1c87d2d20SMatthew G Knepley#!/usr/bin/env python 2c87d2d20SMatthew G Knepleyimport os 3c87d2d20SMatthew G Knepleyfrom benchmarkExample import PETScExample 4c87d2d20SMatthew G Knepley 5c87d2d20SMatthew G Knepleydef processSummary(moduleName, times, events): 6c87d2d20SMatthew G Knepley '''Process the Python log summary into plot data''' 7c87d2d20SMatthew G Knepley m = __import__(moduleName) 8c87d2d20SMatthew G Knepley reload(m) 9c87d2d20SMatthew G Knepley # Total Time 10c87d2d20SMatthew G Knepley times.append(m.Time[0]) 11c87d2d20SMatthew G Knepley # Common events 12c87d2d20SMatthew G Knepley # Add the time and flop rate 13c87d2d20SMatthew G Knepley for name in ['MatCUSPSetValBch', 'ElemAssembly']: 14c87d2d20SMatthew G Knepley if not name in events: 15c87d2d20SMatthew G Knepley events[name] = [] 16c87d2d20SMatthew G Knepley events[name].append((m.Main_Stage.event[name].Time[0], m.Main_Stage.event[name].Flops[0]/(m.Main_Stage.event[name].Time[0] * 1e6))) 17c87d2d20SMatthew G Knepley return 18c87d2d20SMatthew G Knepley 19c87d2d20SMatthew G Knepleydef plotSummary(library, num, sizes, times, events): 20c87d2d20SMatthew G Knepley from pylab import legend, plot, show, title, xlabel, ylabel 21c87d2d20SMatthew G Knepley import numpy as np 22c87d2d20SMatthew G Knepley showEventTime = True 23c87d2d20SMatthew G Knepley print events 24c87d2d20SMatthew G Knepley if showEventTime: 25c87d2d20SMatthew G Knepley data = [] 26c87d2d20SMatthew G Knepley names = [] 27c87d2d20SMatthew G Knepley for event, style in [('MatCUSPSetValBch', 'b-'), ('ElemAssembly', 'b:')]: 28c87d2d20SMatthew G Knepley names.append(event) 29c87d2d20SMatthew G Knepley data.append(sizes) 30c87d2d20SMatthew G Knepley data.append(np.array(events[event])[:,0]) 31c87d2d20SMatthew G Knepley data.append(style) 32c87d2d20SMatthew G Knepley plot(*data) 33c87d2d20SMatthew G Knepley title('Performance on '+library+' Example '+str(num)) 34c87d2d20SMatthew G Knepley xlabel('Number of Dof') 35c87d2d20SMatthew G Knepley ylabel('Time (s)') 36c87d2d20SMatthew G Knepley legend(names, 'upper left', shadow = True) 37c87d2d20SMatthew G Knepley show() 38c87d2d20SMatthew G Knepley return 39c87d2d20SMatthew G Knepley 40c87d2d20SMatthew G Knepleyif __name__ == '__main__': 41c87d2d20SMatthew G Knepley library = 'KSP' 42c87d2d20SMatthew G Knepley num = 4 43c87d2d20SMatthew G Knepley ex = PETScExample(library, num, log_summary_python='summary.py', preload='off') 44*21c1d55bSMatthew G Knepley if 1: 45c87d2d20SMatthew G Knepley sizes = [] 46c87d2d20SMatthew G Knepley times = [] 47c87d2d20SMatthew G Knepley events = {} 48c87d2d20SMatthew G Knepley for n in [10, 20, 50, 100, 150, 200, 250, 300, 350]: 49c87d2d20SMatthew G Knepley ex.run(da_grid_x=n, da_grid_y=n, cusp_synchronize=1) 50c87d2d20SMatthew G Knepley sizes.append(n*n) 51c87d2d20SMatthew G Knepley processSummary('summary', times, events) 52c87d2d20SMatthew G Knepley plotSummary(library, num, sizes, times, events) 53*21c1d55bSMatthew G Knepley else: 54*21c1d55bSMatthew G Knepley times = [] 55*21c1d55bSMatthew G Knepley sizes = [] 56*21c1d55bSMatthew G Knepley for n in range(150, 1350, 100): 57*21c1d55bSMatthew G Knepley sizes.append(n*n) 58*21c1d55bSMatthew G Knepley baconostEvents = {'ElemAssembly': [(0.040919999999999998, 0.0), (0.1242, 0.0), (0.24410000000000001, 0.0), (0.374, 0.0), (0.56259999999999999, 0.0), (0.79049999999999998, 0.0), (1.0880000000000001, 0.0), (1.351, 0.0), (1.6930000000000001, 0.0), (2.0609999999999999, 0.0), (2.4820000000000002, 0.0), (3.0640000000000001, 0.0)], 'MatCUSPSetValBch': [(0.0123, 0.0), (0.023429999999999999, 0.0), (0.043540000000000002, 0.0), (0.06608, 0.0), (0.09579, 0.0), (0.12920000000000001, 0.0), (0.17169999999999999, 0.0), (0.2172, 0.0), (0.27179999999999999, 0.0), (0.48309999999999997, 0.0), (0.44180000000000003, 0.0), (0.51529999999999998, 0.0)]} 59*21c1d55bSMatthew G Knepley plotSummary(library, num, sizes, times, baconostEvents) 60