Exemplo n.º 1
0
def test():
  appList = []
  for line in open('filelist.txt'):
    appList.append(str(line.rsplit('\n')[0]))

  for app in appList:
    globalvars.appName = "app" + str(appList.index(app) + 69)
    globalvars.pinballLoc = str(app)
    globalvars.outputDirBase = "/home/gangwan2/workdir1/cs446/outputs/"+globalvars.appName+"/"
    baseConfig = tuple([96, 64, 256, 4, 512])
    featureGeneration.extract([baseConfig], [featureNames],
        globalvars.outputDirBase, True)
Exemplo n.º 2
0
def parallelDetailed(appName, pinballLoc, outputDirBase):
  # log the output of the process to a specific file
  sys.stdout = open(outputDirBase+"plog.out", "w")
  appfeatures = list(list())
   
  #append the names of the features 
  appfeatures.append(featureNames)

  goodConfigs = goodConfigDict[appName]

  # now that we have the good configs, we need to launch sniper runs again for
  # these configs with detailed stat (counter-data) collection enabled
  #print('++Detailed-Run++')
  launcher.run(goodConfigs, parameterNames, True, False, pinballLoc, outputDirBase)

  # from the detailed runs, we now extract the feature vectors - this forms the
  # training data. Feature vectors are logged to a file
  #print('++Extraction++')
  featureGeneration.extract(goodConfigs, appfeatures, outputDirBase)