Révision 287 Pi/XPU/PiXpuMPI.py
| PiXpuMPI.py (revision 287) | ||
|---|---|---|
| 235 | 235 |
DurationItem=numpy.array([]).astype(numpy.float32) |
| 236 | 236 |
Duration=numpy.array([]).astype(numpy.float32) |
| 237 | 237 |
Rate=numpy.array([]).astype(numpy.float32) |
| 238 |
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| 238 | 239 |
for i in range(Redo): |
| 239 | 240 |
time_start=time.time() |
| 240 | 241 |
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| ... | ... | |
| 288 | 289 |
NewIterations+=OutputCL['NewIterations'] |
| 289 | 290 |
Inside+=OutputCL['Inside'] |
| 290 | 291 |
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| 291 |
Duration=numpy.append(Duration,time.time()-time_start) |
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| 292 |
Rate=numpy.append(Rate,NewIterations/Duration[-1]) |
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| 293 |
print("Itops %i\nLogItops %.2f " % (int(Rate),numpy.log(Rate)/numpy.log(10)))
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print("Pi estimation %.8f" % (4./NewIterations*Inside))
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Duration=numpy.append(Duration,time.time()-time_start) |
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Rate=numpy.append(Rate,NewIterations/Duration[-1]) |
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| 295 | 294 |
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print("Itops %i\nLogItops %.2f " % (int(Rate[-1]),numpy.log(Rate[-1])/numpy.log(10)))
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print("Pi estimation %.8f" % (4./NewIterations*Inside))
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| 296 | 297 |
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| 297 | 298 |
avgD=numpy.append(avgD,numpy.average(Duration)) |
| 298 | 299 |
medD=numpy.append(medD,numpy.median(Duration)) |
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