1#!/usr/bin/env python 2import os 3from benchmarkExample import PETScExample 4 5savedTiming = {'baconost': {'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)], 6 '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)]} 7 } 8 9def calculateNonzeros(n): 10 num = 0 11 # corners 12 num += 2*3 + 2*4 13 # edges 14 num += 4*(n-2)*5 15 # interior 16 num += (n-2)*(n-2)*7 17 return num 18 19def processSummary(moduleName, times, events): 20 '''Process the Python log summary into plot data''' 21 m = __import__(moduleName) 22 reload(m) 23 # Total Time 24 times.append(m.Time[0]) 25 # Common events 26 # Add the time and flop rate 27 for stageName, eventName in [('GPU_Stage','MatCUSPSetValBch'), ('CPU_Stage','ElemAssembly')]: 28 s = getattr(m, stageName) 29 if not eventName in events: 30 events[eventName] = [] 31 events[eventName].append((s.event[eventName].Time[0], s.event[eventName].Flops[0]/(s.event[eventName].Time[0] * 1e6))) 32 return 33 34def plotSummary(library, num, sizes, nonzeros, times, events): 35 from pylab import legend, plot, show, title, xlabel, ylabel, ylim 36 import numpy as np 37 showEventTime = True 38 showTimePerRow = False 39 showTimePerNonzero = True 40 print events 41 if showEventTime: 42 data = [] 43 names = [] 44 for event, style in [('MatCUSPSetValBch', 'b-'), ('ElemAssembly', 'b:')]: 45 names.append(event) 46 data.append(sizes) 47 data.append(np.array(events[event])[:,0]) 48 data.append(style) 49 plot(*data) 50 title('Performance on '+library+' Example '+str(num)) 51 xlabel('Number of Dof') 52 ylabel('Time (s)') 53 legend(names, 'upper left', shadow = True) 54 show() 55 if showTimePerRow: 56 data = [] 57 names = [] 58 for event, style in [('MatCUSPSetValBch', 'b-'), ('ElemAssembly', 'b:')]: 59 names.append(event) 60 data.append(sizes) 61 rows = np.sqrt(sizes) 62 data.append(np.array(events[event])[:,0]/rows/3) 63 data.append(style) 64 plot(*data) 65 title('Performance on '+library+' Example '+str(num)) 66 xlabel('Number of Dof') 67 ylabel('Time/Row (s)') 68 legend(names, 'upper left', shadow = True) 69 show() 70 if showTimePerNonzero: 71 data = [] 72 names = [] 73 for event, style in [('MatCUSPSetValBch', 'b-'), ('ElemAssembly', 'b:')]: 74 names.append(event) 75 data.append(sizes) 76 data.append(np.array(events[event])[:,0]/nonzeros * 10**9) 77 data.append(style) 78 plot(*data) 79 title('Performance on '+library+' Example '+str(num)) 80 xlabel('Number of Dof') 81 ylabel('Time/Nonzero (ns)') 82 legend(names, 'center right', shadow = True) 83 show() 84 return 85 86if __name__ == '__main__': 87 import argparse 88 89 parser = argparse.ArgumentParser(description = 'PETSc Benchmarking', 90 epilog = 'This script runs src/<library>/examples/tutorials/ex<num>, For more information, visit http://www.mcs.anl.gov/petsc', 91 formatter_class = argparse.ArgumentDefaultsHelpFormatter) 92 parser.add_argument('--library', default='KSP', help='The PETSc library used in this example') 93 parser.add_argument('--num', type = int, default='4', help='The example number') 94 parser.add_argument('--module', default='summary', help='The module for timing output') 95 parser.add_argument('--saved', help='Name of saved data') 96 parser.add_argument('--scaling', help='Run parallel scaling test') 97 parser.add_argument('--small', action='store_true', default=False, help='Use small sizes') 98 parser.add_argument('--batch', action='store_true', default=False, help='Generate batch files for the runs instead') 99 100 args = parser.parse_args() 101 print(args) 102 ex = PETScExample(args.library, args.num, log_summary_python = None if args.batch else args.module+'.py', preload='off') 103 sizes = [] 104 nonzeros = [] 105 times = [] 106 if args.saved is None: 107 events = {} 108 if args.scaling == 'strong': 109 procs = [1, 2, 4, 8] 110 if args.small: 111 grid = [10]*len(procs) 112 else: 113 grid = [1250]*len(procs) 114 else: 115 if args.small: 116 grid = [100, 150, 200, 250, 300] 117 else: 118 grid = range(150, 1350, 100) 119 procs = [1]*len(grid) 120 for n, p in zip(grid, procs): 121 ex.run(p, da_grid_x=n, da_grid_y=n, cusp_synchronize=1, batch=args.batch) 122 sizes.append(n*n) 123 nonzeros.append(calculateNonzeros(n)) 124 if not args.batch: 125 processSummary(args.module, times, events) 126 os.remove(args.module+'.pyc') 127 else: 128 if args.batch: raise RuntimeException('Cannot use batch option with saved data') 129 if args.saved in savedTiming: 130 events = savedTiming[args.saved] 131 else: 132 # Process output to produce module 133 events = {} 134 filenameBase = args.saved[:-7] 135 jobnumBase = int(args.saved[-7:]) 136 for i, n in enumerate(range(150, 1350, 100)): 137 filename = filenameBase+str(jobnumBase+i) 138 print 'Processing',filename 139 headerSeen = False 140 with file(filename) as f, file(args.module+'.py', 'w') as o: 141 for line in f.readlines(): 142 if not headerSeen: 143 if not line[0] == '#': continue 144 headerSeen = True 145 if line[0] == '#' and line[-6:] == '=====\n': break 146 o.write(line) 147 #print line 148 processSummary(args.module, times, events) 149 # I can't believe that this is necessary 150 os.remove(args.module+'.pyc') 151 for n in range(150, 1350, 100): 152 sizes.append(n*n) 153 nonzeros.append(calculateNonzeros(n)) 154 if not args.batch: plotSummary(args.library, args.num, sizes, nonzeros, times, events) 155