030518, 'time_this_iter_s_variance': 365.8755052938873, 'time_this_iter_s_std': 19.127872471707022, 'time_this_iter_s_q1': 94.90646982192993}\n", + "Stats for 20240730/ray29-gcd-ihp-sg13g2.csv\n", + "{'count': 98, 'qor_mean': 265.051783622449, 'qor_median': 254.08825000000002, 'qor_range': 125.90309999999997, 'qor_variance': 982.8398214373394, 'qor_std': 31.35027625775153, 'qor_q1': 243.57935, 'time_this_iter_s_mean': 112.97350606139825, 'time_this_iter_s_median': 110.93965423107147, 'time_this_iter_s_range': 95.03484797477722, 'time_this_iter_s_variance': 245.46761874928606, 'time_this_iter_s_std': 15.667406254683193, 'time_this_iter_s_q1': 102.60060232877731}\n", + "-------------------\n", + "Q1 for gcd ihp-sg13g2 {'ray27': 243.334975, 'ray28': 244.9645, 'ray29': 243.57935}\n", + "Maximum Q1 value: 244.9645\n", + "-------------------\n", + "Stats for 20240730/ray27-aes-asap7.csv\n", + "{'count': 89, 'qor_mean': 76365.11696629213, 'qor_median': 73531.54, 'qor_range': 43416.689999999995, 'qor_variance': 83380756.73914638, 'qor_std': 9131.306409224606, 'qor_q1': 70370.02, 'time_this_iter_s_mean': 3909.322732060143, 'time_this_iter_s_median': 3457.629956483841, 'time_this_iter_s_range': 6243.933995723724, 'time_this_iter_s_variance': 1471831.5756431683, 'time_this_iter_s_std': 1213.1906592301016, 'time_this_iter_s_q1': 3163.334707975388}\n", + "Stats for 20240730/ray28-aes-asap7.csv\n", + "{'count': 85, 'qor_mean': 76587.15505882351, 'qor_median': 74257.22, 'qor_range': 58536.05999999999, 'qor_variance': 96935991.95043004, 'qor_std': 9845.607749165616, 'qor_q1': 70851.84000000001, 'time_this_iter_s_mean': 4254.110071112128, 'time_this_iter_s_median': 3752.1688289642334, 'time_this_iter_s_range': 4940.01443696022, 'time_this_iter_s_variance': 1776489.023419011, 'time_this_iter_s_std': 1332.849962831155, 'time_this_iter_s_q1': 3350.5559244155884}\n", + "Stats for 20240730/ray29-aes-asap7.csv\n", + "{'count': 91, 'qor_mean': 76875.9523076923, 'qor_median': 74900.92, 'qor_range': 63896.84, 'qor_variance': 106513209.82799797, 'qor_std': 10320.523718687824, 'qor_q1': 69675.44, 'time_this_iter_s_mean': 4059.540028587802, 'time_this_iter_s_median': 3473.943818569184, 'time_this_iter_s_range': 6451.522083997726, 'time_this_iter_s_variance': 1757353.2920761318, 'time_this_iter_s_std': 1325.6520252600724, 'time_this_iter_s_q1': 3251.2324138879776}\n", + "-------------------\n", + "Q1 for aes asap7 {'ray27': 70370.02, 'ray28': 70851.84000000001, 'ray29': 69675.44}\n", + "Maximum Q1 value: 70851.84000000001\n", + "-------------------\n", + "Stats for 20240730/ray27-aes-sky130hd.csv\n", + "{'count': 100, 'qor_mean': 557.9700366929999, 'qor_median': 555.2149999999999, 'qor_range': 141.60877000000005, 'qor_variance': 1129.915769103444, 'qor_std': 33.61421974556964, 'qor_q1': 531.645585, 'time_this_iter_s_mean': 2147.2896325206757, 'time_this_iter_s_median': 2131.3478298187256, 'time_this_iter_s_range': 2574.2651529312134, 'time_this_iter_s_variance': 182371.30033962103, 'time_this_iter_s_std': 427.0495291410834, 'time_this_iter_s_q1': 1860.4742531776433}\n", + "Stats for 20240730/ray28-aes-sky130hd.csv\n", + "{'count': 100, 'qor_mean': 558.3103719200001, 'qor_median': 553.0498, 'qor_range': 146.6417199999999, 'qor_variance': 1081.9498009572314, 'qor_std': 32.89300535003196, 'qor_q1': 532.98385, 'time_this_iter_s_mean': 2183.8264768815043, 'time_this_iter_s_median': 2108.631588101387, 'time_this_iter_s_range': 2877.529473543167, 'time_this_iter_s_variance': 245557.78323702683, 'time_this_iter_s_std': 495.5378726565981, 'time_this_iter_s_q1': 1799.0079539418218}\n", + "Stats for 20240730/ray29-aes-sky130hd.csv\n", + "{'count': 100, 'qor_mean': 562.558026781, 'qor_median': 562.0978250000001, 'qor_range': 123.75295299999999, 'qor_variance': 974.3474149388688, 'qor_std': 31.214538518755468, 'qor_q1': 537.0193174999999, 'time_this_iter_s_mean': 2028.8850155091286, 'time_this_iter_s_median': 1932.9161655902863, 'time_this_iter_s_range': 2493.8400864601135, 'time_this_iter_s_variance': 241786.6055208677, 'time_this_iter_s_std': 491.71801423261655, 'time_this_iter_s_q1': 1705.5352216362953}\n", + "-------------------\n", + "Q1 for aes sky130hd {'ray27': 531.645585, 'ray28': 532.98385, 'ray29': 537.0193174999999}\n", + "Maximum Q1 value: 537.0193174999999\n", + "-------------------\n", + "Stats for 20240730/ray27-aes-ihp-sg13g2.csv\n", + "{'count': 83, 'qor_mean': 557.3554152048193, 'qor_median': 548.3263, 'qor_range': 328.6799000000001, 'qor_variance': 2934.0939073513773, 'qor_std': 54.16727709006035, 'qor_q1': 523.46293, 'time_this_iter_s_mean': 5618.940455741193, 'time_this_iter_s_median': 5384.021718978882, 'time_this_iter_s_range': 22308.259251832962, 'time_this_iter_s_variance': 9719623.42777066, 'time_this_iter_s_std': 3117.6310602395947, 'time_this_iter_s_q1': 3636.360120177269}\n", + "Stats for 20240730/ray28-aes-ihp-sg13g2.csv\n", + "{'count': 92, 'qor_mean': 552.2387584347825, 'qor_median': 542.829, 'qor_range': 282.83070000000004, 'qor_variance': 1977.504018355496, 'qor_std': 44.46913557014006, 'qor_q1': 525.80005, 'time_this_iter_s_mean': 5202.011931269065, 'time_this_iter_s_median': 4988.8257023096085, 'time_this_iter_s_range': 8102.373443365097, 'time_this_iter_s_variance': 4185022.999063683, 'time_this_iter_s_std': 2045.732875784051, 'time_this_iter_s_q1': 3562.7876136302953}\n", + "Stats for 20240730/ray29-aes-ihp-sg13g2.csv\n", + "{'count': 93, 'qor_mean': 568.2079060215053, 'qor_median': 556.8970999999999, 'qor_range': 385.7513999999999, 'qor_variance': 3241.0655449037504, 'qor_std': 56.9303569715117, 'qor_q1': 535.7910999999999, 'time_this_iter_s_mean': 4340.748850284084, 'time_this_iter_s_median': 3543.0774805545807, 'time_this_iter_s_range': 34982.0858104229, 'time_this_iter_s_variance': 15058059.653731477, 'time_this_iter_s_std': 3880.4715762045566, 'time_this_iter_s_q1': 2869.6042470932007}\n", + "-------------------\n", + "Q1 for aes ihp-sg13g2 {'ray27': 523.46293, 'ray28': 525.80005, 'ray29': 535.7910999999999}\n", + "Maximum Q1 value: 535.7910999999999\n", + "-------------------\n", + "Stats for 20240730/ray27-ibex-asap7.csv\n", + "{'count': 98, 'qor_mean': 210868.38234693877, 'qor_median': 209223.51, 'qor_range': 43063.67999999999, 'qor_variance': 64695423.64843052, 'qor_std': 8043.346545339851, 'qor_q1': 205584.34750000003, 'time_this_iter_s_mean': 3634.5914097732425, 'time_this_iter_s_median': 3599.164971113205, 'time_this_iter_s_range': 1434.401823759078, 'time_this_iter_s_variance': 79581.02227225449, 'time_this_iter_s_std': 282.10108520219217, 'time_this_iter_s_q1': 3413.4663274288177}\n", + "Stats for 20240730/ray28-ibex-asap7.csv\n", + "{'count': 95, 'qor_mean': 208985.62063157896, 'qor_median': 207575.73, 'qor_range': 31646.610000000015, 'qor_variance': 41780455.650437884, 'qor_std': 6463.780291009115, 'qor_q1': 204219.655, 'time_this_iter_s_mean': 3303.8576516327107, 'time_this_iter_s_median': 3217.984939813614, 'time_this_iter_s_range': 1136.116209745407, 'time_this_iter_s_variance': 67927.34090166385, 'time_this_iter_s_std': 260.6287415111078, 'time_this_iter_s_q1': 3104.4721785783768}\n", + "Stats for 20240730/ray29-ibex-asap7.csv\n", + "{'count': 91, 'qor_mean': 210460.23615384617, 'qor_median': 208961.94, 'qor_range': 50443.01999999999, 'qor_variance': 65152438.55823504, 'qor_std': 8071.706050038929, 'qor_q1': 205678.545, 'time_this_iter_s_mean': 3576.2077652622056, 'time_this_iter_s_median': 3513.3161759376526, 'time_this_iter_s_range': 1582.5553004741664, 'time_this_iter_s_variance': 89354.94423412888, 'time_this_iter_s_std': 298.92297374763433, 'time_this_iter_s_q1': 3359.5693979263306}\n", + "-------------------\n", + "Q1 for ibex asap7 {'ray27': 205584.34750000003, 'ray28': 204219.655, 'ray29': 205678.545}\n", + "Maximum Q1 value: 205678.545\n", + "-------------------\n", + "Stats for 20240730/ray27-ibex-sky130hd.csv\n", + "{'count': 99, 'qor_mean': 1451.529284545455, 'qor_median': 1442.0791399999998, 'qor_range': 218.76405, 'qor_variance': 2821.492511463972, 'qor_std': 53.11772313892955, 'qor_q1': 1407.990365, 'time_this_iter_s_mean': 2423.0869750880233, 'time_this_iter_s_median': 1942.265698671341, 'time_this_iter_s_range': 6106.393856763839, 'time_this_iter_s_variance': 1495588.5369123127, 'time_this_iter_s_std': 1222.9425730230805, 'time_this_iter_s_q1': 1571.2147682905197}\n", + "Stats for 20240730/ray28-ibex-sky130hd.csv\n", + "{'count': 100, 'qor_mean': 1459.1225344299999, 'qor_median': 1448.9783, 'qor_range': 214.20714999999996, 'qor_variance': 2364.6978833513153, 'qor_std': 48.628159366269614, 'qor_q1': 1425.9959125, 'time_this_iter_s_mean': 2409.811683785915, 'time_this_iter_s_median': 2102.1462622880936, 'time_this_iter_s_range': 5390.993848323822, 'time_this_iter_s_variance': 1018585.1440624123, 'time_this_iter_s_std': 1009.2497926987215, 'time_this_iter_s_q1': 1715.205883026123}\n", + "Stats for 20240730/ray29-ibex-sky130hd.csv\n", + "{'count': 99, 'qor_mean': 1460.492545151515, 'qor_median': 1453.5119, 'qor_range': 216.38620000000014, 'qor_variance': 2852.9037933038016, 'qor_std': 53.412580852302966, 'qor_q1': 1414.6327999999999, 'time_this_iter_s_mean': 2505.095220298478, 'time_this_iter_s_median': 2180.4902305603027, 'time_this_iter_s_range': 12097.299293041231, 'time_this_iter_s_variance': 1797823.878394519, 'time_this_iter_s_std': 1340.8295485983738, 'time_this_iter_s_q1': 1917.6135770082471}\n", + "-------------------\n", + "Q1 for ibex sky130hd {'ray27': 1407.990365, 'ray28': 1425.9959125, 'ray29': 1414.6327999999999}\n", + "Maximum Q1 value: 1425.9959125\n", + "-------------------\n", + "Stats for 20240730/ray27-ibex-ihp-sg13g2.csv\n", + "{'count': 89, 'qor_mean': 1483.9112110561798, 'qor_median': 1464.566, 'qor_range': 580.76, 'qor_variance': 11419.93505492713, 'qor_std': 106.8640961919724, 'qor_q1': 1410.552, 'time_this_iter_s_mean': 5042.592064198483, 'time_this_iter_s_median': 4660.758789777756, 'time_this_iter_s_range': 23167.165396928787, 'time_this_iter_s_variance': 8240845.814732858, 'time_this_iter_s_std': 2870.68734186307, 'time_this_iter_s_q1': 3951.843639850617}\n", + "Stats for 20240730/ray28-ibex-ihp-sg13g2.csv\n", + "{'count': 88, 'qor_mean': 1497.0126304363635, 'qor_median': 1474.9433, 'qor_range': 655.4199999999998, 'qor_variance': 11564.437877992708, 'qor_std': 107.53807641013813, 'qor_q1': 1422.3090000000002, 'time_this_iter_s_mean': 4358.08595496958, 'time_this_iter_s_median': 4007.1067019701004, 'time_this_iter_s_range': 9731.753960847855, 'time_this_iter_s_variance': 2860429.574428256, 'time_this_iter_s_std': 1691.2804541022333, 'time_this_iter_s_q1': 3361.006528317928}\n", + "Stats for 20240730/ray29-ibex-ihp-sg13g2.csv\n", + "{'count': 94, 'qor_mean': 1468.906374680851, 'qor_median': 1440.995, 'qor_range': 574.4680000000001, 'qor_variance': 10389.976776936792, 'qor_std': 101.93123553129723, 'qor_q1': 1415.1480000000001, 'time_this_iter_s_mean': 5209.307440283451, 'time_this_iter_s_median': 5010.720875263214, 'time_this_iter_s_range': 8802.107405424118, 'time_this_iter_s_variance': 2284923.234800596, 'time_this_iter_s_std': 1511.5962538987042, 'time_this_iter_s_q1': 4152.796854197979}\n", + "-------------------\n", + "Q1 for ibex ihp-sg13g2 {'ray27': 1410.552, 'ray28': 1422.3090000000002, 'ray29': 1415.1480000000001}\n", + "Maximum Q1 value: 1422.3090000000002\n", + "-------------------\n" ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Stats for ray27-gcd-ihp-sg13g2.csv\n", - "{'count': minimum 100\n", - "time_this_iter_s 100\n", - "checkpoint_dir_name 0\n", - "dtype: int64, 'mean': minimum 267.480920\n", - "time_this_iter_s 114.854753\n", - "checkpoint_dir_name NaN\n", - "dtype: float64, 'median': minimum 256.95930\n", - "time_this_iter_s 115.20528\n", - "checkpoint_dir_name NaN\n", - "dtype: float64, 'mode': minimum 223.960000\n", - "time_this_iter_s 81.536851\n", - "checkpoint_dir_name NaN\n", - "Name: 0, dtype: float64, 'range': minimum 122.959900\n", - "time_this_iter_s 67.891551\n", - "checkpoint_dir_name NaN\n", - "dtype: float64, 'variance': minimum 974.769452\n", - "time_this_iter_s 248.276374\n", - "checkpoint_dir_name NaN\n", - "dtype: float64, 'std': minimum 31.221298\n", - "time_this_iter_s 15.756788\n", - "checkpoint_dir_name NaN\n", - "dtype: float64}\n", - "Stats for ray28-gcd-ihp-sg13g2.csv\n", - "{'count': minimum 99\n", - "time_this_iter_s 99\n", - "dtype: int64, 'mean': minimum 270.932717\n", - "time_this_iter_s 106.450210\n", - "dtype: float64, 'median': minimum 260.319600\n", - "time_this_iter_s 102.142484\n", - "dtype: float64, 'mode': minimum 227.368000\n", - "time_this_iter_s 81.673118\n", - "Name: 0, dtype: float64, 'range': minimum 118.167600\n", - "time_this_iter_s 92.438993\n", - "dtype: float64, 'variance': minimum 1130.963869\n", - "time_this_iter_s 365.875505\n", - "dtype: float64, 'std': minimum 33.629806\n", - "time_this_iter_s 19.127872\n", - "dtype: float64}\n", - "Stats for ray29-gcd-ihp-sg13g2.csv\n", - "{'count': minimum 98\n", - "time_this_iter_s 98\n", - "dtype: int64, 'mean': minimum 265.051784\n", - "time_this_iter_s 112.973506\n", - "dtype: float64, 'median': minimum 254.088250\n", - "time_this_iter_s 110.939654\n", - "dtype: float64, 'mode': minimum 218.757100\n", - "time_this_iter_s 84.829326\n", - "Name: 0, dtype: float64, 'range': minimum 125.903100\n", - "time_this_iter_s 95.034848\n", - "dtype: float64, 'variance': minimum 982.839821\n", - "time_this_iter_s 245.467619\n", - "dtype: float64, 'std': minimum 31.350276\n", - "time_this_iter_s 15.667406\n", - "dtype: float64}\n", - "Stats for ray27-aes-asap7.csv\n", - "{'count': minimum 89\n", - "time_this_iter_s 89\n", - "checkpoint_dir_name 0\n", - "dtype: int64, 'mean': minimum 76365.116966\n", - "time_this_iter_s 3909.322732\n", - "checkpoint_dir_name NaN\n", - "dtype: float64, 'median': minimum 73531.540000\n", - "time_this_iter_s 3457.629956\n", - "checkpoint_dir_name NaN\n", - "dtype: float64, 'mode': minimum 63116.270000\n", - "time_this_iter_s 2909.953124\n", - "checkpoint_dir_name NaN\n", - "Name: 0, dtype: float64, 'range': minimum 43416.690000\n", - "time_this_iter_s 6243.933996\n", - "checkpoint_dir_name NaN\n", - "dtype: float64, 'variance': minimum 8.338076e+07\n", - "time_this_iter_s 1.471832e+06\n", - "checkpoint_dir_name NaN\n", - "dtype: float64, 'std': minimum 9131.306409\n", - "time_this_iter_s 1213.190659\n", - "checkpoint_dir_name NaN\n", - "dtype: float64}\n", - "Stats for ray28-aes-asap7.csv\n", - "{'count': minimum 85\n", - "time_this_iter_s 85\n", - "dtype: int64, 'mean': minimum 76587.155059\n", - "time_this_iter_s 4254.110071\n", - "dtype: float64, 'median': minimum 74257.220000\n", - "time_this_iter_s 3752.168829\n", - "dtype: float64, 'mode': minimum 63845.230000\n", - "time_this_iter_s 3023.127349\n", - "Name: 0, dtype: float64, 'range': minimum 58536.060000\n", - "time_this_iter_s 4940.014437\n", - "dtype: float64, 'variance': minimum 9.693599e+07\n", - "time_this_iter_s 1.776489e+06\n", - "dtype: float64, 'std': minimum 9845.607749\n", - "time_this_iter_s 1332.849963\n", - "dtype: float64}\n", - "Stats for ray29-aes-asap7.csv\n", - "{'count': minimum 91\n", - "time_this_iter_s 91\n", - "dtype: int64, 'mean': minimum 76875.952308\n", - "time_this_iter_s 4059.540029\n", - "dtype: float64, 'median': minimum 74900.920000\n", - "time_this_iter_s 3473.943819\n", - "dtype: float64, 'mode': minimum 64721.630000\n", - "time_this_iter_s 2897.851462\n", - "Name: 0, dtype: float64, 'range': minimum 63896.840000\n", - "time_this_iter_s 6451.522084\n", - "dtype: float64, 'variance': minimum 1.065132e+08\n", - "time_this_iter_s 1.757353e+06\n", - "dtype: float64, 'std': minimum 10320.523719\n", - "time_this_iter_s 1325.652025\n", - "dtype: float64}\n", - "Stats for ray27-aes-sky130hd.csv\n", - "{'count': minimum 100\n", - "time_this_iter_s 100\n", - "checkpoint_dir_name 0\n", - "dtype: int64, 'mean': minimum 557.970037\n", - "time_this_iter_s 2147.289633\n", - "checkpoint_dir_name NaN\n", - "dtype: float64, 'median': minimum 555.21500\n", - "time_this_iter_s 2131.34783\n", - "checkpoint_dir_name NaN\n", - "dtype: float64, 'mode': minimum 499.071230\n", - "time_this_iter_s 1246.325862\n", - "checkpoint_dir_name NaN\n", - "Name: 0, dtype: float64, 'range': minimum 141.608770\n", - "time_this_iter_s 2574.265153\n", - "checkpoint_dir_name NaN\n", - "dtype: float64, 'variance': minimum 1129.915769\n", - "time_this_iter_s 182371.300340\n", - "checkpoint_dir_name NaN\n", - "dtype: float64, 'std': minimum 33.614220\n", - "time_this_iter_s 427.049529\n", - "checkpoint_dir_name NaN\n", - "dtype: float64}\n", - "Stats for ray28-aes-sky130hd.csv\n", - "{'count': minimum 100\n", - "time_this_iter_s 100\n", - "dtype: int64, 'mean': minimum 558.310372\n", - "time_this_iter_s 2183.826477\n", - "dtype: float64, 'median': minimum 553.049800\n", - "time_this_iter_s 2108.631588\n", - "dtype: float64, 'mode': minimum 499.504980\n", - "time_this_iter_s 1456.120545\n", - "Name: 0, dtype: float64, 'range': minimum 146.641720\n", - "time_this_iter_s 2877.529474\n", - "dtype: float64, 'variance': minimum 1081.949801\n", - "time_this_iter_s 245557.783237\n", - "dtype: float64, 'std': minimum 32.893005\n", - "time_this_iter_s 495.537873\n", - "dtype: float64}\n", - "Stats for ray29-aes-sky130hd.csv\n", - "{'count': minimum 100\n", - "time_this_iter_s 100\n", - "dtype: int64, 'mean': minimum 562.558027\n", - "time_this_iter_s 2028.885016\n", - "dtype: float64, 'median': minimum 562.097825\n", - "time_this_iter_s 1932.916166\n", - "dtype: float64, 'mode': minimum 501.826247\n", - "time_this_iter_s 1298.292833\n", - "Name: 0, dtype: float64, 'range': minimum 123.752953\n", - "time_this_iter_s 2493.840086\n", - "dtype: float64, 'variance': minimum 974.347415\n", - "time_this_iter_s 241786.605521\n", - "dtype: float64, 'std': minimum 31.214539\n", - "time_this_iter_s 491.718014\n", - "dtype: float64}\n", - "Stats for ray27-aes-ihp-sg13g2.csv\n", - "{'count': minimum 83\n", - "time_this_iter_s 83\n", - "checkpoint_dir_name 0\n", - "dtype: int64, 'mean': minimum 557.355415\n", - "time_this_iter_s 5618.940456\n", - "checkpoint_dir_name NaN\n", - "dtype: float64, 'median': minimum 548.326300\n", - "time_this_iter_s 5384.021719\n", - "checkpoint_dir_name NaN\n", - "dtype: float64, 'mode': minimum 454.042100\n", - "time_this_iter_s 2064.153147\n", - "checkpoint_dir_name NaN\n", - "Name: 0, dtype: float64, 'range': minimum 328.679900\n", - "time_this_iter_s 22308.259252\n", - "checkpoint_dir_name NaN\n", - "dtype: float64, 'variance': minimum 2.934094e+03\n", - "time_this_iter_s 9.719623e+06\n", - "checkpoint_dir_name NaN\n", - "dtype: float64, 'std': minimum 54.167277\n", - "time_this_iter_s 3117.631060\n", - "checkpoint_dir_name NaN\n", - "dtype: float64}\n", - "Stats for ray28-aes-ihp-sg13g2.csv\n", - "{'count': minimum 92\n", - "time_this_iter_s 92\n", - "dtype: int64, 'mean': minimum 552.238758\n", - "time_this_iter_s 5202.011931\n", - "dtype: float64, 'median': minimum 542.829000\n", - "time_this_iter_s 4988.825702\n", - "dtype: float64, 'mode': minimum 471.245300\n", - "time_this_iter_s 1991.868049\n", - "Name: 0, dtype: float64, 'range': minimum 282.830700\n", - "time_this_iter_s 8102.373443\n", - "dtype: float64, 'variance': minimum 1.977504e+03\n", - "time_this_iter_s 4.185023e+06\n", - "dtype: float64, 'std': minimum 44.469136\n", - "time_this_iter_s 2045.732876\n", - "dtype: float64}\n", - "Stats for ray29-aes-ihp-sg13g2.csv\n", - "{'count': minimum 93\n", - "time_this_iter_s 93\n", - "dtype: int64, 'mean': minimum 568.207906\n", - "time_this_iter_s 4340.748850\n", - "dtype: float64, 'median': minimum 556.897100\n", - "time_this_iter_s 3543.077481\n", - "dtype: float64, 'mode': minimum 482.363600\n", - "time_this_iter_s 2144.719427\n", - "Name: 0, dtype: float64, 'range': minimum 385.75140\n", - "time_this_iter_s 34982.08581\n", - "dtype: float64, 'variance': minimum 3.241066e+03\n", - "time_this_iter_s 1.505806e+07\n", - "dtype: float64, 'std': minimum 56.930357\n", - "time_this_iter_s 3880.471576\n", - "dtype: float64}\n", - "Stats for ray27-ibex-asap7.csv\n", - "{'count': minimum 98\n", - "time_this_iter_s 98\n", - "checkpoint_dir_name 0\n", - "dtype: int64, 'mean': minimum 210868.382347\n", - "time_this_iter_s 3634.591410\n", - "checkpoint_dir_name NaN\n", - "dtype: float64, 'median': minimum 209223.510000\n", - "time_this_iter_s 3599.164971\n", - "checkpoint_dir_name NaN\n", - "dtype: float64, 'mode': minimum 194762.820000\n", - "time_this_iter_s 3178.493515\n", - "checkpoint_dir_name NaN\n", - "Name: 0, dtype: float64, 'range': minimum 43063.680000\n", - "time_this_iter_s 1434.401824\n", - "checkpoint_dir_name NaN\n", - "dtype: float64, 'variance': minimum 6.469542e+07\n", - "time_this_iter_s 7.958102e+04\n", - "checkpoint_dir_name NaN\n", - "dtype: float64, 'std': minimum 8043.346545\n", - "time_this_iter_s 282.101085\n", - "checkpoint_dir_name NaN\n", - "dtype: float64}\n", - "Stats for ray28-ibex-asap7.csv\n", - "{'count': minimum 95\n", - "time_this_iter_s 95\n", - "dtype: int64, 'mean': minimum 208985.620632\n", - "time_this_iter_s 3303.857652\n", - "dtype: float64, 'median': minimum 207575.73000\n", - "time_this_iter_s 3217.98494\n", - "dtype: float64, 'mode': minimum 198389.830000\n", - "time_this_iter_s 2996.846359\n", - "Name: 0, dtype: float64, 'range': minimum 31646.61000\n", - "time_this_iter_s 1136.11621\n", - "dtype: float64, 'variance': minimum 4.178046e+07\n", - "time_this_iter_s 6.792734e+04\n", - "dtype: float64, 'std': minimum 6463.780291\n", - "time_this_iter_s 260.628742\n", - "dtype: float64}\n", - "Stats for ray29-ibex-asap7.csv\n", - "{'count': minimum 91\n", - "time_this_iter_s 91\n", - "dtype: int64, 'mean': minimum 210460.236154\n", - "time_this_iter_s 3576.207765\n", - "dtype: float64, 'median': minimum 208961.940000\n", - "time_this_iter_s 3513.316176\n", - "dtype: float64, 'mode': minimum 195896.200000\n", - "time_this_iter_s 3132.065917\n", - "Name: 0, dtype: float64, 'range': minimum 50443.0200\n", - "time_this_iter_s 1582.5553\n", - "dtype: float64, 'variance': minimum 6.515244e+07\n", - "time_this_iter_s 8.935494e+04\n", - "dtype: float64, 'std': minimum 8071.706050\n", - "time_this_iter_s 298.922974\n", - "dtype: float64}\n", - "Stats for ray27-ibex-sky130hd.csv\n", - "{'count': minimum 99\n", - "time_this_iter_s 99\n", - "checkpoint_dir_name 0\n", - "dtype: int64, 'mean': minimum 1451.529285\n", - "time_this_iter_s 2423.086975\n", - "checkpoint_dir_name NaN\n", - "dtype: float64, 'median': minimum 1442.079140\n", - "time_this_iter_s 1942.265699\n", - "checkpoint_dir_name NaN\n", - "dtype: float64, 'mode': minimum 1372.651400\n", - "time_this_iter_s 1400.828328\n", - "checkpoint_dir_name NaN\n", - "Name: 0, dtype: float64, 'range': minimum 218.764050\n", - "time_this_iter_s 6106.393857\n", - "checkpoint_dir_name NaN\n", - "dtype: float64, 'variance': minimum 2.821493e+03\n", - "time_this_iter_s 1.495589e+06\n", - "checkpoint_dir_name NaN\n", - "dtype: float64, 'std': minimum 53.117723\n", - "time_this_iter_s 1222.942573\n", - "checkpoint_dir_name NaN\n", - "dtype: float64}\n", - "Stats for ray28-ibex-sky130hd.csv\n", - "{'count': minimum 100\n", - "time_this_iter_s 100\n", - "dtype: int64, 'mean': minimum 1459.122534\n", - "time_this_iter_s 2409.811684\n", - "dtype: float64, 'median': minimum 1448.978300\n", - "time_this_iter_s 2102.146262\n", - "dtype: float64, 'mode': minimum 1378.325000\n", - "time_this_iter_s 1248.697668\n", - "Name: 0, dtype: float64, 'range': minimum 214.207150\n", - "time_this_iter_s 5390.993848\n", - "dtype: float64, 'variance': minimum 2.364698e+03\n", - "time_this_iter_s 1.018585e+06\n", - "dtype: float64, 'std': minimum 48.628159\n", - "time_this_iter_s 1009.249793\n", - "dtype: float64}\n", - "Stats for ray29-ibex-sky130hd.csv\n", - "{'count': minimum 99\n", - "time_this_iter_s 99\n", - "dtype: int64, 'mean': minimum 1460.492545\n", - "time_this_iter_s 2505.095220\n", - "dtype: float64, 'median': minimum 1453.511900\n", - "time_this_iter_s 2180.490231\n", - "dtype: float64, 'mode': minimum 1374.475800\n", - "time_this_iter_s 1535.102256\n", - "Name: 0, dtype: float64, 'range': minimum 216.386200\n", - "time_this_iter_s 12097.299293\n", - "dtype: float64, 'variance': minimum 2.852904e+03\n", - "time_this_iter_s 1.797824e+06\n", - "dtype: float64, 'std': minimum 53.412581\n", - "time_this_iter_s 1340.829549\n", - "dtype: float64}\n", - "Stats for ray27-ibex-ihp-sg13g2.csv\n", - "{'count': minimum 89\n", - "time_this_iter_s 89\n", - "checkpoint_dir_name 0\n", - "dtype: int64, 'mean': minimum 1483.911211\n", - "time_this_iter_s 5042.592064\n", - "checkpoint_dir_name NaN\n", - "dtype: float64, 'median': minimum 1464.56600\n", - "time_this_iter_s 4660.75879\n", - "checkpoint_dir_name NaN\n", - "dtype: float64, 'mode': minimum 1303.13600\n", - "time_this_iter_s 2226.44617\n", - "checkpoint_dir_name NaN\n", - "Name: 0, dtype: float64, 'range': minimum 580.760000\n", - "time_this_iter_s 23167.165397\n", - "checkpoint_dir_name NaN\n", - "dtype: float64, 'variance': minimum 1.141994e+04\n", - "time_this_iter_s 8.240846e+06\n", - "checkpoint_dir_name NaN\n", - "dtype: float64, 'std': minimum 106.864096\n", - "time_this_iter_s 2870.687342\n", - "checkpoint_dir_name NaN\n", - "dtype: float64}\n", - "Stats for ray28-ibex-ihp-sg13g2.csv\n", - "{'count': minimum 88\n", - "time_this_iter_s 88\n", - "dtype: int64, 'mean': minimum 1497.012630\n", - "time_this_iter_s 4358.085955\n", - "dtype: float64, 'median': minimum 1474.943300\n", - "time_this_iter_s 4007.106702\n", - "dtype: float64, 'mode': minimum 1283.3340\n", - "time_this_iter_s 2149.5708\n", - "Name: 0, dtype: float64, 'range': minimum 655.420000\n", - "time_this_iter_s 9731.753961\n", - "dtype: float64, 'variance': minimum 1.156444e+04\n", - "time_this_iter_s 2.860430e+06\n", - "dtype: float64, 'std': minimum 107.538076\n", - "time_this_iter_s 1691.280454\n", - "dtype: float64}\n", - "Stats for ray29-ibex-ihp-sg13g2.csv\n", - "{'count': minimum 94\n", - "time_this_iter_s 94\n", - "dtype: int64, 'mean': minimum 1468.906375\n", - "time_this_iter_s 5209.307440\n", - "dtype: float64, 'median': minimum 1440.995000\n", - "time_this_iter_s 5010.720875\n", - "dtype: float64, 'mode': minimum 1314.551000\n", - "time_this_iter_s 2576.372125\n", - "Name: 0, dtype: float64, 'range': minimum 574.468000\n", - "time_this_iter_s 8802.107405\n", - "dtype: float64, 'variance': minimum 1.038998e+04\n", - "time_this_iter_s 2.284923e+06\n", - "dtype: float64, 'std': minimum 101.931236\n", - "time_this_iter_s 1511.596254\n", - "dtype: float64}\n" 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", 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", 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", 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", 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MOaP1AAA8EwEKANColi1bJi8vL3l5een9998/qd/pdCoiIkJeXl4aPHiwCRUCAHBqLcwuAADgmfz8/LRixQpdccUVbu0bNmzQd999J19fX7f2qqoqtWjRsP9tbd++Xd7e/GYIADh9/N8EAGCKa6+9Vq+99pqOHz/u1r5ixQrFx8crNDTUrd3Pz6/BAcrX11ctW7ZscK0AANQiQAEATHHTTTfpwIEDysnJcbXV1NRo5cqVGjly5Enjf34P1KxZs+Tl5aUdO3ZozJgxCgoKUmBgoG677TYdOXLEbduf3wNVexnh+++/rz/84Q/q2LGjgoKCdOedd6qmpkbl5eW69dZb1bZtW7Vt21b333+/nE6na/v169fLy8tL69evdztOSUmJvLy8tGzZMlfbmDFj1Lp1a+3atUuDBw9W69atdd5552nx4sWSpC+++EIDBgxQq1at1KVLF61YsaIBnyYAoLEQoAAApoiMjFRiYqJeeuklV9s777yjiooKjRgxwvB+hg8frsrKSmVmZmr48OFatmyZZs+ebWjbSZMmqbi4WLNnz9Z1112nv/3tb3rooYc0ZMgQ2e12zZkzR1dccYXmzZunF154od7nWMtut+uaa65RRESE5s6dq8jISE2cOFHLli3T1VdfrUsuuUSPP/642rRpo1tvvVU7d+5s8LEAAGcX90ABAEwzcuRIZWRkqKqqSv7+/nrxxRf129/+VuHh4Yb3cfHFF+vZZ591vT9w4ICeffZZPf7447+6bUhIiN5++215eXnp7rvv1o4dOzRv3jzdeeedWrJkiSTpjjvuUGRkpP75z3/q1ltvrf9JSjp69KhGjRqljIwMST+dd3h4uG6//Xa99NJL+v3vfy9J+t3vfqeYmBg9//zzDV5xEABwdjEDBQAwzfDhw1VVVaXs7GxVVlYqOzu7zsv3fsldd93l9j4pKUkHDhyQzWb71W3Hjh0rLy8v1/uEhAQ5nU6NHTvW1WaxWHTJJZfom2++qVddPzdu3DjXvwcFBal79+5q1aqVhg8f7mrv3r27goKCTvtYAICzhxkoAIBpOnbsqOTkZK1YsUJHjhyR3W5XWlpavfbRuXNnt/dt27aVJP3444+yWq312jYwMFCSFBERcVL7jz/+WK+6TuTn56eOHTuetM9OnTq5BbgzcSwAwNlFgAIAmGrkyJEaP368ysrKdM011ygoKKhe21ssljrbT1z0ob7b1tV+4v5+Hnpq2e320z7Oz48FAGhauIQPAGCqG264Qd7e3vrggw/qffmeWWpnucrLy93av/32WxOqAQA0JmagAACmat26tZYsWaKSkhINGTLE7HIM6dKliywWizZu3KjU1FRX+zPPPGNeUQCARkGAAgCYbvTo0WaXUC+BgYG68cYb9fTTT8vLy0tdu3ZVdna29u3bZ3ZpAICzjAAFAEADPP300zp27JiWLl0qX19fDR8+XPPmzVPPnj3NLg0AcBZ5OblTFQAAAAAMYREJAAAAADCIAAUAAAAABhGgAAAAAMAgAhQAAAAAGESAAgAAAACDPHoZc4fDoT179qhNmzby8vIyuxwAAAAAJnE6naqsrFR4eLi8vU89z+TRAWrPnj2KiIgwuwwAAAAATcTu3bvVqVOnU/Z7dIBq06aNpJ8+JKvVanI1AAAAAMxis9kUERHhygin4tEBqvayPavVSoACAAAA8Ku39rCIBAAAAAAYRIACAAAAAIMIUAAAAABgEAEKAAAAAAwiQAEAAACAQQQoAAAAADCIAAUAAAAABhGgAAAAAMAgj36QLgAAADyb3W5XXl6eSktLFRYWpqSkJFksFrPLQhPGDBQAAAA8UlZWlqKjo9W/f3+NHDlS/fv3V3R0tLKysswuDU0YAQoAAAAeJysrS2lpaYqLi1N+fr4qKyuVn5+vuLg4paWlEaJwSl5Op9NpdhFmsdlsCgwMVEVFhaxWq9nlAAAAoBHY7XZFR0crLi5Oq1atkrf3/+YUHA6HUlNTVVhYqOLiYi7n8yBGswEzUAAAAPAoeXl5Kikp0YMPPugWniTJ29tbGRkZ2rlzp/Ly8kyqEE0ZAQoAAAAepbS0VJLUs2fPOvtr22vHASciQAEAAMCjhIWFSZIKCwvr7K9trx0HnIgABQAAAI+SlJSkyMhIzZkzRw6Hw63P4XAoMzNTUVFRSkpKMqlCNGUEKAAAAHgUi8WiBQsWKDs7W6mpqW6r8KWmpio7O1vz589nAQnUiQfpAgAAwOMMHTpUK1eu1LRp09S3b19Xe1RUlFauXKmhQ4eaWB2aMpYxZxlzAAAAj2W325WXl6fS0lKFhYUpKSmJmScPZTQbMAMFAAAAj2WxWNSvXz+zy8A5hHugAAAAAMAgAhQAAAAAGESAAgAAAACDCFAAAAAAYBABCgAAAAAMIkABAAAAgEEEKAAAAAAwiAAFAAAAAAYRoAAAAADAIAIUAAAAABhEgAIAAAAAgwhQAAAAAGAQAQoAAAAADCJAAQAAAIBBBCgAAAAAMIgABQAAAAAGEaAAAAAAwCACFAAAAAAYRIACAAAAAIMIUAAAAABgEAEKAAAAAAwiQAEAAACAQQQoAAAAADCIAAUAAAAABhGgAAAAAMAgAhQAAAAAGESAAgAAAACDCFAAAAAAYBABCgAAAAAMIkABAAAAgEEEKAAAAAAwiAAFAAAAAAYRoAAAAADAIAIUAAAAABhEgAIAAAAAgwhQAAAAAGAQAQoAAAAADCJAAQAAAIBBBCgAAAAAMIgABQAAAAAGEaAAAAAAwCACFAAAAAAYZEqAstvteuihhxQVFSV/f3917dpVjz76qJxOp2uM0+nUzJkzFRYWJn9/fyUnJ6u4uNhtPwcPHtTNN98sq9WqoKAgjR07VocOHWrs0wEAAADgIUwJUI8//riWLFmiRYsWadu2bXr88cc1d+5cPf30064xc+fO1VNPPaWlS5dq8+bNatWqlVJSUnT06FHXmJtvvllbt25VTk6OsrOztXHjRt1xxx1mnBIAAAAAD+DlPHHap5EMHjxYISEhevbZZ11tw4YNk7+/v5YvXy6n06nw8HBNmzZN9957rySpoqJCISEhWrZsmUaMGKFt27apR48e+uijj3TJJZdIktasWaNrr71W3333ncLDw3+1DpvNpsDAQFVUVMhqtZ6dkwUAAADQ5BnNBqbMQPXt21e5ubn66quvJEmfffaZ3n//fV1zzTWSpJ07d6qsrEzJycmubQIDA5WQkKD8/HxJUn5+voKCglzhSZKSk5Pl7e2tzZs313nc6upq2Ww2txcAAAAAGNXCjIM+8MADstlsiomJkcVikd1u15/+9CfdfPPNkqSysjJJUkhIiNt2ISEhrr6ysjIFBwe79bdo0ULt2rVzjfm5zMxMzZ49+0yfDgAAAAAPYcoM1KuvvqoXX3xRK1as0CeffKLnn39e8+fP1/PPP39Wj5uRkaGKigrXa/fu3Wf1eAAAAACaF1NmoO677z498MADGjFihCQpLi5O3377rTIzMzV69GiFhoZKkvbu3auwsDDXdnv37lWvXr0kSaGhodq3b5/bfo8fP66DBw+6tv85X19f+fr6noUzAgAAAOAJTJmBOnLkiLy93Q9tsVjkcDgkSVFRUQoNDVVubq6r32azafPmzUpMTJQkJSYmqry8XAUFBa4xa9eulcPhUEJCQiOcBQAAAABPY8oM1JAhQ/SnP/1JnTt31m9+8xt9+umn+stf/qLbb79dkuTl5aXJkyfrscceU7du3RQVFaWHHnpI4eHhSk1NlSTFxsbq6quv1vjx47V06VIdO3ZMEydO1IgRIwytwAcAAAAA9WVKgHr66af10EMP6e6779a+ffsUHh6uO++8UzNnznSNuf/++3X48GHdcccdKi8v1xVXXKE1a9bIz8/PNebFF1/UxIkTddVVV8nb21vDhg3TU089ZcYpAQAAAPAApjwHqqngOVAAAAAApCb+HCgAAAAAOBeZcgkf0BTY7Xbl5eWptLRUYWFhSkpKksViMbssAAAANGHMQMEjZWVlKTo6Wv3799fIkSPVv39/RUdHKysry+zSAAAA0IQRoOBxsrKylJaWpri4OOXn56uyslL5+fmKi4tTWloaIQoAAACnxCISLCLhUex2u6KjoxUXF6dVq1a5PY/M4XAoNTVVhYWFKi4u5nI+AAAAD8IiEkAd8vLyVFJSogcffPCkhzl7e3srIyNDO3fuVF5enkkVAgAAoCkjQMGjlJaWSpJ69uxZZ39te+04AAAA4EQEKHiUsLAwSVJhYWGd/bXtteMAAACAExGg4FGSkpIUGRmpOXPmyOFwuPU5HA5lZmYqKipKSUlJJlUIAACApowABY9isVi0YMECZWdnKzU11W0VvtTUVGVnZ2v+/PksIAEAAIA68SBdeJyhQ4dq5cqVmjZtmvr27etqj4qK0sqVKzV06FATqwMAAEBTxjLmLGPusex2u/Ly8lRaWqqwsDAlJSUx8wQAAOChjGYDZqDgsSwWi/r162d2GQAAADiHcA8UAAAAABhEgAIAAAAAgwhQAAAAAGAQAQoAAAAADCJAAQAAAIBBBCgAAAAAMIgABQAAAAAGEaAAAAAAwCACFAAAAAAYRIACAAAAAINamF0AAABmsdvtysvLU2lpqcLCwpSUlCSLxWJ2WQCAJowZKACAR8rKylJ0dLT69++vkSNHqn///oqOjlZWVpbZpQEAmjACFADA42RlZSktLU1xcXHKz89XZWWl8vPzFRcXp7S0NEIUAOCUvJxOp9PsIsxis9kUGBioiooKWa1Ws8sBADQCu92u6OhoxcXFadWqVfL2/t9viQ6HQ6mpqSosLFRxcTGX8wGABzGaDZiBAgB4lLy8PJWUlOjBBx90C0+S5O3trYyMDO3cuVN5eXkmVQgAaMoIUAAAj1JaWipJ6tmzZ539te214wAAOBEBCgDgUcLCwiRJhYWFdfbXtteOAwDgRAQoAIBHSUpKUmRkpObMmSOHw+HW53A4lJmZqaioKCUlJZlUIQCgKSNAAQA8isVi0YIFC5Sdna3U1FS3VfhSU1OVnZ2t+fPns4AE4CHsdrvWr1+vl156SevXr5fdbje7JDRxPEgXAOBxhg4dqpUrV2ratGnq27evqz0qKkorV67U0KFDTawOQGPJysrStGnTVFJS4mqLjIzUggUL+B7AKTEDBQDwSEOHDtWOHTu0bt06rVixQuvWrVNxcTF/NAEegufBoaF4DhTPgQIAAPAoPA8OdeE5UAAAAEAdeB4cTgcBCgAAAB6F58HhdBCgAAAA4FF4HhxOB/dAcQ8UAACARznxHqjXX39d//3vf1VaWqqwsDBdfvnlGjZsGPdAeSCj2YBlzAEAAOBRap8HN2zYMAUGBqqqqsrV5+/vr6qqKr3++uuEJ9SJS/gAAADgkby8vOpsq6sdqMUlfFzCBwAA4FG4hA914RI+AAAAoA61y5i/9NJLatmypfr16+fWn5GRob59+yovL++kPoBL+AAAAOBRWMYcp4MABQAAAI/CMuY4HQQoAAAAeJSkpCRFRkZqzpw5cjgcbn0Oh0OZmZmKiopSUlKSSRWiKSNAAQAAwKPULmOenZ2t1NRU5efnq7KyUvn5+UpNTVV2drbmz5/PAhKoE4tIAAAAwOMMHTpUK1eu1LRp09S3b19Xe1RUlFauXKmhQ4eaWB2aMpYxZxlzAAAAj2W325WXl+daxjwpKYmZJw/FMuYAAPwK/nACYLFYWKoc9cI9UAAAj5SVlaXo6Gj1799fI0eOVP/+/RUdHa2srCyzSwMANGEEKACAx8nKylJaWpri4uLcbh6Pi4tTWloaIQrwIHa7XevXr9dLL72k9evXy263m10SmjjugeIeKADwKHa7XdHR0YqLi9OqVavk7f2/3xIdDodSU1NVWFio4uJiLucDmrmsrCxNmzZNJSUlrrbIyEgtWLCARSQ8kNFswAwUAMCj5OXlqaSkRA8++KBbeJIkb29vZWRkaOfOncrLyzOpQgCNgZloNBQBCgDgUUpLSyVJPXv2rLO/tr12HIDmx263a9q0aRo8eLBWrVqlPn36qHXr1urTp49WrVqlwYMH69577+VyPtSJAAUA8ChhYWGSpMLCwjr7a9trxwFofpiJxukgQAEAPEpSUpIiIyM1Z84cORwOtz6Hw6HMzExFRUUpKSnJpAoBnG3MRON0EKAAAB7FYrFowYIFys7OVmpqqtu9D6mpqcrOztb8+fNZQAJoxpiJxulgFT5W4QMAj1TX6ltRUVGaP38+q28BzRyrcaIuRrMBAYoABQAey263Ky8vT6WlpQoLC1NSUhJ/LAEeonYVvsGDBysjI0M9e/ZUYWGhMjMzlZ2drZUrV/JjiochQBlAgAIAAPBczETjRAQoAwhQAAAAnq2mpkbPPPOMvv76a3Xt2lV33323fHx8zC4LJjCaDVo0Yk0AAABAk1HXDNSTTz6pBQsWMAOFU2IVPgAAAHic2nug4uLi3FbjjIuLU1pamrKysswuEU0Ul/BxCR8AAIBHYRU+1MVoNmAGCgAAAB4lLy9PJSUlevDBB93CkyR5e3srIyNDO3fuVF5enkkVoikzJUBFRkbKy8vrpFd6erok6ejRo0pPT1f79u3VunVrDRs2THv37nXbx65duzRo0CAFBAQoODhY9913n44fP27G6QAAAOAcUlpaKknq2bNnnf217bXjgBOZEqA++ugjlZaWul45OTmSpBtvvFGSNGXKFP373//Wa6+9pg0bNmjPnj1uN/LZ7XYNGjRINTU12rRpk55//nktW7ZMM2fONON0AAAAcA4JCwuTJBUWFtbZX9teOw44UZO4B2ry5MnKzs5WcXGxbDabOnbsqBUrVigtLU2SVFRUpNjYWOXn56tPnz565513NHjwYO3Zs0chISGSpKVLl2r69Onav3//KZeerK6uVnV1teu9zWZTREQE90ABAAB4EO6BQl3OmXugampqtHz5ct1+++3y8vJSQUGBjh07puTkZNeYmJgYde7cWfn5+ZLkWiGlNjxJUkpKimw2m7Zu3XrKY2VmZiowMND1ioiIOHsnBgAAgCbJYrFowYIFys7OVmpqqtsqfKmpqcrOztb8+fMJT6iT6QFq1apVKi8v15gxYyRJZWVl8vHxUVBQkNu4kJAQlZWVucacGJ5q+2v7TiUjI0MVFRWu1+7du8/ciQAAAOCcMXToUK1cuVJffPGF+vbtK6vVqr59+6qwsFArV67kOVA4JdMfpPvss8/qmmuuUXh4+Fk/lq+vr3x9fc/6cQAAAND0DR06VNdff73y8vJUWlqqsLAwJSUlMfOEX2RqgPr222/13nvvuT2oLDQ0VDU1NSovL3ebhdq7d69CQ0NdYz788EO3fdWu0lc7BgAAAPg1FotF/fr1M7sMnENMvYTvueeeU3BwsAYNGuRqi4+PV8uWLZWbm+tq2759u3bt2qXExERJUmJior744gvt27fPNSYnJ0dWq1U9evRovBMAAAAA4FFMm4FyOBx67rnnNHr0aLVo8b8yAgMDNXbsWE2dOlXt2rWT1WrVpEmTlJiYqD59+kiSBg4cqB49euiWW27R3LlzVVZWphkzZig9PZ1L9AAAAACcNaYFqPfee0+7du3S7bffflLfE088IW9vbw0bNkzV1dVKSUnRM8884+q3WCzKzs7WhAkTlJiYqFatWmn06NF65JFHGvMUAAAAAHiYJvEcKLMYXesdAAAAQPN2zjwHCgAAAADOFQQoAAAAADCIAAUAAAAABhGgAAAAAMAgAhQAAAAAGGTaMubwHEeOHFFRUZHZZdSpqqpKJSUlioyMlL+/v9nl1CkmJkYBAQFmlwEAAAARoNAIioqKFB8fb3YZ56yCggL17t3b7DIAAAAgAhQaQUxMjAoKCswuo07btm3TqFGjtHz5csXGxppdTp1iYmLMLgEAAAD/jwCFsy4gIKDJz6DExsY2+RoBAABgPhaRAAAAAACDCFAAAAAAYBABCgAAAAAMIkABAAAAgEEEKAAAAAAwiAAFAAAAAAYRoAAAAADAIAIUAAAAABhEgAIAAAAAgwhQAAAAAGAQAQoAAAAADCJAAQAAAIBBLcwuAAAAADCL3W5XXl6eSktLFRYWpqSkJFksFrPLQhPGDBQAAAA8UlZWlqKjo9W/f3+NHDlS/fv3V3R0tLKysswuDU0YAQoAAAAeJysrS2lpaYqLi1N+fr4qKyuVn5+vuLg4paWlEaJwSl5Op9NpdhFmsdlsCgwMVEVFhaxWq9nlwASffPKJ4uPjVVBQoN69e5tdDgAAaAR2u13R0dGKi4vTqlWr5O39vzkFh8Oh1NRUFRYWqri4mMv5PIjRbMAMFAAAADxKXl6eSkpK9OCDD7qFJ0ny9vZWRkaGdu7cqby8PJMqRFNGgAIAAIBHKS0tlST17Nmzzv7a9tpxwIkIUAAAAPAoYWFhkqTCwsI6+2vba8cBJyJAAQAAwKMkJSUpMjJSc+bMkcPhcOtzOBzKzMxUVFSUkpKSTKoQTRkBCgAAAB7FYrFowYIFys7OVmpqqtsqfKmpqcrOztb8+fNZQAJ14kG6AAAA8DhDhw7VypUrNW3aNPXt29fVHhUVpZUrV2ro0KEmVoemjAAFAAAAjzR06FBdf/31ysvLU2lpqcLCwpSUlMTME34RAQoAAAAey2KxqF+/fmaXgXMI90ABAAAAgEHMQAEAAKBRHDlyREVFRWaXcZKqqiqVlJQoMjJS/v7+ZpdTp5iYGAUEBJhdBkSAAgAAQCMpKipSfHy82WWckwoKCtS7d2+zy4AIUAAAAGgkMTExKigoMLuMk2zbtk2jRo3S8uXLFRsba3Y5dYqJiTG7BPw/AhQAAAAaRUBAQJOeRYmNjW3S9aFpYBEJAAAAADCIAAUAAAAABhGgAAAAAMAgAhQAAAAAGESAAgAAAACDCFAAAAAAYBABCgAAAAAMIkABAAAAgEEEKAAAAAAwiAAFAAAAAAYRoAAAAADAIAIUAAAAABjUwuwCAADN35EjR1RUVGR2GXWqqqpSSUmJIiMj5e/vb3Y5dYqJiVFAQIDZZQAARIACADSCoqIixcfHm13GOaugoEC9e/c2uwwAgAhQAIBGEBMTo4KCArPLqNO2bds0atQoLV++XLGxsWaXU6eYmBizSwAA/D8CFADgrAsICGjyMyixsbFNvkYAgPlYRAIAAAAADCJAAQAAAIBBBCgAAAAAMIgABQAAAAAGEaAAAAAAwCACFAAAAAAYRIACAAAAAIMIUAAAAABgEAEKAAAAAAwiQAEAAACAQQQoAAAAADDItAD1/fffa9SoUWrfvr38/f0VFxenjz/+2NXvdDo1c+ZMhYWFyd/fX8nJySouLnbbx8GDB3XzzTfLarUqKChIY8eO1aFDhxr7VAAAAAB4CFMC1I8//qjLL79cLVu21DvvvKMvv/xSCxYsUNu2bV1j5s6dq6eeekpLly7V5s2b1apVK6WkpOjo0aOuMTfffLO2bt2qnJwcZWdna+PGjbrjjjvMOCUAAAAAHqCFGQd9/PHHFRERoeeee87VFhUV5fp3p9OphQsXasaMGbr++uslSf/6178UEhKiVatWacSIEdq2bZvWrFmjjz76SJdccokk6emnn9a1116r+fPnKzw8vHFPCgAAAECzZ8oM1FtvvaVLLrlEN954o4KDg3XxxRfr73//u6t/586dKisrU3JysqstMDBQCQkJys/PlyTl5+crKCjIFZ4kKTk5Wd7e3tq8eXOdx62urpbNZnN7AQAAAIBRpgSob775RkuWLFG3bt307rvvasKECfrDH/6g559/XpJUVlYmSQoJCXHbLiQkxNVXVlam4OBgt/4WLVqoXbt2rjE/l5mZqcDAQNcrIiLiTJ8aAAAAgGbMlADlcDjUu3dvzZkzRxdffLHuuOMOjR8/XkuXLj2rx83IyFBFRYXrtXv37rN6PAAAAADNiykBKiwsTD169HBri42N1a5duyRJoaGhkqS9e/e6jdm7d6+rLzQ0VPv27XPrP378uA4ePOga83O+vr6yWq1uLwAAAAAwypQAdfnll2v79u1ubV999ZW6dOki6acFJUJDQ5Wbm+vqt9ls2rx5sxITEyVJiYmJKi8vV0FBgWvM2rVr5XA4lJCQ0AhnAQAAAMDTmLIK35QpU9S3b1/NmTNHw4cP14cffqi//e1v+tvf/iZJ8vLy0uTJk/XYY4+pW7duioqK0kMPPaTw8HClpqZK+mnG6uqrr3Zd+nfs2DFNnDhRI0aMYAU+AAAAAGeFKQHq0ksv1RtvvKGMjAw98sgjioqK0sKFC3XzzTe7xtx///06fPiw7rjjDpWXl+uKK67QmjVr5Ofn5xrz4osvauLEibrqqqvk7e2tYcOG6amnnjLjlAAAAAB4AFMClCQNHjxYgwcPPmW/l5eXHnnkET3yyCOnHNOuXTutWLHibJQHAAAAACcx5R4oAAAAADgXEaAAAAAAwCDTLuHDmVdcXKzKykqzyzinbNu2ze2fMKZNmzbq1q2b2WUAAAA0OgJUM1FcXKwLLrjA7DLOWaNGjTK7hHPOV199RYgCAAAehwDVTNTOPC1fvlyxsbEmV3PuqKqqUklJiSIjI+Xv7292OeeEbdu2adSoUcx2AgAAj0SAamZiY2PVu3dvs8s4p1x++eVmlwAAwBnFZf31wyX9DeeJl/UToAAAAJoRLutvOC7pbxhPu6yfAAUAANCMcFl//XFJf8N46mX9BCgAAIBmiMv664dL+mEUz4ECAAAAAIMIUAAAAABgEAEKAAAAAAziHigAaGZYvrh+WL644Txx+WIAIEABQDPC8sUNx/LFDeNpyxcDAAEKAJoRli+uP5YvbhhPXb4YAAhQANAMsXxx/bB8MQDAKBaRAAAAAACDCFAAAAAAYBABCgAAAAAMIkABAAAAgEEEKAAAAAAwiAAFAAAAAAYRoAAAAADAIAIUAAAAABhEgAIAAAAAg1qYXQAAAADOrNDWXvIv/0raw2/lOHv8y79SaGsvs8todAQoAACAZubOeB/FbrxT2mh2JWjOYvXTf2uehgAFAADQzPy1oEa/n7lMsTExZpeCZmxbUZH+umCkrjO7kEZGgAIAAGhmyg45VRV0gRTey+xS0IxVlTlUdshpdhmNjgtjAQAAAMAgAhQAAAAAGESAAgAAAACDuAeqGWHJUjQGT12yFAAAQCJANSssWYrG4KlLlgIAAEgEqGaFJUvRGDx1yVIAAACJANWssGQpGoOnLlkKAAAgEaAAoNnhfkg0Bu6HBOCpCFAA0MxwPyQaA/dDAvBUBCgAaGa4HxKNgfshAXgqAhQANDPcD4nGwP2QADwVF8gDAAAAgEEEKAAAAAAwiEv4AAAAmpEjR45Ikj755BOTKzl3VFVVqaSkRJGRkfL39ze7nHPGtm3bzC7BFAQoAACAZqSoqEiSNH78eJMrgado06aN2SU0KgIUAABAM5KamipJiomJUUBAgLnFnCO2bdumUaNGafny5YqNjTW7nHNKmzZt1K1bN7PLaFQEKAAAgGakQ4cOGjdunNllnJNiY2PVu3dvs8tAE8ciEgAAAABgEAEKAAAAAAwiQAEAAACAQdwDBQDNCMsX1x/LFzeMpy5fDAAEKABoRli+GI3N05YvBgACVDPBr84Nwy/P9cevzk0byxfXH8sXN5wnLl8MAASoZoJfndHY+NW5aWL54oZj+WIAgBEEqGaCX50bhl+eG4ZfnQEAgKciQDUT/Op8evjlGQAAAEawjDkAAAAAGESAAgAAAACDCFAAAAAAYBABCgAAAAAMIkABAAAAgEEEKAAAAAAwiAAFAAAAAAYRoAAAAADAIAIUAAAAABhEgAIAAAAAgwhQAAAAAGCQKQFq1qxZ8vLycnvFxMS4+o8ePar09HS1b99erVu31rBhw7R37163fezatUuDBg1SQECAgoODdd999+n48eONfSoAAAAAPEgLsw78m9/8Ru+9997/Cmnxv1KmTJmi1atX67XXXlNgYKAmTpyooUOH6r///a8kyW63a9CgQQoNDdWmTZtUWlqqW2+9VS1bttScOXMa/VwAAAAAeAbTAlSLFi0UGhp6UntFRYWeffZZrVixQgMGDJAkPffcc4qNjdUHH3ygPn366D//+Y++/PJLvffeewoJCVGvXr306KOPavr06Zo1a5Z8fHwa+3QAAAAAeADT7oEqLi5WeHi4zj//fN18883atWuXJKmgoEDHjh1TcnKya2xMTIw6d+6s/Px8SVJ+fr7i4uIUEhLiGpOSkiKbzaatW7ee8pjV1dWy2WxuLwAAAAAwypQAlZCQoGXLlmnNmjVasmSJdu7cqaSkJFVWVqqsrEw+Pj4KCgpy2yYkJERlZWWSpLKyMrfwVNtf23cqmZmZCgwMdL0iIiLO7IkBAAAAaNZMuYTvmmuucf37hRdeqISEBHXp0kWvvvqq/P39z9pxMzIyNHXqVNd7m81GiAIAAABgWJNYxjwoKEgXXHCBduzYodDQUNXU1Ki8vNxtzN69e133TIWGhp60Kl/t+7ruq6rl6+srq9Xq9gIAAAAAo5pEgDp06JC+/vprhYWFKT4+Xi1btlRubq6rf/v27dq1a5cSExMlSYmJifriiy+0b98+15icnBxZrVb16NGj0esHAAAA4BlMuYTv3nvv1ZAhQ9SlSxft2bNHDz/8sCwWi2666SYFBgZq7Nixmjp1qtq1ayer1apJkyYpMTFRffr0kSQNHDhQPXr00C233KK5c+eqrKxMM2bMUHp6unx9fc04JQAAAAAewJQA9d133+mmm27SgQMH1LFjR11xxRX64IMP1LFjR0nSE088IW9vbw0bNkzV1dVKSUnRM88849reYrEoOztbEyZMUGJiolq1aqXRo0frkUceMeN0AAAAAHgIUwLUyy+//Iv9fn5+Wrx4sRYvXnzKMV26dNHbb799pksDAAAAgFNqEvdAAQAAAMC5gAAFAAAAAAYRoAAAAADAIAIUAAAAABhEgAIAAAAAgwhQAAAAAGCQKcuYAwAAwPMcOXJERUVFZpdxkm3btrn9symKiYlRQECA2WVABCgAAAA0kqKiIsXHx5tdximNGjXK7BJOqaCgQL179za7DIgABQAAgEYSExOjgoICs8s4SVVVlUpKShQZGSl/f3+zy6lTTEyM2SXg/xGgAAAA0CgCAgKa7CzK5ZdfbnYJOEewiAQAAAAAGESAAgAAAACDCFAAAAAAYBABCgAAAAAMYhEJAMBZ11Sf/SLx/BcAQP0QoAAAZ11Tf/aLxPNfAADGEKAAAGddU332i8TzXwAA9UOAAgCcdU352S8Sz38BABjHIhIAAAAAYBABCgAAAAAMIkABAAAAgEEEKAAAAAAwiAAFAAAAAAYRoAAAAADAIAIUAAAAABhEgAIAAAAAgwhQAAAAAGBQC7MLQPN35MgRFRUVmV1GnbZt2+b2z6YoJiZGAQEBZpcBAAAAEaDQCIqKihQfH292Gb9o1KhRZpdwSgUFBerdu7fZZQAAAEAEKDSCmJgYFRQUmF1GnaqqqlRSUqLIyEj5+/ubXU6dYmJizC4BAAAA/8/L6XQ6zS7CLDabTYGBgaqoqJDVajW7HAAAAAAmMZoNWEQCAAAAAAwiQAEAAACAQQQoAAAAADCIAAUAAAAABhGgAAAAAMAgAhQAAAAAGESAAgAAAACDCFAAAAAAYBABCgAAAAAMIkABAAAAgEEEKAAAAAAwiAAFAAAAAAa1MLsAMzmdTkmSzWYzuRIAAAAAZqrNBLUZ4VQ8OkBVVlZKkiIiIkyuBAAAAEBTUFlZqcDAwFP2ezl/LWI1Yw6HQ3v27FGbNm3k5eVldjkwgc1mU0REhHbv3i2r1Wp2OQBMwPcAAL4HIP0081RZWanw8HB5e5/6TiePnoHy9vZWp06dzC4DTYDVauULE/BwfA8A4HsAvzTzVItFJAAAAADAIAIUAAAAABhEgIJH8/X11cMPPyxfX1+zSwFgEr4HAPA9gPrw6EUkAAAAAKA+mIECAAAAAIMIUAAAAABgEAEKAAAAAAwiQAEAAACAQQQoAAAAADCIAIVmKzMzU5deeqnatGmj4OBgpaamavv27b+4Tb9+/eTl5XXSa9CgQY1UNYAzqSHfA5K0cOFCde/eXf7+/oqIiNCUKVN09OjRRqgYwJnWkO+BY8eO6ZFHHlHXrl3l5+eniy66SGvWrGmkitHUEaDQbG3YsEHp6en64IMPlJOTo2PHjmngwIE6fPjwKbfJyspSaWmp61VYWCiLxaIbb7yxESsHcKY05HtgxYoVeuCBB/Twww9r27ZtevbZZ/XKK6/owQcfbMTKAZwpDfkemDFjhv7617/q6aef1pdffqm77rpLN9xwgz799NNGrBxNFc+BgsfYv3+/goODtWHDBl155ZWGtlm4cKFmzpyp0tJStWrV6ixXCOBsM/I9MHHiRG3btk25ubmutmnTpmnz5s16//33G6tUAGeJke+B8PBw/fGPf1R6erqrbdiwYfL399fy5csbq1Q0UcxAwWNUVFRIktq1a2d4m2effVYjRowgPAHNhJHvgb59+6qgoEAffvihJOmbb77R22+/rWuvvbZRagRwdhn5Hqiurpafn59bm7+/Pz+iQBIzUPAQDodD1113ncrLyw1/+X344YdKSEjQ5s2bddlll53lCgGcbfX5Hnjqqad07733yul06vjx47rrrru0ZMmSRqoUwNli9Htg5MiR+uyzz7Rq1Sp17dpVubm5uv7662W321VdXd2IFaMpYgYKHiE9PV2FhYV6+eWXDW/z7LPPKi4ujvAENBNGvwfWr1+vOXPm6JlnntEnn3yirKwsrV69Wo8++mgjVQrgbDH6PfDkk0+qW7duiomJkY+PjyZOnKjbbrtN3t786QxmoOABJk6cqDfffFMbN25UVFSUoW0OHz6s8PBwPfLII7rnnnvOcoUAzrb6fA8kJSWpT58+mjdvnqtt+fLluuOOO3To0CH+gALOUQ35e+Do0aM6cOCAwsPD9cADDyg7O1tbt249y5WiqeP/Ami2nE6nJk6cqDfeeENr1641/GUpSa+99pqqq6s1atSos1ghgLOtId8DR44cOSkkWSwW1/4AnFtO5+8BPz8/nXfeeTp+/Lhef/11XX/99WexUpwrWphdAHC2pKena8WKFXrzzTfVpk0blZWVSZICAwPl7+8vSbr11lt13nnnKTMz023bZ599VqmpqWrfvn2j1w3gzGnI98CQIUP0l7/8RRdffLESEhK0Y8cOPfTQQxoyZIgrSAE4dzTke2Dz5s36/vvv1atXL33//feaNWuWHA6H7r//ftPOA00HAQrNVu0N3/369XNrf+655zRmzBhJ0q5du076pXn79u16//339Z///KcxygRwFjXke2DGjBny8vLSjBkz9P3336tjx44aMmSI/vSnPzVW2QDOoIZ8Dxw9elQzZszQN998o9atW+vaa6/VCy+8oKCgoEaqGk0Z90ABAAAAgEHcAwUAAAAABhGgAAAAAMAgAhQAAAAAGESAAgAAAACDCFAAAAAAYBABCgAAAAAMIkABAAAAgEEEKAAAAAAwiAAFAAAAAAYRoAAAAADAIAIUAAAAABhEgAIAAAAAgwhQAAAAAGAQAQoAAAAADCJAAQAAAIBBBCgAAAAAMIgABQAAAAAGEaAAAAAAwCACFAAAAAAYRIACAAAAAIMIUAAAAABgEAEKAAAAAAwiQAEAAACAQQQoAAAAADCIAAUAAAAABhGgAAAAAMAgAhQA4IwbM2aMIiMjzS7DkMjISA0ePPhXx61fv15eXl5av379aR/zXPp8AADuCFAAAEO8vLwMvc5EwDjTvvzyS82aNUslJSVml1KnI0eOaNasWU3yswMAuGthdgEAgHPDCy+84Pb+X//6l3Jyck5qj42N1d///nc5HI7GLO8Xffnll5o9e7b69evX4JmfK6+8UlVVVfLx8Tnten7++Rw5ckSzZ8+WJPXr1++09w8AOHsIUAAAQ0aNGuX2/oMPPlBOTs5J7c2Vt7e3/Pz8zsi+WrZseUb282sOHz6sVq1aNcqxAMBTcAkfAOCM+/k9PiUlJfLy8tL8+fO1ePFinX/++QoICNDAgQO1e/duOZ1OPfroo+rUqZP8/f11/fXX6+DBgyft95133lFSUpJatWqlNm3aaNCgQdq6desv1rJs2TLdeOONkqT+/fuf8lLD999/X5dddpn8/Px0/vnn61//+pdbf133QBUXF2vYsGEKDQ2Vn5+fOnXqpBEjRqiiosLw51NSUqKOHTtKkmbPnu2qb9asWa7xRUVFSktLU7t27eTn56dLLrlEb7311knn6eXlpQ0bNujuu+9WcHCwOnXq9It1AADqjxkoAECjefHFF1VTU6NJkybp4MGDmjt3roYPH64BAwZo/fr1mj59unbs2KGnn35a9957r/75z3+6tn3hhRc0evRopaSk6PHHH9eRI0e0ZMkSXXHFFfr0009PeWnelVdeqT/84Q966qmn9OCDDyo2NlaSXP+UpB07digtLU1jx47V6NGj9c9//lNjxoxRfHy8fvOb39S535qaGqWkpKi6ulqTJk1SaGiovv/+e2VnZ6u8vFyBgYGGPpOOHTtqyZIlmjBhgm644QYNHTpUknThhRdKkrZu3arLL79c5513nh544AG1atVKr776qlJTU/X666/rhhtucNvf3XffrY4dO2rmzJk6fPiwoRoAAPXgBACgAdLT052n+t/I6NGjnV26dHG937lzp1OSs2PHjs7y8nJXe0ZGhlOS86KLLnIeO3bM1X7TTTc5fXx8nEePHnU6nU5nZWWlMygoyDl+/Hi345SVlTkDAwNPav+51157zSnJuW7dupP6unTp4pTk3Lhxo6tt3759Tl9fX+e0adNcbevWrXPbx6effuqU5Hzttdd+8dh1+fnns3//fqck58MPP3zS2KuuusoZFxfn+iycTqfT4XA4+/bt6+zWrZur7bnnnnNKcl5xxRXO48eP17smAIAxXMIHAGg0N954o9vMTEJCgqSf7q9q0aKFW3tNTY2+//57SVJOTo7Ky8t100036YcffnC9LBaLEhIStG7dutOqq0ePHkpKSnK979ixo7p3765vvvnmlNvUnse7776rI0eOnNbxT+XgwYNau3athg8frsrKStd5HzhwQCkpKSouLnZ9RrXGjx8vi8VyVuoBAHAJHwCgEXXu3NntfW0IiYiIqLP9xx9/lPTTvUaSNGDAgDr3a7Vaz2hdktS2bVvX8esSFRWlqVOn6i9/+YtefPFFJSUl6brrrtOoUaMMX773a3bs2CGn06mHHnpIDz30UJ1j9u3bp/POO8+tLgDA2UOAAgA0mlPNjJyq3el0SpJrye8XXnhBoaGhJ407cfbqTNZVe/xTWbBggcaMGaM333xT//nPf/SHP/xBmZmZ+uCDD87IAg61533vvfcqJSWlzjHR0dFu7/39/U/7uACAUyNAAQCavK5du0qSgoODlZycXO/tvby8znRJLnFxcYqLi9OMGTO0adMmXX755Vq6dKkee+yx067v/PPPl/TTsucNOW8AwJnHPVAAgCYvJSVFVqtVc+bM0bFjx07q379//y9uX/sspPLy8jNWk81m0/Hjx93a4uLi5O3trerq6nrtKyAgQNLJ9QUHB6tfv37661//qtLS0pO2+7XzBgCcecxAAQCaPKvVqiVLluiWW25R7969NWLECHXs2FG7du3S6tWrdfnll2vRokWn3L5Xr16yWCx6/PHHVVFRIV9fXw0YMEDBwcENrmnt2rWaOHGibrzxRl1wwQU6fvy4XnjhBVksFg0bNqxe+/L391ePHj30yiuv6IILLlC7du3Us2dP9ezZU4sXL9YVV1yhuLg4jR8/Xueff7727t2r/Px8fffdd/rss88afA4AgPojQAEAzgkjR45UeHi4/vznP2vevHmqrq7Weeedp6SkJN12222/uG1oaKiWLl2qzMxMjR07Vna7XevWrTutAHXRRRcpJSVF//73v/X9998rICBAF110kd555x316dOn3vv7xz/+oUmTJmnKlCmqqanRww8/rJ49e6pHjx76+OOPNXv2bC1btkwHDhxQcHCwLr74Ys2cObPB9QMAGsbL+Wt3yAIAAAAAJHEPFAAAAAAYRoACAAAAAIMIUAAAAABgEAEKAAAAAAwiQAEAAACAQR69jLnD4dCePXvUpk2bs/qUegAAAABNm9PpVGVlpcLDw+Xtfep5Jo8OUHv27FFERITZZQAAAABoInbv3q1OnTqdst+jA1SbNm0k/fQhWa1Wk6sBAAAAYBabzaaIiAhXRjgVjw5QtZftWa1WAhQAAACAX721h0UkAAAAAMAgAhQAAAAAGESAAgAAAACDCFAAAAAAYBABCgAAAAAMIkABAAAAgEEEKAAAAAAwiAAFAAAAAAZ59IN0AQAA4Nnsdrvy8vJUWlqqsLAwJSUlyWKxmF0WmjBmoAAAAOCRsrKyFB0drf79+2vkyJHq37+/oqOjlZWVZXZpaMIIUAAAAPA4WVlZSktLU1xcnPLz81VZWan8/HzFxcUpLS2NEIVT8nI6nU6zizCLzWZTYGCgKioqZLVazS4HAAAAjcButys6OlpxcXFatWqVvL3/N6fgcDiUmpqqwsJCFRcXczmfBzGaDZiBAgAAgEfJy8tTSUmJHnzwQbfwJEne3t7KyMjQzp07lZeXZ1KFaMoIUAAAAPAopaWlkqSePXvW2V/bXjsOOBEBCgAAAB4lLCxMklRYWFhnf2177TjgRAQoAAAAeJSkpCRFRkZqzpw5cjgcbn0Oh0OZmZmKiopSUlKSSRWiKSNAAQAAwKNYLBYtWLBA2dnZSk1NdVuFLzU1VdnZ2Zo/fz4LSKBOPEgXAAAAHmfo0KFauXKlpk2bpr59+7rao6KitHLlSg0dOtTE6tCUsYw5y5gDAAB4LLvdrry8PJWWliosLExJSUnMPHkoo9mAGSgAAAB4LIvFon79+pldBs4h3AMFAAAAAAYRoAAAAADAIAIUAAAAABhEgAIAAAAAgwhQAAAAAGAQAQoAAAAADCJAAQAAAIBBBCgAAAAAMIgABQAAAAAG1StALVmyRBdeeKGsVqusVqsSExP1zjvvuPr79esnLy8vt9ddd93lto9du3Zp0KBBCggIUHBwsO677z4dP37cbcz69evVu3dv+fr6Kjo6WsuWLTuplsWLFysyMlJ+fn5KSEjQhx9+WJ9TAQAAAIB6q1eA6tSpk/785z+roKBAH3/8sQYMGKDrr79eW7dudY0ZP368SktLXa+5c+e6+ux2uwYNGqSamhpt2rRJzz//vJYtW6aZM2e6xuzcuVODBg1S//79tWXLFk2ePFnjxo3Tu+++6xrzyiuvaOrUqXr44Yf1ySef6KKLLlJKSor27dt3Op8FAAAAAPwiL6fT6TydHbRr107z5s3T2LFj1a9fP/Xq1UsLFy6sc+w777yjwYMHa8+ePQoJCZEkLV26VNOnT9f+/fvl4+Oj6dOna/Xq1SosLHRtN2LECJWXl2vNmjWSpISEBF166aVatGiRJMnhcCgiIkKTJk3SAw88cMpaq6urVV1d7Xpvs9kUERGhiooKWa3W0/kYAAAAAJzDbDabAgMDfzUbNPgeKLvdrpdfflmHDx9WYmKiq/3FF19Uhw4d1LNnT2VkZOjIkSOuvvz8fMXFxbnCkySlpKTIZrO5ZrHy8/OVnJzsdqyUlBTl5+dLkmpqalRQUOA2xtvbW8nJya4xp5KZmanAwEDXKyIioqGnDwAAAMADtajvBl988YUSExN19OhRtW7dWm+88YZ69OghSRo5cqS6dOmi8PBwff7555o+fbq2b9+urKwsSVJZWZlbeJLkel9WVvaLY2w2m6qqqvTjjz/KbrfXOaaoqOgXa8/IyNDUqVNd72tnoAAAAADAiHoHqO7du2vLli2qqKjQypUrNXr0aG3YsEE9evTQHXfc4RoXFxensLAwXXXVVfr666/VtWvXM1p4Q/j6+srX19fsMgAAAACco+p9CZ+Pj4+io6MVHx+vzMxMXXTRRXryySfrHJuQkCBJ2rFjhyQpNDRUe/fudRtT+z40NPQXx1itVvn7+6tDhw6yWCx1jqndBwAAAACcDaf9HCiHw+G2MMOJtmzZIkkKCwuTJCUmJuqLL75wWy0vJydHVqvVdRlgYmKicnNz3faTk5Pjus/Kx8dH8fHxbmMcDodyc3Pd7sUCAAAAgDOtXpfwZWRk6JprrlHnzp1VWVmpFStWaP369Xr33Xf19ddfa8WKFbr22mvVvn17ff7555oyZYquvPJKXXjhhZKkgQMHqkePHrrllls0d+5clZWVacaMGUpPT3ddWnfXXXdp0aJFuv/++3X77bdr7dq1evXVV7V69WpXHVOnTtXo0aN1ySWX6LLLLtPChQt1+PBh3XbbbWfwowEAAAAAd/UKUPv27dOtt96q0tJSBQYG6sILL9S7776r3/3ud9q9e7fee+89V5iJiIjQsGHDNGPGDNf2FotF2dnZmjBhghITE9WqVSuNHj1ajzzyiGtMVFSUVq9erSlTpujJJ59Up06d9I9//EMpKSmuMb///e+1f/9+zZw5U2VlZerVq5fWrFlz0sISAAAAAHAmnfZzoM5lRtd6BwAAANC8nfXnQAEAAACApyFAAQAAAIBBBCgAAAAAMIgABQAAAAAGEaAAAAAAwCACFAAAAAAYRIACAAAAAIMIUAAAAABgEAEKAAAAAAwiQAEAAACAQQQoAAAAADCIAAUAAAAABhGgAAAAAMAgAhQAAAAAGESAAgAAAACDCFAAAAAAYBABCgAAAAAMIkABAAAAgEEEKAAAAAAwiAAFAAAAAAYRoAAAAADAIAIUAAAAABhEgAIAAAAAgwhQAAAAAGAQAQoAAAAADCJAAQAAAIBBBCgAAAAAMIgABQAAAAAGEaAAAAAAwCACFAAAAAAYRIACAAAAAIMIUAAAAABgEAEKAAAAAAwiQAEAAACAQfUKUEuWLNGFF14oq9Uqq9WqxMREvfPOO67+o0ePKj09Xe3bt1fr1q01bNgw7d27120fu3bt0qBBgxQQEKDg4GDdd999On78uNuY9evXq3fv3vL19VV0dLSWLVt2Ui2LFy9WZGSk/Pz8lJCQoA8//LA+pwIAAAAA9VavANWpUyf9+c9/VkFBgT7++GMNGDBA119/vbZu3SpJmjJliv7973/rtdde04YNG7Rnzx4NHTrUtb3dbtegQYNUU1OjTZs26fnnn9eyZcs0c+ZM15idO3dq0KBB6t+/v7Zs2aLJkydr3Lhxevfdd11jXnnlFU2dOlUPP/ywPvnkE1100UVKSUnRvn37TvfzAAAAAIBT8nI6nc7T2UG7du00b948paWlqWPHjlqxYoXS0tIkSUVFRYqNjVV+fr769Omjd955R4MHD9aePXsUEhIiSVq6dKmmT5+u/fv3y8fHR9OnT9fq1atVWFjoOsaIESNUXl6uNWvWSJISEhJ06aWXatGiRZIkh8OhiIgITZo0SQ888IDh2m02mwIDA1VRUSGr1Xo6HwMAAACAc5jRbNDge6DsdrtefvllHT58WImJiSooKNCxY8eUnJzsGhMTE6POnTsrPz9fkpSfn6+4uDhXeJKklJQU2Ww21yxWfn6+2z5qx9Tuo6amRgUFBW5jvL29lZyc7BpzKtXV1bLZbG4vAAAAADCq3gHqiy++UOvWreXr66u77rpLb7zxhnr06KGysjL5+PgoKCjIbXxISIjKysokSWVlZW7hqba/tu+XxthsNlVVVemHH36Q3W6vc0ztPk4lMzNTgYGBrldERER9Tx8AAACAB6t3gOrevbu2bNmizZs3a8KECRo9erS+/PLLs1HbGZeRkaGKigrXa/fu3WaXBAAAAOAc0qK+G/j4+Cg6OlqSFB8fr48++khPPvmkfv/736umpkbl5eVus1B79+5VaGioJCk0NPSk1fJqV+k7cczPV+7bu3evrFar/P39ZbFYZLFY6hxTu49T8fX1la+vb31PGQAAAAAknYHnQDkcDlVXVys+Pl4tW7ZUbm6uq2/79u3atWuXEhMTJUmJiYn64osv3FbLy8nJkdVqVY8ePVxjTtxH7Zjaffj4+Cg+Pt5tjMPhUG5urmsMAAAAAJwN9ZqBysjI0DXXXKPOnTursrJSK1as0Pr16/Xuu+8qMDBQY8eO1dSpU9WuXTtZrVZNmjRJiYmJ6tOnjyRp4MCB6tGjh2655RbNnTtXZWVlmjFjhtLT010zQ3fddZcWLVqk+++/X7fffrvWrl2rV199VatXr3bVMXXqVI0ePVqXXHKJLrvsMi1cuFCHDx/WbbfddgY/GgAAAABwV68AtW/fPt16660qLS1VYGCgLrzwQr377rv63e9+J0l64okn5O3trWHDhqm6ulopKSl65plnXNtbLBZlZ2drwoQJSkxMVKtWrTR69Gg98sgjrjFRUVFavXq1pkyZoieffFKdOnXSP/7xD6WkpLjG/P73v9f+/fs1c+ZMlZWVqVevXlqzZs1JC0sAAAAAwJl02s+BOpfxHCgAAAAAUiM8BwoAAAAAPA0BCgAAAAAMIkABAAAAgEEEKAAAAAAwiAAFAAAAAAYRoAAAAADAIAIUAAAAABhEgAIAAAAAgwhQAAAAAGAQAQoAAAAADCJAAQAAAIBBBCgAAAAAMIgABQAAAAAGEaAAAAAAwCACFAAAAAAYRIACAAAAAIMIUAAAAABgEAEKAAAAAAwiQAEAAACAQQQoAAAAADCIAAUAAAAABhGgAAAAAMAgAhQAAAAAGESAAgAAAACDCFAAAAAAYBABCgAAAAAMIkABAAAAgEEEKAAAAAAwiAAFAAAAAAYRoAAAAADAIAIUAAAAABhEgAIAAAAAgwhQAAAAAGAQAQoAAAAADKpXgMrMzNSll16qNm3aKDg4WKmpqdq+fbvbmH79+snLy8vtddddd7mN2bVrlwYNGqSAgAAFBwfrvvvu0/Hjx93GrF+/Xr1795avr6+io6O1bNmyk+pZvHixIiMj5efnp4SEBH344Yf1OR0AAAAAqJd6BagNGzYoPT1dH3zwgXJycnTs2DENHDhQhw8fdhs3fvx4lZaWul5z58519dntdg0aNEg1NTXatGmTnn/+eS1btkwzZ850jdm5c6cGDRqk/v37a8uWLZo8ebLGjRund9991zXmlVde0dSpU/Xwww/rk08+0UUXXaSUlBTt27evoZ8FAAAAAPwiL6fT6Wzoxvv371dwcLA2bNigK6+8UtJPM1C9evXSwoUL69zmnXfe0eDBg7Vnzx6FhIRIkpYuXarp06dr//798vHx0fTp07V69WoVFha6thsxYoTKy8u1Zs0aSVJCQoIuvfRSLVq0SJLkcDgUERGhSZMm6YEHHjBUv81mU2BgoCoqKmS1Whv6MQAAAAA4xxnNBqd1D1RFRYUkqV27dm7tL774ojp06KCePXsqIyNDR44ccfXl5+crLi7OFZ4kKSUlRTabTVu3bnWNSU5OdttnSkqK8vPzJUk1NTUqKChwG+Pt7a3k5GTXmLpUV1fLZrO5vQAAAADAqBYN3dDhcGjy5Mm6/PLL1bNnT1f7yJEj1aVLF4WHh+vzzz/X9OnTtX37dmVlZUmSysrK3MKTJNf7srKyXxxjs9lUVVWlH3/8UXa7vc4xRUVFp6w5MzNTs2fPbugpAwAAAPBwDQ5Q6enpKiws1Pvvv+/Wfscdd7j+PS4uTmFhYbrqqqv09ddfq2vXrg2v9AzIyMjQ1KlTXe9tNpsiIiJMrAhmstvtysvLU2lpqcLCwpSUlCSLxWJ2WQAAAGjCGhSgJk6cqOzsbG3cuFGdOnX6xbEJCQmSpB07dqhr164KDQ09abW8vXv3SpJCQ0Nd/6xtO3GM1WqVv7+/LBaLLBZLnWNq91EXX19f+fr6GjtJNGtZWVmaNm2aSkpKXG2RkZFasGCBhg4dal5hAAAAaNLqdQ+U0+nUxIkT9cYbb2jt2rWKior61W22bNkiSQoLC5MkJSYm6osvvnBbLS8nJ0dWq1U9evRwjcnNzXXbT05OjhITEyVJPj4+io+PdxvjcDiUm5vrGgOcSlZWltLS0hQXF6f8/HxVVla67s1LS0tzXW4KAAAA/Fy9VuG7++67tWLFCr355pvq3r27qz0wMFD+/v76+uuvtWLFCl177bVq3769Pv/8c02ZMkWdOnXShg0bJP102VSvXr0UHh6uuXPnqqysTLfccovGjRunOXPmSPppGfOePXsqPT1dt99+u9auXas//OEPWr16tVJSUiT9tIz56NGj9de//lWXXXaZFi5cqFdffVVFRUUn3Rt1KqzC53nsdruio6MVFxenVatWydv7f78hOBwOpaamqrCwUMXFxVzOBwAA4EEMZwNnPUiq8/Xcc885nU6nc9euXc4rr7zS2a5dO6evr68zOjraed999zkrKirc9lNSUuK85pprnP7+/s4OHTo4p02b5jx27JjbmHXr1jl79erl9PHxcZ5//vmuY5zo6aefdnbu3Nnp4+PjvOyyy5wffPBBfU7HWVFR4ZR0Un1ovtatW+eU5MzPz6+zf9OmTU5JznXr1jVuYQAAADCV0WxwWs+BOtcxA+V5XnrpJY0cOVKVlZVq3br1Sf2VlZWyWq1asWKFbrrpJhMqBAAAgBka5TlQwLmm9l68Ex/SfKLa9tpxAAAAwIkIUPAoSUlJioyM1Jw5c+RwONz6HA6HMjMzFRUVpaSkJJMqBAAAQFNGgIJHsVgsWrBggbKzs5Wamuq2Cl9qaqqys7M1f/58FpAAAABAnRr8IF3gXDV06FCtXLlS06ZNU9++fV3tUVFRWrlyJc+BAgAAwCmxiASLSHgsu92uvLw8lZaWKiwsTElJScw8AQAAeCij2YAZKHgsi8Wifv36mV0GAAAAziHcAwUAAAAABhGgAAAAAMAgAhQAAAAAGESAAgAAAACDCFAAAAAAYBABCgAAAAAMIkABAAAAgEEEKAAAAAAwiAAFAAAAAAYRoAAAAADAIAIUAAAAABhEgAIAAAAAgwhQAAAAAGAQAQoAAAAADCJAAQAAAIBBBCgAAAAAMIgABQAAAAAGEaAAAAAAwCACFAAAAAAYRIACAAAAAIMIUAAAAABgEAEKAAAAAAwiQAEAAACAQQQoAAAAADCIAAUAAAAABhGgAAAAAMAgAhQAAAAAGESAAgAAAACDCFAAAAAAYFC9AlRmZqYuvfRStWnTRsHBwUpNTdX27dvdxhw9elTp6elq3769WrdurWHDhmnv3r1uY3bt2qVBgwYpICBAwcHBuu+++3T8+HG3MevXr1fv3r3l6+ur6OhoLVu27KR6Fi9erMjISPn5+SkhIUEffvhhfU4HAAAAAOqlXgFqw4YNSk9P1wcffKCcnBwdO3ZMAwcO1OHDh11jpkyZon//+9967bXXtGHDBu3Zs0dDhw519dvtdg0aNEg1NTXatGmTnn/+eS1btkwzZ850jdm5c6cGDRqk/v37a8uWLZo8ebLGjRund9991zXmlVde0dSpU/Xwww/rk08+0UUXXaSUlBTt27fvdD4PAAAAADglL6fT6Wzoxvv371dwcLA2bNigK6+8UhUVFerYsaNWrFihtLQ0SVJRUZFiY2OVn5+vPn366J133tHgwYO1Z88ehYSESJKWLl2q6dOna//+/fLx8dH06dO1evVqFRYWuo41YsQIlZeXa82aNZKkhIQEXXrppVq0aJEkyeFwKCIiQpMmTdIDDzxQZ73V1dWqrq52vbfZbIqIiFBFRYWsVmtDPwYAAAAA5zibzabAwMBfzQandQ9URUWFJKldu3aSpIKCAh07dkzJycmuMTExMercubPy8/MlSfn5+YqLi3OFJ0lKSUmRzWbT1q1bXWNO3EftmNp91NTUqKCgwG2Mt7e3kpOTXWPqkpmZqcDAQNcrIiLidE4fAAAAgIdpcIByOByaPHmyLr/8cvXs2VOSVFZWJh8fHwUFBbmNDQkJUVlZmWvMieGptr+275fG2Gw2VVVV6YcffpDdbq9zTO0+6pKRkaGKigrXa/fu3fU/cQAAAAAeq0VDN0xPT1dhYaHef//9M1nPWeXr6ytfX1+zywAAAABwjmrQDNTEiROVnZ2tdevWqVOnTq720NBQ1dTUqLy83G383r17FRoa6hrz81X5at//2hir1Sp/f3916NBBFoulzjG1+wAAAACAM61eAcrpdGrixIl64403tHbtWkVFRbn1x8fHq2XLlsrNzXW1bd++Xbt27VJiYqIkKTExUV988YXbank5OTmyWq3q0aOHa8yJ+6gdU7sPHx8fxcfHu41xOBzKzc11jQEAAACAM61el/Clp6drxYoVevPNN9WmTRvX/UaBgYHy9/dXYGCgxo4dq6lTp6pdu3ayWq2aNGmSEhMT1adPH0nSwIED1aNHD91yyy2aO3euysrKNGPGDKWnp7sur7vrrru0aNEi3X///br99tu1du1avfrqq1q9erWrlqlTp2r06NG65JJLdNlll2nhwoU6fPiwbrvttjP12QAAAACAm3otY+7l5VVn+3PPPacxY8ZI+ulButOmTdNLL72k6upqpaSk6JlnnnG7tO7bb7/VhAkTtH79erVq1UqjR4/Wn//8Z7Vo8b88t379ek2ZMkVffvmlOnXqpIceesh1jFqLFi3SvHnzVFZWpl69eumpp55SQkKC4ZM3ulQhAAAAgObNaDY4redAnesIUAAAAACkRnoOFAAAAAB4EgIUAAAAABhEgAIAAAAAgwhQAAAAAGAQAQoAAAAADCJAAQAAAIBBBCgAAAAAMIgABQAAAAAGEaAAAAAAwCACFAAAAAAYRIACAAAAAIMIUAAAAABgEAEKAAAAAAwiQAEAAACAQQQoAAAAADCIAAUAAAAABhGgAAAAAMAgAhQAAAAAGESAAgAAAACDCFAAAAAAYBABCgAAAAAMIkABAAAAgEEEKAAAAAAwqIXZBQBmsdvtysvLU2lpqcLCwpSUlCSLxWJ2WQAAAGjCmIGCR8rKylJ0dLT69++vkSNHqn///oqOjlZWVpbZpQEAAKAJI0DB42RlZSktLU1xcXHKz89XZWWl8vPzFRcXp7S0NEIUAAAATsnL6XQ6zS7CLDabTYGBgaqoqJDVajW7HDQCu92u6OhoxcXFadWqVfL2/t9vCA6HQ6mpqSosLFRxcTGX8wEAAHgQo9mAGSh4lLy8PJWUlOjBBx90C0+S5O3trYyMDO3cuVN5eXkmVQgAAICmjAAFj1JaWipJ6tmzZ539te214wAAAIATEaDgUcLCwiRJhYWFdfbXtteOAwAAAE5EgIJHSUpKUmRkpObMmSOHw+HW53A4lJmZqaioKCUlJZlUIQAAAJoyAhQ8isVi0YIFC5Sdna3U1FS3VfhSU1OVnZ2t+fPns4AEAAAA6sSDdOFxhg4dqpUrV2ratGnq27evqz0qKkorV67U0KFDTawOAAAATRnLmLOMucey2+3Ky8tTaWmpwsLClJSUxMwTAACAhzpry5hv3LhRQ4YMUXh4uLy8vLRq1Sq3/jFjxsjLy8vtdfXVV7uNOXjwoG6++WZZrVYFBQVp7NixOnTokNuYzz//XElJSfLz81NERITmzp17Ui2vvfaaYmJi5Ofnp7i4OL399tv1PR14MIvFon79+ummm25Sv379CE8AAAD4VfUOUIcPH9ZFF12kxYsXn3LM1VdfrdLSUtfrpZdecuu/+eabtXXrVuXk5Cg7O1sbN27UHXfc4eq32WwaOHCgunTpooKCAs2bN0+zZs3S3/72N9eYTZs26aabbtLYsWP16aefKjU11fUQVAAAAMAIu92u9evX66WXXtL69etlt9vNLglN3Gldwufl5aU33nhDqamprrYxY8aovLz8pJmpWtu2bVOPHj300Ucf6ZJLLpEkrVmzRtdee62+++47hYeHa8mSJfrjH/+osrIy+fj4SJIeeOABrVq1SkVFRZKk3//+9zp8+LCys7Nd++7Tp4969eqlpUuXGqqfS/g8G5fwAQDg2bKysjRt2jSVlJS42iIjI7VgwQLuifZAZ+0SPiPWr1+v4OBgde/eXRMmTNCBAwdcffn5+QoKCnKFJ0lKTk6Wt7e3Nm/e7Bpz5ZVXusKTJKWkpGj79u368ccfXWOSk5PdjpuSkqL8/PxT1lVdXS2bzeb2gmfKyspSdHS0+vfvr5EjR6p///6Kjo5WVlaW2aUBAIBGkJWVpbS0NMXFxbmtyhsXF6e0tDT+JsApnfEAdfXVV+tf//qXcnNz9fjjj2vDhg265pprXNOhZWVlCg4OdtumRYsWateuncrKylxjQkJC3MbUvv+1MbX9dcnMzFRgYKDrFRERcXoni3MSX5gAAHg2u92uadOmafDgwVq1apX69Omj1q1bq0+fPlq1apUGDx6se++9l8v5UKczHqBGjBih6667TnFxca7n6nz00Udav379mT5UvWVkZKiiosL12r17t9kloZHxhQkAAPLy8lRSUqIHH3xQ3t7ufw57e3srIyNDO3fuVF5enkkVoik76w/SPf/889WhQwft2LFDkhQaGqp9+/a5jTl+/LgOHjyo0NBQ15i9e/e6jal9/2tjavvr4uvrK6vV6vaCZ+ELEwAAlJaWSpJ69uxZZ39te+044ERnPUB99913OnDggMLCwiRJiYmJKi8vV0FBgWvM2rVr5XA4lJCQ4BqzceNGHTt2zDUmJydH3bt3V9u2bV1jcnNz3Y6Vk5OjxMTEs31KOIfxhQkAAGr/Lj3V6s217bXjgBPVO0AdOnRIW7Zs0ZYtWyRJO3fu1JYtW7Rr1y4dOnRI9913nz744AOVlJQoNzdX119/vaKjo5WSkiJJio2N1dVXX63x48frww8/1H//+19NnDhRI0aMUHh4uCRp5MiR8vHx0dixY7V161a98sorevLJJzV16lRXHffcc4/WrFmjBQsWqKioSLNmzdLHH3+siRMnnoGPBc0VX5gAACApKUmRkZGaM2eOHA6HW5/D4VBmZqaioqKUlJRkUoVo0pz1tG7dOqekk16jR492HjlyxDlw4EBnx44dnS1btnR26dLFOX78eGdZWZnbPg4cOOC86aabnK1bt3ZarVbnbbfd5qysrHQb89lnnzmvuOIKp6+vr/O8885z/vnPfz6plldffdV5wQUXOH18fJy/+c1vnKtXr67XuVRUVDglOSsqKur7MeAcdfz4cWdkZKRzyJAhTrvd7tZnt9udQ4YMcUZFRTmPHz9uUoUAAKAxvP76604vLy/nkCFDnJs2bXLabDbnpk2bnEOGDHF6eXk5X3/9dbNLRCMzmg1O6zlQ5zqeA+WZalfhGzx4sDIyMtSzZ08VFhYqMzNT2dnZWrlyJc9+AADAA9T1HKioqCjNnz+fvwU8kNFsQIAiQHkkvjABAID00wq9eXl5Ki0tVVhYmJKSkmSxWMwuCyYgQBlAgPJsfGECAACgltFs0KIRawKaFIvFon79+pldBgAAAM4hZ30ZcwAAAABoLghQAAAAAGAQAQoAAAAADCJAAQAAAIBBBCgAAAAAMIgABQAAAAAGEaAAAAAAwCACFAAAAAAYRIACAAAAAIMIUAAAAABgEAEKAAAAAAwiQAEAAACAQQQoAAAAADCIAAUAAAAABhGgAAAAAMAgAhQAAAAAGESAAgAAAACDCFAAAAAAYBABCgAAAAAMIkABAAAAgEEEKAAAAAAwiAAFAAAAAAYRoAAAAADAIAIUAAAAABhEgAIAAAAAgwhQAAAAAGAQAQoAAAAADCJAAQAAAIBBBCgAAAAAMIgABQAAAAAGEaAAAAAAwKB6B6iNGzdqyJAhCg8Pl5eXl1atWuXW73Q6NXPmTIWFhcnf31/JyckqLi52G3Pw4EHdfPPNslqtCgoK0tixY3Xo0CG3MZ9//rmSkpLk5+eniIgIzZ0796RaXnvtNcXExMjPz09xcXF6++2363s6AAAAAGBYvQPU4cOHddFFF2nx4sV19s+dO1dPPfWUli5dqs2bN6tVq1ZKSUnR0aNHXWNuvvlmbd26VTk5OcrOztbGjRt1xx13uPptNpsGDhyoLl26qKCgQPPmzdOsWbP0t7/9zTVm06ZNuummmzR27Fh9+umnSk1NVWpqqgoLC+t7SgAAAABgiJfT6XQ2eGMvL73xxhtKTU2V9NPsU3h4uKZNm6Z7771XklRRUaGQkBAtW7ZMI0aM0LZt29SjRw999NFHuuSSSyRJa9as0bXXXqvvvvtO4eHhWrJkif74xz+qrKxMPj4+kqQHHnhAq1atUlFRkSTp97//vQ4fPqzs7GxXPX369FGvXr20dOlSQ/XbbDYFBgaqoqJCVqu1oR8DAOBXHDlyxPX93dRUVVWppKREkZGR8vf3N7ucOsXExCggIMDsMgCgWTOaDVqcyYPu3LlTZWVlSk5OdrUFBgYqISFB+fn5GjFihPLz8xUUFOQKT5KUnJwsb29vbd68WTfccIPy8/N15ZVXusKTJKWkpOjxxx/Xjz/+qLZt2yo/P19Tp051O35KSspJlxSeqLq6WtXV1a73NpvtDJw1AODXFBUVKT4+3uwyzlkFBQXq3bu32WUAAHSGA1RZWZkkKSQkxK09JCTE1VdWVqbg4GD3Ilq0ULt27dzGREVFnbSP2r62bduqrKzsF49Tl8zMTM2ePbsBZwYAOB0xMTEqKCgwu4w6bdu2TaNGjdLy5csVGxtrdjl1iomJMbsEAMD/O6MBqqnLyMhwm7Wy2WyKiIgwsSIA8AwBAQFNfgYlNja2ydcIADDfGQ1QoaGhkqS9e/cqLCzM1b5371716tXLNWbfvn1u2x0/flwHDx50bR8aGqq9e/e6jal9/2tjavvr4uvrK19f3wacGU4H9z6cHu59AAAAaDrOaICKiopSaGiocnNzXYHJZrNp8+bNmjBhgiQpMTFR5eXlKigocF0Pv3btWjkcDiUkJLjG/PGPf9SxY8fUsmVLSVJOTo66d++utm3busbk5uZq8uTJruPn5OQoMTHxTJ4SzgDufTg93PsAAADQdNQ7QB06dEg7duxwvd+5c6e2bNmidu3aqXPnzpo8ebIee+wxdevWTVFRUXrooYcUHh7uWqkvNjZWV199tcaPH6+lS5fq2LFjmjhxokaMGKHw8HBJ0siRIzV79myNHTtW06dPV2FhoZ588kk98cQTruPec889+u1vf6sFCxZo0KBBevnll/Xxxx+7LXWOpoF7H04P9z4AAAA0HfUOUB9//LH69+/vel97T9Ho0aO1bNky3X///Tp8+LDuuOMOlZeX64orrtCaNWvk5+fn2ubFF1/UxIkTddVVV8nb21vDhg3TU0895eoPDAzUf/7zH6Wnpys+Pl4dOnTQzJkz3Z4V1bdvX61YsUIzZszQgw8+qG7dumnVqlXq2bNngz4InD3c+wAAAIDm4rSeA3Wu4zlQ+OSTTxQfH89lcoAH43sAACCZ9BwoAAAA4FxSU1OjZ555Rl9//bW6du2qu+++2+1ZpMDPEaAAAADgke6//3498cQTOn78uKvtvvvu05QpUzR37lwTK0NT5m12AQAAAEBju//++zVv3jy1b99ef//731VaWqq///3vat++vebNm6f777/f7BLRRBGgAAAA4FFqamr0xBNPKCQkRN99953GjRun0NBQjRs3Tt99951CQkL0xBNPqKamxuxS0QQRoAAAAOBRnnnmGR0/flyPPfaYWrRwv6OlRYsWeuSRR3T8+HE988wzJlWIpowABQAAAI/y9ddfS5IGDx5cZ39te+044EQEKAAAAHiUrl27SpKys7Pr7K9trx0HnIgABQAAAI9y9913q0WLFpoxY4bbCnySdPz4cc2cOVMtWrTQ3XffbVKFaMpYxhwAAAAexcfHR1OmTNG8efPUqVMn3XzzzTr//PP1zTff6MUXX9TevXt133338Two1IkABQAAAI8zd+5cffXVV3rzzTf1l7/8xa3v+uuv5zlQOCUCFAAAADxOVlaW3nrrLQ0aNEjR0dGqqqqSv7+/duzYobfeektZWVkaOnSo2WWiCSJAAQAAwKPY7XZNmzZNgwcP1qpVq+Tt/b9lARwOh1JTU3Xvvffq+uuvl8ViMbFSNEUsIgEAAACPkpeXp5KSEj344INu4UmSvL29lZGRoZ07dyovL8+kCtGUEaAAAADgUUpLSyVJPXv2rLO/tr12HHAiAhQAAAA8SlhYmCSpsLCwzv7a9tpxwIkIUAAAAPAoSUlJioyM1Jw5c+RwONz6HA6HMjMzFRUVpaSkJJMqRFNGgAIAAIBHsVgsWrBggbKzs5Wamqr8/HxVVlYqPz9fqampys7O1vz581lAAnViFT4AAAA0iiNHjqioqMjsMiRJkZGRmjt3rp544gn17dvX1X7eeedp7ty5ioyM1CeffGJihe5iYmIUEBBgdhkQAQoAAACNpKioSPHx8WaX8Yu+//573XfffWaXcZKCggL17t3b7DIgAhQAAAAaSUxMjAoKCswu4yTbtm3TqFGjtHz5csXGxppdTp1iYmLMLgH/jwAFAACARhEQENCkZ1FiY2ObdH1oGlhEAgAAAAAMIkABAAAAgEEEKAAAAAAwiAAFAAAAAAaxiAQANDPFxcWqrKw0u4xzxrZt29z+CePatGmjbt26mV0GADQqAlQzwh9N9ccfTg3DH01NV3FxsS644AKzyzgnjRo1yuwSzklfffUV3wcAPAoBqpngj6bTwx9O9ccfTU1T7Y8oTflZJk1NVVWVSkpKFBkZKX9/f7PLOWfUPjeHH+4AeBoCVDPBH00Nwx9O9ccfTecGnmVSP5dffrnZJQAAzhEEqGaGP5rqjz+cAAAAYBSr8AEAAACAQQQoAAAAADCIAAUAAAAABhGgAAAAAMCgM76IxKxZszR79my3tu7du6uoqEiSdPToUU2bNk0vv/yyqqurlZKSomeeeUYhISGu8bt27dKECRO0bt06tW7dWqNHj1ZmZqZatPhfuevXr9fUqVO1detWRUREaMaMGRozZsyZPp1zSmhrL/mXfyXtIRfj7PEv/0qhrb3MLgMAAMAUZ2UVvt/85jd67733/neQE4LPlClTtHr1ar322msKDAzUxIkTNXToUP33v/+VJNntdg0aNEihoaHatGmTSktLdeutt6ply5aaM2eOJGnnzp0aNGiQ7rrrLr344ovKzc3VuHHjFBYWppSUlLNxSueEO+N9FLvxTmmj2ZWgOYvVT/+tAQAAeKKzEqBatGih0NDQk9orKir07LPPasWKFRowYIAk6bnnnlNsbKw++OAD9enTR//5z3/05Zdf6r333lNISIh69eqlRx99VNOnT9esWbPk4+OjpUuXKioqSgsWLJD009Ld77//vp544gmPDlB/LajR72cuU2xMjNmloBnbVlSkvy4YqevMLgQAAMAEZyVAFRcXKzw8XH5+fkpMTFRmZqY6d+6sgoICHTt2TMnJya6xMTEx6ty5s/Lz89WnTx/l5+crLi7O7ZK+lJQUTZgwQVu3btXFF1+s/Px8t33Ujpk8efIv1lVdXa3q6mrXe5vNdmZOuIkoO+RUVdAFUngvs0tBM1ZV5lDZIafZZeAXcDkvGgOX8wLwVGc8QCUkJGjZsmXq3r27SktLNXv2bCUlJamwsFBlZWXy8fFRUFCQ2zYhISEqKyuTJJWVlbmFp9r+2r5fGmOz2VRVVSV/f/86a8vMzDzp/iwAaG64nBeNgct5AXiqMx6grrnmGte/X3jhhUpISFCXLl306quvnjLYNJaMjAxNnTrV9d5msykiIsLEigDgzONyXjQGLucF4KnOyiV8JwoKCtIFF1ygHTt26He/+51qampUXl7uNgu1d+9e1z1ToaGh+vDDD932sXfvXldf7T9r204cY7VafzGk+fr6ytfX90ycFgA0WVzOi8bA5bxNW3FxsSorK80u45yxbds2t3/CuDZt2qhbt25ml9GoznqAOnTokL7++mvdcsstio+PV8uWLZWbm6thw4ZJkrZv365du3YpMTFRkpSYmKg//elP2rdvn4KDgyVJOTk5slqt6tGjh2vM22+/7XacnJwc1z4AAAA8VXFxsS644AKzyzgnjRo1yuwSzklfffWVR4WoMx6g7r33Xg0ZMkRdunTRnj179PDDD8tiseimm25SYGCgxo4dq6lTp6pdu3ayWq2aNGmSEhMT1adPH0nSwIED1aNHD91yyy2aO3euysrKNGPGDKWnp7tmj+666y4tWrRI999/v26//XatXbtWr776qlavXn2mTwcAAOCcUjvztHz5csXGxppczbmhqqpKJSUlioyMNP2Wk3PJtm3bNGrUKI+b7TzjAeq7777TTTfdpAMHDqhjx4664oor9MEHH6hjx46SpCeeeELe3t4aNmyY24N0a1ksFmVnZ2vChAlKTExUq1atNHr0aD3yyCOuMVFRUVq9erWmTJmiJ598Up06ddI//vEPj17CHAAA4ESxsbHq3bu32WWcMy6//HKzS8A54owHqJdffvkX+/38/LR48WItXrz4lGO6dOly0iV6P9evXz99+umnDaoRAAAAABqCh4QAAAAAgEEEKAAAAAAwiAAFAAAAAAYRoAAAAADAoLP+HCg0jiNHjkiSPvnkE5MrObewbGn98ZBBAADgyQhQzURRUZEkafz48SZXAk/Rpk0bs0tAHfgxpf74IaVh+DGlaQtt7SX/8q+kPVxshLPHv/wrhbb2MruMRkeAaiZSU1MlSTExMQoICDC3mHNI7QPgeNhg/bRp08ajnjh+LuHHFDQ2fkxpmu6M91HsxjuljWZXguYsVj/9t+ZpCFDNRIcOHTRu3Dizyzhn8bBBNBf8mFJ//JDScPyY0nT9taBG/9fe/YVWXTdgAH82IzdqmxR5cWwXIb35XkRGlBEUXnVhTI2IN0SibkLYIKIIqaVhlBfxhhUUXoxeSKSILKEiCiPDiyZoBNYUwotiKUSQm9qGtvNevDiIsPfr0fPHcz4f2M2R33i8eXae32/nu39t+k/+uWxZs6PQxiYOH872f6/L6mYHaTADCqCNuJlSOzdSaCfHT1bz+6J/JJXlzY5CG/v9+FyOn6w2O0bD+cVYAACAQgYUAABAIb/CBwDQRpzGeeGcxlmbTj2N04ACAGgjTuOk0TrtNE4DCgCgjTiN88I5jbN2nXgapwEFANBGnMZZO6dxUsIhEgAAAIUMKAAAgEIGFAAAQCGfgQIAoCFOnz49f0pgKzl3HHcrH8vtUJDWYUBRd61alonChEbRAxdHD9AuDh8+nNtuu63ZMc5r/fr1zY5wXgcOHHDARYvoqlar1WaHaJapqakMDAzkxIkT6e/vb3actnXw4MGWLstWpzBpB3rg4ugB2kWr3ky5HP6Qrhsp9Ve6DQwoA6ruWrUsE4UJjaIHLo4eAKg/A6qAAQUAACTl28ApfAAAAIUMKAAAgEIGFAAAQCEDCgAAoJABBQAAUMiAAgAAKGRAAQAAFDKgAAAAChlQAAAAhQwoAACAQgYUAABAIQMKAACg0BXNDtBM1Wo1STI1NdXkJAAAQDOd2wTnNsL5dPSAmp6eTpIMDg42OQkAANAKpqenMzAwcN5/76r+v4nVxubm5vLzzz+nr68vXV1dzY5DE0xNTWVwcDA//fRT+vv7mx0HaAI9AOgBkv89eZqenk6lUkl39/k/6dTRT6C6u7tz/fXXNzsGLaC/v19hQofTA4Ae4O+ePJ3jEAkAAIBCBhQAAEAhA4qOtnDhwmzevDkLFy5sdhSgSfQAoAe4EB19iAQAAMCF8AQKAACgkAEFAABQyIACAAAoZEABAAAUMqAAAAAKGVC0ra1bt+b2229PX19fFi9enLVr1+bIkSN/e83KlSvT1dX1l6/77ruvQamBS6mWHkiSbdu25aabbkpvb28GBwfzxBNPZGZmpgGJgUutlh44c+ZMtmzZkqVLl6anpye33HJLPv300wYlptUZULStvXv3Znh4OF9//XU+//zznDlzJvfee29OnTp13mt27dqVY8eOzX8dOnQoCxYsyIMPPtjA5MClUksP7Ny5Mxs3bszmzZszMTGRsbGxvPvuu3nmmWcamBy4VGrpgdHR0Wzfvj2vv/56vv/++2zYsCH3339/vvnmmwYmp1X5O1B0jF9++SWLFy/O3r17c8899xRds23btmzatCnHjh3LVVddVeeEQL2V9MDIyEgmJiayZ8+e+deefPLJjI+PZ9++fY2KCtRJSQ9UKpU8++yzGR4enn/tgQceSG9vb3bs2NGoqLQoT6DoGCdOnEiSXHPNNcXXjI2N5aGHHjKeoE2U9MBdd92VAwcOZP/+/UmSo0eP5pNPPsmqVasakhGor5IemJ2dTU9Pz59e6+3tdROFJJ5A0SHm5uayevXq/Pbbb8Xlt3///qxYsSLj4+O544476pwQqLcL6YHXXnstTz31VKrVas6ePZsNGzbkzTffbFBSoF5Ke2DdunX59ttv8+GHH2bp0qXZs2dP1qxZkz/++COzs7MNTEwr8gSKjjA8PJxDhw7lnXfeKb5mbGwsN998s/EEbaK0B7788su89NJLeeONN3Lw4MHs2rUrH3/8cV544YUGJQXqpbQHXn311dx4441ZtmxZrrzyyoyMjOTRRx9Nd7e3zngCRQcYGRnJ7t2789VXX+WGG24ouubUqVOpVCrZsmVLHn/88TonBOrtQnrg7rvvzp133pmXX355/rUdO3bksccey8mTJ72BgstULe8HZmZm8uuvv6ZSqWTjxo356KOP8t1339U5Ka3OTwHaVrVazcjISD744IN88cUXxWWZJO+9915mZ2ezfv36OiYE6q2WHjh9+vRfRtKCBQvmvx9webmY9wM9PT1ZsmRJzp49m/fffz9r1qypY1IuF1c0OwDUy/DwcHbu3Jndu3enr68vx48fT5IMDAykt7c3SfLwww9nyZIl2bp165+uHRsby9q1a3Pttdc2PDdw6dTSA0NDQ3nllVdy6623ZsWKFfnhhx/y3HPPZWhoaH5IAZePWnpgfHw8k5OTWb58eSYnJ/P8889nbm4uTz/9dNP+H7QOA4q2de4D3ytXrvzT62+99VYeeeSRJMmPP/74lzvNR44cyb59+/LZZ581IiZQR7X0wOjoaLq6ujI6OprJyclcd911GRoayosvvtio2MAlVEsPzMzMZHR0NEePHs3VV1+dVatW5e23386iRYsalJpW5jNQAAAAhXwGCgAAoJABBQAAUMiAAgAAKGRAAQAAFDKgAAAAChlQAAAAhQwoAACAQgYUAABAIQMKAACgkAEFAABQyIACAAAo9F+UW7DbdNv4owAAAABJRU5ErkJggg==", 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", 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" } ], "source": [ @@ -700,8 +118,8 @@ " cols_to_remove = [\n", " \"done\", \"training_iteration\", \"trial_id\", \"date\",\n", " \"timestamp\", \"pid\", \"hostname\", \"node_ip\", \"time_since_restore\",\n", - " \"time_total_s\", \"iterations_since_restore\"\n", - " ] \n", + " \"time_total_s\", \"iterations_since_restore\",\n", + " ]\n", " return pd.read_csv(filename).drop(columns=cols_to_remove)\n", "\n", "def calculate_stats(df):\n", @@ -709,13 +127,19 @@ " # count, mean, median, mode, range, variance, standard deviation\n", " stats = {}\n", " df = df[df['minimum'] != 9e99]\n", - " stats['count'] = df.count()\n", - " stats['mean'] = df.mean()\n", - " stats['median'] = df.median()\n", - " stats['mode'] = df.mode().iloc[0]\n", - " stats['range'] = df.max() - df.min()\n", - " stats['variance'] = df.var()\n", - " stats['std'] = df.std()\n", + " stats['count'] = df['minimum'].count()\n", + " stats['qor_mean'] = df['minimum'].mean()\n", + " stats['qor_median'] = df['minimum'].median()\n", + " stats['qor_range'] = df['minimum'].max() - df['minimum'].min()\n", + " stats['qor_variance'] = df['minimum'].var()\n", + " stats['qor_std'] = df['minimum'].std()\n", + " stats['qor_q1'] = df['minimum'].quantile(0.25)\n", + " stats['time_this_iter_s_mean'] = df['time_this_iter_s'].mean()\n", + " stats['time_this_iter_s_median'] = df['time_this_iter_s'].median()\n", + " stats['time_this_iter_s_range'] = df['time_this_iter_s'].max() - df['time_this_iter_s'].min()\n", + " stats['time_this_iter_s_variance'] = df['time_this_iter_s'].var()\n", + " stats['time_this_iter_s_std'] = df['time_this_iter_s'].std()\n", + " stats['time_this_iter_s_q1'] = df['time_this_iter_s'].quantile(0.25)\n", " return stats, df\n", "\n", "def plot(df_list, title):\n", @@ -736,28 +160,153 @@ "df_list = []\n", "\n", "# Generate all the plots for the following matrix:\n", - "# ray27, ray28, ray29\n", - "# gcd, aes, ibex\n", - "# asap7, sky130hd, ihp-sg13g2\n", - "# Independent variable is the Ray version. \n", - "# Dependent variable is the minimum and time_this_iter_s\n", - "# For each of the 3 Ray versions, we have 3 different GCDs\n", - "\n", + "DATE = \"20240730\"\n", "for design in ['gcd', 'aes', 'ibex']:\n", " for platform in ['asap7', 'sky130hd', 'ihp-sg13g2']:\n", " df_list = []\n", - " plt.figure()\n", + " q1_list = {}\n", + " # plt.figure()\n", " for ray_version in ['ray27', 'ray28', 'ray29']:\n", - " filename = f\"{ray_version}-{design}-{platform}.csv\"\n", + " filename = f\"{DATE}/{ray_version}-{design}-{platform}.csv\"\n", " df = load_df(filename)\n", " stats, df = calculate_stats(df)\n", " print(f\"Stats for {filename}\")\n", " print(stats)\n", " df_list.append(df)\n", - " plot(df_list, title=f\"{design} {platform}\")\n", + " q1_list[ray_version] = stats['qor_q1']\n", + " # plot(df_list, f\"{design} {platform}\")\n", + " print(\"-------------------\")\n", + " print(f\"Q1 for {design} {platform} {q1_list}\")\n", + " print(f\"Maximum Q1 value: {max(q1_list.values())}\")\n", + " print(\"-------------------\")\n", " " ] }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Stats for 20240809/ray27-gcd-asap7.csv\n", + "{'count': 41, 'qor_mean': 46249.361024390244, 'qor_median': 48524.96000000001, 'qor_range': 23917.25, 'qor_variance': 69339029.04619217, 'qor_std': 8327.00600733494, 'qor_q1': 37668.29, 'time_this_iter_s_mean': 131.02429841785897, 'time_this_iter_s_median': 131.36773920059204, 'time_this_iter_s_range': 40.33270788192749, 'time_this_iter_s_variance': 92.62936265883744, 'time_this_iter_s_std': 9.624414925533783, 'time_this_iter_s_q1': 123.78145623207092}\n", + "Stats for 20240809/ray28-gcd-asap7.csv\n", + "{'count': 43, 'qor_mean': 44209.70265348837, 'qor_median': 44253.729, 'qor_range': 25638.65, 'qor_variance': 75373790.11152509, 'qor_std': 8681.80799784959, 'qor_q1': 35914.255000000005, 'time_this_iter_s_mean': 134.52496968868167, 'time_this_iter_s_median': 133.40503215789795, 'time_this_iter_s_range': 47.48045492172241, 'time_this_iter_s_variance': 108.49322833075547, 'time_this_iter_s_std': 10.416008272402411, 'time_this_iter_s_q1': 128.58220982551575}\n", + "Stats for 20240809/ray29-gcd-asap7.csv\n", + "{'count': 46, 'qor_mean': 46202.256586956515, 'qor_median': 48899.378, 'qor_range': 23370.060000000005, 'qor_variance': 68360667.3659331, 'qor_std': 8268.051001652875, 'qor_q1': 37378.94, 'time_this_iter_s_mean': 133.539592774018, 'time_this_iter_s_median': 132.09797322750092, 'time_this_iter_s_range': 71.28152918815609, 'time_this_iter_s_variance': 183.60254263168798, 'time_this_iter_s_std': 13.550001573124927, 'time_this_iter_s_q1': 123.57363653182983}\n", + "-------------------\n", + "Q1 for gcd asap7 {'ray27': 37668.29, 'ray28': 35914.255000000005, 'ray29': 37378.94}\n", + "Maximum Q1 value: 37668.29\n", + "-------------------\n", + "Stats for 20240809/ray27-gcd-sky130hd.csv\n", + "{'count': 100, 'qor_mean': 338.47373227, 'qor_median': 334.89486, 'qor_range': 61.978260000000034, 'qor_variance': 227.261257398984, 'qor_std': 15.075186811412454, 'qor_q1': 326.61603925000003, 'time_this_iter_s_mean': 104.98445526123047, 'time_this_iter_s_median': 103.79444694519043, 'time_this_iter_s_range': 94.07212495803833, 'time_this_iter_s_variance': 168.9802552979102, 'time_this_iter_s_std': 12.999240566198866, 'time_this_iter_s_q1': 96.83641064167023}\n", + "Stats for 20240809/ray28-gcd-sky130hd.csv\n", + "{'count': 100, 'qor_mean': 334.088899934, 'qor_median': 331.19696500000003, 'qor_range': 56.470399999999984, 'qor_variance': 159.17767038067802, 'qor_std': 12.61656333478646, 'qor_q1': 324.34999250000004, 'time_this_iter_s_mean': 101.96030424833297, 'time_this_iter_s_median': 103.07414209842682, 'time_this_iter_s_range': 49.373416900634766, 'time_this_iter_s_variance': 137.39286960296553, 'time_this_iter_s_std': 11.721470453956087, 'time_this_iter_s_q1': 92.03462594747542}\n", + "Stats for 20240809/ray29-gcd-sky130hd.csv\n", + "{'count': 100, 'qor_mean': 339.2731028890001, 'qor_median': 334.606484, 'qor_range': 58.205600000000004, 'qor_variance': 239.86490174849789, 'qor_std': 15.487572493728573, 'qor_q1': 327.02252500000003, 'time_this_iter_s_mean': 107.82720205783843, 'time_this_iter_s_median': 107.34496915340424, 'time_this_iter_s_range': 55.69068741798401, 'time_this_iter_s_variance': 116.58110932348629, 'time_this_iter_s_std': 10.79727323556676, 'time_this_iter_s_q1': 101.82685959339142}\n", + "-------------------\n", + "Q1 for gcd sky130hd {'ray27': 326.61603925000003, 'ray28': 324.34999250000004, 'ray29': 327.02252500000003}\n", + "Maximum Q1 value: 327.02252500000003\n", + "-------------------\n", + "Stats for 20240809/ray27-gcd-ihp-sg13g2.csv\n", + "{'count': 98, 'qor_mean': 269.94140431632655, 'qor_median': 261.83805, 'qor_range': 112.59190000000004, 'qor_variance': 1019.015429778857, 'qor_std': 31.92202107916817, 'qor_q1': 245.06835, 'time_this_iter_s_mean': 143.10986271683052, 'time_this_iter_s_median': 138.1268949508667, 'time_this_iter_s_range': 116.236120223999, 'time_this_iter_s_variance': 564.1420429519377, 'time_this_iter_s_std': 23.75167452942924, 'time_this_iter_s_q1': 125.38361847400665}\n", + "Stats for 20240809/ray28-gcd-ihp-sg13g2.csv\n", + "{'count': 97, 'qor_mean': 284.19232731958766, 'qor_median': 272.1906, 'qor_range': 131.3913, 'qor_variance': 1456.5989881484304, 'qor_std': 38.1654161270178, 'qor_q1': 251.1022, 'time_this_iter_s_mean': 158.15124891713722, 'time_this_iter_s_median': 163.81208658218384, 'time_this_iter_s_range': 128.07702231407166, 'time_this_iter_s_variance': 751.0716304531371, 'time_this_iter_s_std': 27.40568609710651, 'time_this_iter_s_q1': 140.56542921066284}\n", + "Stats for 20240809/ray29-gcd-ihp-sg13g2.csv\n", + "{'count': 99, 'qor_mean': 279.2113753838384, 'qor_median': 267.6143, 'qor_range': 111.8474, 'qor_variance': 1170.1305513058228, 'qor_std': 34.207171050904265, 'qor_q1': 249.00245, 'time_this_iter_s_mean': 144.79751235788518, 'time_this_iter_s_median': 136.61038208007812, 'time_this_iter_s_range': 153.79870295524594, 'time_this_iter_s_variance': 1094.8243699600077, 'time_this_iter_s_std': 33.08813034851029, 'time_this_iter_s_q1': 121.80710411071777}\n", + "-------------------\n", + "Q1 for gcd ihp-sg13g2 {'ray27': 245.06835, 'ray28': 251.1022, 'ray29': 249.00245}\n", + "Maximum Q1 value: 251.1022\n", + "-------------------\n", + "Stats for 20240809/ray27-aes-asap7.csv\n", + "{'count': 83, 'qor_mean': 75375.9938554217, 'qor_median': 73446.85999999999, 'qor_range': 47269.150000000016, 'qor_variance': 85129092.19667521, 'qor_std': 9226.542808477898, 'qor_q1': 69640.815, 'time_this_iter_s_mean': 4216.010735172823, 'time_this_iter_s_median': 3777.794238567352, 'time_this_iter_s_range': 6232.855261087419, 'time_this_iter_s_variance': 2042548.0665361015, 'time_this_iter_s_std': 1429.177409049031, 'time_this_iter_s_q1': 3354.0642923116684}\n", + "Stats for 20240809/ray28-aes-asap7.csv\n", + "{'count': 85, 'qor_mean': 75814.26721882352, 'qor_median': 75428.12, 'qor_range': 44278.240000000005, 'qor_variance': 50876051.49645986, 'qor_std': 7132.7450183263845, 'qor_q1': 70934.14, 'time_this_iter_s_mean': 4145.446913138558, 'time_this_iter_s_median': 3721.46470284462, 'time_this_iter_s_range': 5018.214689731597, 'time_this_iter_s_variance': 1271328.4055839055, 'time_this_iter_s_std': 1127.5319975876098, 'time_this_iter_s_q1': 3405.216753721237}\n", + "Stats for 20240809/ray29-aes-asap7.csv\n", + "{'count': 84, 'qor_mean': 75149.43821428569, 'qor_median': 73046.425, 'qor_range': 39901.88, 'qor_variance': 75929110.6846245, 'qor_std': 8713.731157467764, 'qor_q1': 68993.1525, 'time_this_iter_s_mean': 3871.6794871290526, 'time_this_iter_s_median': 3400.308669447899, 'time_this_iter_s_range': 5083.299695014954, 'time_this_iter_s_variance': 1486540.0995899606, 'time_this_iter_s_std': 1219.2375074570011, 'time_this_iter_s_q1': 3114.129406809807}\n", + "-------------------\n", + "Q1 for aes asap7 {'ray27': 69640.815, 'ray28': 70934.14, 'ray29': 68993.1525}\n", + "Maximum Q1 value: 70934.14\n", + "-------------------\n", + "Stats for 20240809/ray27-aes-sky130hd.csv\n", + "{'count': 99, 'qor_mean': 569.8513546666666, 'qor_median': 567.48947, 'qor_range': 144.69225, 'qor_variance': 1020.1758596750873, 'qor_std': 31.940191916691536, 'qor_q1': 546.4332, 'time_this_iter_s_mean': 3154.836308460043, 'time_this_iter_s_median': 3145.811172246933, 'time_this_iter_s_range': 3453.280466556549, 'time_this_iter_s_variance': 780481.5035293029, 'time_this_iter_s_std': 883.4486422703376, 'time_this_iter_s_q1': 2370.3216873407364}\n", + "Stats for 20240809/ray28-aes-sky130hd.csv\n", + "{'count': 100, 'qor_mean': 558.2712890299998, 'qor_median': 555.52805, 'qor_range': 137.92677000000003, 'qor_variance': 1110.9069157596539, 'qor_std': 33.33027026232541, 'qor_q1': 533.022525, 'time_this_iter_s_mean': 3104.4407084965706, 'time_this_iter_s_median': 2762.7178295850754, 'time_this_iter_s_range': 4344.091899633408, 'time_this_iter_s_variance': 1046121.6846570042, 'time_this_iter_s_std': 1022.8009017677899, 'time_this_iter_s_q1': 2350.5376983284955}\n", + "Stats for 20240809/ray29-aes-sky130hd.csv\n", + "{'count': 100, 'qor_mean': 569.66596748, 'qor_median': 564.34881, 'qor_range': 167.64053400000006, 'qor_variance': 1566.1683454874187, 'qor_std': 39.574844857401764, 'qor_q1': 541.96505, 'time_this_iter_s_mean': 3233.001205983162, 'time_this_iter_s_median': 2890.620113015175, 'time_this_iter_s_range': 3909.561240673065, 'time_this_iter_s_variance': 1084179.5678440414, 'time_this_iter_s_std': 1041.2394382869106, 'time_this_iter_s_q1': 2338.5571151971817}\n", + "-------------------\n", + "Q1 for aes sky130hd {'ray27': 546.4332, 'ray28': 533.022525, 'ray29': 541.96505}\n", + "Maximum Q1 value: 546.4332\n", + "-------------------\n", + "Stats for 20240809/ray27-aes-ihp-sg13g2.csv\n", + "{'count': 65, 'qor_mean': 594.6867072153846, 'qor_median': 576.9225, 'qor_range': 306.29060000000004, 'qor_variance': 4561.397026989331, 'qor_std': 67.53811536450607, 'qor_q1': 544.8348, 'time_this_iter_s_mean': 7113.224942449423, 'time_this_iter_s_median': 6838.318456172943, 'time_this_iter_s_range': 11479.967837572096, 'time_this_iter_s_variance': 5336602.919691944, 'time_this_iter_s_std': 2310.108854511394, 'time_this_iter_s_q1': 5511.647229909897}\n", + "Stats for 20240809/ray28-aes-ihp-sg13g2.csv\n", + "{'count': 77, 'qor_mean': 567.4996147116883, 'qor_median': 554.964, 'qor_range': 405.5096999999998, 'qor_variance': 3246.1558684830993, 'qor_std': 56.9750460156295, 'qor_q1': 532.6742, 'time_this_iter_s_mean': 6635.355656676478, 'time_this_iter_s_median': 6644.341965436935, 'time_this_iter_s_range': 9812.30588054657, 'time_this_iter_s_variance': 4008479.7911553443, 'time_this_iter_s_std': 2002.1188254335316, 'time_this_iter_s_q1': 4979.509278535843}\n", + "Stats for 20240809/ray29-aes-ihp-sg13g2.csv\n", + "{'count': 62, 'qor_mean': 580.7765411838709, 'qor_median': 568.660675, 'qor_range': 348.62080000000003, 'qor_variance': 3987.190246200032, 'qor_std': 63.14420199986719, 'qor_q1': 532.5684249999999, 'time_this_iter_s_mean': 7393.647945938572, 'time_this_iter_s_median': 7201.622696280479, 'time_this_iter_s_range': 9818.939694404604, 'time_this_iter_s_variance': 3885870.1354138413, 'time_this_iter_s_std': 1971.2610520714504, 'time_this_iter_s_q1': 6286.900694906712}\n", + "-------------------\n", + "Q1 for aes ihp-sg13g2 {'ray27': 544.8348, 'ray28': 532.6742, 'ray29': 532.5684249999999}\n", + "Maximum Q1 value: 544.8348\n", + "-------------------\n", + "Stats for 20240809/ray27-ibex-asap7.csv\n", + "{'count': 94, 'qor_mean': 210063.20297872342, 'qor_median': 209426.235, 'qor_range': 35125.48999999999, 'qor_variance': 40253678.55189426, 'qor_std': 6344.57867410392, 'qor_q1': 206067.8075, 'time_this_iter_s_mean': 3865.230781425821, 'time_this_iter_s_median': 3738.2693178653717, 'time_this_iter_s_range': 2001.105250120163, 'time_this_iter_s_variance': 244665.94511392745, 'time_this_iter_s_std': 494.6371853327724, 'time_this_iter_s_q1': 3452.253939449787}\n", + "Stats for 20240809/ray28-ibex-asap7.csv\n", + "{'count': 89, 'qor_mean': 209008.57483146063, 'qor_median': 208032.11, 'qor_range': 45649.350000000035, 'qor_variance': 58769565.809361644, 'qor_std': 7666.131084801619, 'qor_q1': 203962.0, 'time_this_iter_s_mean': 3666.686477752214, 'time_this_iter_s_median': 3675.053591966629, 'time_this_iter_s_range': 1792.888142824173, 'time_this_iter_s_variance': 182451.14883250985, 'time_this_iter_s_std': 427.14300747233335, 'time_this_iter_s_q1': 3455.4904642105103}\n", + "Stats for 20240809/ray29-ibex-asap7.csv\n", + "{'count': 93, 'qor_mean': 210199.9249462366, 'qor_median': 209132.29, 'qor_range': 30955.47000000003, 'qor_variance': 41771051.591286175, 'qor_std': 6463.052807403493, 'qor_q1': 205952.23, 'time_this_iter_s_mean': 3572.009611719398, 'time_this_iter_s_median': 3552.6238646507263, 'time_this_iter_s_range': 1947.2108659744263, 'time_this_iter_s_variance': 159817.45025915396, 'time_this_iter_s_std': 399.7717477000519, 'time_this_iter_s_q1': 3323.666220188141}\n", + "-------------------\n", + "Q1 for ibex asap7 {'ray27': 206067.8075, 'ray28': 203962.0, 'ray29': 205952.23}\n", + "Maximum Q1 value: 206067.8075\n", + "-------------------\n", + "Stats for 20240809/ray27-ibex-sky130hd.csv\n", + "{'count': 100, 'qor_mean': 1470.1593188800002, 'qor_median': 1455.993285, 'qor_range': 186.93090000000007, 'qor_variance': 2335.4398007540635, 'qor_std': 48.326388244457746, 'qor_q1': 1435.641025, 'time_this_iter_s_mean': 4289.420304288864, 'time_this_iter_s_median': 3641.345679283142, 'time_this_iter_s_range': 8025.56929397583, 'time_this_iter_s_variance': 2589964.597515787, 'time_this_iter_s_std': 1609.336694888856, 'time_this_iter_s_q1': 3126.1362833976746}\n", + "Stats for 20240809/ray28-ibex-sky130hd.csv\n", + "{'count': 100, 'qor_mean': 1475.8486648500004, 'qor_median': 1473.2482, 'qor_range': 228.66830000000004, 'qor_variance': 3109.138718797844, 'qor_std': 55.75965135111449, 'qor_q1': 1429.8954749999998, 'time_this_iter_s_mean': 3737.1537130403517, 'time_this_iter_s_median': 3283.1477369070053, 'time_this_iter_s_range': 14665.375083208084, 'time_this_iter_s_variance': 3048950.8927596835, 'time_this_iter_s_std': 1746.1245352951444, 'time_this_iter_s_q1': 2751.3125768899918}\n", + "Stats for 20240809/ray29-ibex-sky130hd.csv\n", + "{'count': 99, 'qor_mean': 1479.0990852525254, 'qor_median': 1484.6584, 'qor_range': 221.6905999999999, 'qor_variance': 2799.9127620327363, 'qor_std': 52.914201893562904, 'qor_q1': 1439.7591499999999, 'time_this_iter_s_mean': 3510.5403692963146, 'time_this_iter_s_median': 3127.4683861732483, 'time_this_iter_s_range': 8119.471207618712, 'time_this_iter_s_variance': 2185041.643285548, 'time_this_iter_s_std': 1478.1886358937913, 'time_this_iter_s_q1': 2374.216277360916}\n", + "-------------------\n", + "Q1 for ibex sky130hd {'ray27': 1435.641025, 'ray28': 1429.8954749999998, 'ray29': 1439.7591499999999}\n", + "Maximum Q1 value: 1439.7591499999999\n", + "-------------------\n", + "Stats for 20240809/ray27-ibex-ihp-sg13g2.csv\n", + "{'count': 82, 'qor_mean': 1497.537889207317, 'qor_median': 1500.57395, 'qor_range': 417.001, 'qor_variance': 6758.812867399577, 'qor_std': 82.2119995341287, 'qor_q1': 1432.3829999999998, 'time_this_iter_s_mean': 6830.817105950378, 'time_this_iter_s_median': 7472.989594817162, 'time_this_iter_s_range': 7052.46266579628, 'time_this_iter_s_variance': 4036738.0755477725, 'time_this_iter_s_std': 2009.1635263332282, 'time_this_iter_s_q1': 4650.432884931564}\n", + "Stats for 20240809/ray28-ibex-ihp-sg13g2.csv\n", + "{'count': 100, 'qor_mean': 1487.8273682999998, 'qor_median': 1463.68495, 'qor_range': 484.65999999999985, 'qor_variance': 9238.07645367855, 'qor_std': 96.11491275384142, 'qor_q1': 1431.4724999999999, 'time_this_iter_s_mean': 6644.881909101009, 'time_this_iter_s_median': 6126.311794757843, 'time_this_iter_s_range': 8513.875883817671, 'time_this_iter_s_variance': 3157428.8207010673, 'time_this_iter_s_std': 1776.9155356125027, 'time_this_iter_s_q1': 5236.626863181591}\n", + "Stats for 20240809/ray29-ibex-ihp-sg13g2.csv\n", + "{'count': 87, 'qor_mean': 1508.1076131954023, 'qor_median': 1506.9352, 'qor_range': 470.34299999999985, 'qor_variance': 8224.943031788647, 'qor_std': 90.69147165962545, 'qor_q1': 1435.1086, 'time_this_iter_s_mean': 6324.080235927954, 'time_this_iter_s_median': 5922.613965034485, 'time_this_iter_s_range': 10108.984694004059, 'time_this_iter_s_variance': 4388173.736748339, 'time_this_iter_s_std': 2094.7968246940654, 'time_this_iter_s_q1': 4643.203210473061}\n", + "-------------------\n", + "Q1 for ibex ihp-sg13g2 {'ray27': 1432.3829999999998, 'ray28': 1431.4724999999999, 'ray29': 1435.1086}\n", + "Maximum Q1 value: 1435.1086\n", + "-------------------\n" + ] + } + ], + "source": [ + "# Update: 20240809\n", + "DATE=\"20240809\"\n", + "for design in ['gcd', 'aes', 'ibex']:\n", + " for platform in ['asap7', 'sky130hd', 'ihp-sg13g2']:\n", + " df_list = []\n", + " q1_list = {}\n", + " # plt.figure()\n", + " for ray_version in ['ray27', 'ray28', 'ray29']:\n", + " filename = f\"{DATE}/{ray_version}-{design}-{platform}.csv\"\n", + " df = load_df(filename)\n", + " stats, df = calculate_stats(df)\n", + " print(f\"Stats for {filename}\")\n", + " print(stats)\n", + " df_list.append(df)\n", + " q1_list[ray_version] = stats['qor_q1']\n", + " # plot(df_list, f\"{design} {platform}\")\n", + " print(\"-------------------\")\n", + " print(f\"Q1 for {design} {platform} {q1_list}\")\n", + " print(f\"Maximum Q1 value: {max(q1_list.values())}\")\n", + " print(\"-------------------\")" + ] + }, { "cell_type": "code", "execution_count": null, diff --git a/tools/AutoTuner/test/regression_tune_base.py b/tools/AutoTuner/test/regression_tune_base.py new file mode 100644 index 0000000000..e3d4f08880 --- /dev/null +++ b/tools/AutoTuner/test/regression_tune_base.py @@ -0,0 +1,72 @@ +import unittest +import subprocess +import os +import json +import pandas as pd +import glob + +cur_dir = os.path.dirname(os.path.abspath(__file__)) +src_dir = os.path.join(cur_dir, "../src/autotuner") +os.chdir(src_dir) + + +def get_latest_date(path): + return max(glob.glob(f"{path}/*"), key=os.path.getmtime) + +def combine_csv(path): + df = pd.concat([pd.read_csv(fname) for fname in glob.glob(f"{path}/*/progress.csv")]) + df.to_csv(f"{path}/progress_overall.csv", index=False) + +def load_df(filename): + df = pd.read_csv(filename) + cols_to_remove = [ + "done", "training_iteration", "trial_id", "date", + "timestamp", "pid", "hostname", "node_ip", "time_since_restore", + "time_total_s", "iterations_since_restore", + ] + df = df[df['minimum'] != 9e99] + df = df.drop(columns=cols_to_remove) + return df + +class BaseTuneRegressionBaseTest(unittest.TestCase): + platform = "" + design = "" + qor = 0 + CONFIDENCE_INTERVAL = 0.05 + + def setUp(self): + self.config = os.path.join( + cur_dir, + f"../../../flow/designs/{self.platform}/{self.design}/autotuner.json", + ) + self.experiment = f"smoke-test-tune-{self.platform}" + self.command = ( + "python3 distributed.py" + f" --design {self.design}" + f" --platform {self.platform}" + f" --experiment {self.experiment}" + f" --config {self.config}" + f" tune --samples 10" + ) + + +class ASAP7TuneRegressionBaseTest(BaseTuneRegressionBaseTest): + platform = "asap7" + design = "gcd" + qor = 37668.29 + + def test_tune(self): + # out = subprocess.run(self.command, shell=True, check=True) + # successful = out.returncode == 0 + # self.assertTrue(successful) + + # check if the final mean QoR is within 1% of the expected value + latest_path = get_latest_date(f"../../../../flow/logs/{self.platform}/{self.design}") + combine_csv(latest_path) + df = load_df(f"{latest_path}/progress_overall.csv") + mean_qor = df["minimum"].mean() + self.assertLess(abs(mean_qor - self.qor) / self.qor, self.CONFIDENCE_INTERVAL) + + +if __name__ == "__main__": + unittest.main()