本文整理汇总了Python中job.Job.approxAlgoMapVal方法的典型用法代码示例。如果您正苦于以下问题：Python Job.approxAlgoMapVal方法的具体用法？Python Job.approxAlgoMapVal怎么用？Python Job.approxAlgoMapVal使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类job.Job的用法示例。
在下文中一共展示了Job.approxAlgoMapVal方法的3个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: unit_test
# 需要导入模块: from job import Job [as 别名]
# 或者: from job.Job import approxAlgoMapVal [as 别名]
def unit_test():
for i in range(0, 20):
job = Job(nmaps=64, lmap=140, lmapapprox=60, nreds=1, lred=15, submit=i*150)
job.approxAlgoMapVal = options.approx # Approximate 50% of the maps
if random.random() < 0.5:
job.priority = Job.Priority.VERY_HIGH
jobId = simulator.addJob(job)
for jobID in simulator.jobsQueue:
myjob = simulator.jobs[jobID]
print myjob.jobId, myjob.priority, myjob.submit
sys.exit(0)示例2: read
# 需要导入模块: from job import Job [as 别名]
# 或者: from job.Job import approxAlgoMapVal [as 别名]
def read(self, inFile):
#lineno=0
with open(inFile, "r") as f:
for line in f:
line = line.replace('\n', '')
line = line.strip()
if not line.startswith('#') and len(line) > 0:
# Job(nmaps=64, lmap=140, lmapapprox=60, nreds=1, lred=15, submit=i*150, approx)
splits = line.split()
nmaps0 = int(splits[0])
lmap0 = int(splits[1])
lmapapprox0 = int(splits[2])
nreds0 = int(splits[3])
lred0 = int(splits[4])
#lredapprox0 = int(splits[4]) # TODO cheng
submit0 = int(splits[5])
approx0 = float(splits[6])
# Create job
job = Job(nmaps=nmaps0, lmap=lmap0, lmapapprox=lmapapprox0, nreds=nreds0, lred=lred0, submit=submit0)
job.approxAlgoMapVal = approx0
self.jobQueue.append(job)
#lineno+=1
#return lineno
return self.jobQueue示例3: range
# 需要导入模块: from job import Job [as 别名]
# 或者: from job.Job import approxAlgoMapVal [as 别名]
job.priority=getProbBySchedule(weights, job.nreds)
else:
job.priority=getProbabilisticSJF(job.nreds, options.sjf)
simulator.addJob(job)
'''
manager.initManager(options.infile)
if options.sjf > 0.0:
manager.applySJFPriority(options.sjf)
manager.copyToSimulator(simulator);
'''
else:
# Submit jobs
for i in range(0, options.jobs):
# Create the job
job = Job(nmaps=64, lmap=140, lmapapprox=60, nreds=1, lred=15, submit=0)
job.approxAlgoMapVal = options.approx # Approximate X% of the maps
job.approxDropMapVal = options.drop # Drop X% of the maps
job.gauss = options.gauss # +/-%
# Probabilistic shortest job first policy
job.priority = getProbabilisticSJF(job.nreds, options.sjf)
jobId = simulator.addJob(job)
# Start running simulator
simulator.run()
# Summary
print 'Nodes: %d' % len(simulator.nodes)
print 'Energy: %.1fWh' % (simulator.getEnergy())
print 'Perf: %.1fs %d jobs' % (simulator.getPerformance(), len(simulator.jobs))
print 'Quality: %.1f%%' % (simulator.getQuality())