def testAmdahlModelLinear(self):
points = [SimpleDataPoint(cpuCount=1, cpu=1, time=1000, probSize=35, totalMemory=100),
SimpleDataPoint(cpuCount=2, cpu=1, time=600, probSize=35, totalMemory=100),
SimpleDataPoint(cpuCount=2, cpu=1, time=1200, probSize=70, totalMemory=100)]
model = AmdahlsCompModel(dataPoints=points, scaleFunction='linear')
self.assertEquals(1000, model.modelFunc(probSize=35, cpu=1, count=1))
self.assertEquals(600, model.modelFunc(probSize=35, cpu=1, count=2))
self.assertAlmostEquals(400, model.modelFunc(probSize=35, cpu=1, count=4))
self.assertAlmostEquals(300, model.modelFunc(probSize=35, cpu=1, count=8))
self.assertAlmostEquals(1200, model.modelFunc(probSize=70, cpu=1, count=2))
self.assertAlmostEquals(2400, model.modelFunc(probSize=140, cpu=1, count=2))
return
plots= []
plots.append(plot([35, 35, 70],[1000, 600, 1200],'ro'))
labels = ['real']
probSize = linspace(0,200,5)
for count in range(1,5):
plots.append(plot(probSize, model.modelFunc(probSize, None, count)))
labels.append("%d" % count)
legend([p[0] for p in plots], labels)
show()
def testAmdahlModelLinearVariousCpu2(self):
points = [SimpleDataPoint(cpuCount=1, cpu=1, time=1000, probSize=35, totalMemory=100),
SimpleDataPoint(cpuCount=2, cpu=2, time=300, probSize=35, totalMemory=100),
SimpleDataPoint(cpuCount=2, cpu=1, time=1200, probSize=70, totalMemory=100)]
model = AmdahlsCompModel(dataPoints=points, scaleFunction='linear')
self.assertEquals(1000, model.modelFunc(probSize=35, cpu=1, count=1))
self.assertEquals(600, model.modelFunc(probSize=35, cpu=1, count=2))
self.assertAlmostEquals(400, model.modelFunc(probSize=35, cpu=1, count=4))
self.assertAlmostEquals(300, model.modelFunc(probSize=35, cpu=1, count=8))
self.assertAlmostEquals(1200, model.modelFunc(probSize=70, cpu=1, count=2))
self.assertAlmostEquals(1200, model.modelFunc(probSize=140, cpu=2, count=2))