xref: /petsc/src/benchmarks/benchmarkAssembly.py (revision 089b283744364aef00a310a92368c00bc3aa30b8) 
1#!/usr/bin/env python
2import os
3from benchmarkExample import PETScExample
4
5def processSummary(moduleName, times, events):
6  '''Process the Python log summary into plot data'''
7  m = __import__(moduleName)
8  reload(m)
9  # Total Time
10  times.append(m.Time[0])
11  # Common events
12  #   Add the time and flop rate
13  for name in ['MatCUSPSetValBch', 'ElemAssembly']:
14    if not name in events:
15      events[name] = []
16    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)))
17  return
18
19def plotSummary(library, num, sizes, times, events):
20  from pylab import legend, plot, show, title, xlabel, ylabel
21  import numpy as np
22  showEventTime  = True
23  print events
24  if showEventTime:
25    data  = []
26    names = []
27    for event, style in [('MatCUSPSetValBch', 'b-'), ('ElemAssembly', 'b:')]:
28      names.append(event)
29      data.append(sizes)
30      data.append(np.array(events[event])[:,0])
31      data.append(style)
32    plot(*data)
33    title('Performance on '+library+' Example '+str(num))
34    xlabel('Number of Dof')
35    ylabel('Time (s)')
36    legend(names, 'upper left', shadow = True)
37    show()
38  return
39
40if __name__ == '__main__':
41  library = 'KSP'
42  num     = 4
43  ex      = PETScExample(library, num, log_summary_python='summary.py', preload='off')
44  if 1:
45    sizes   = []
46    times   = []
47    events  = {}
48    for n in [10, 20, 50, 100, 150, 200, 250, 300, 350]:
49      ex.run(da_grid_x=n, da_grid_y=n, cusp_synchronize=1)
50      sizes.append(n*n)
51      processSummary('summary', times, events)
52    plotSummary(library, num, sizes, times, events)
53  else:
54    times   = []
55    sizes   = []
56    for n in range(150, 1350, 100):
57      sizes.append(n*n)
58    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    plotSummary(library, num, sizes, times, baconostEvents)
60