def processTrial(trial):
# extract the non-callpath events from the trial
print "extracting non-callpath..."
extractor = ExtractNonCallpathEventOperation(trial)
extracted = extractor.processData().get(0)
# print "extracting event..."
# extractor = ExtractEventOperation(trial, "MAIN__")
# extracted = extractor.processData().get(0)
# get basic statistics
print "computing mean..."
statMaker = BasicStatisticsOperation(extracted, True)
stats = statMaker.processData()
means = stats.get(BasicStatisticsOperation.MEAN)
# get main event
mainEvent = means.getMainEvent()
print "Main Event: ", mainEvent
# calculate all derived metrics
print "Deriving memory stall metrics..."
derived, PowerPerProc = getMemoryModel(means)
return derived
def main(trialName):
global mainEvent
global True
global False
global Joules
global PPJ
print "--------------- JPython test script start ------------"
print "--- Calculating Power Models --- "
# create a rulebase for processing
#print "Loading Rules..."
#ruleHarness = RuleHarness.useGlobalRules("openuh/OpenUHRules.drl")
# load the trial
print "loading the data..."
# check to see if the user has selected a trial
Utilities.setSession("openuh")
trial = TrialResult(
Utilities.getTrial("Fluid Dynamic Energy/Power", trialName, "1_1"))
# extract the non-callpath events from the trial
print "extracting non-callpath..."
extractor = ExtractNonCallpathEventOperation(trial)
extracted = extractor.processData().get(0)
# get basic statistics
print "computing mean..."
statMaker = BasicStatisticsOperation(extracted, False)
stats = statMaker.processData()
means = stats.get(BasicStatisticsOperation.MEAN)
# get main event
mainEvent = means.getMainEvent()
print "Main Event: ", mainEvent
# calculate all derived metrics
print
print "Deriving power metric..."
derived, PowerPerProc = getPowerModel(means)
# get the top 10 events
top10er = TopXEvents(derived, derived.getTimeMetric(),
AbstractResult.EXCLUSIVE, 10)
top10 = top10er.processData().get(0)
# just one thread
thread = 0
# iterate over events, output inefficiency derived metric
print
#print "Top 10 Average", PowerPerProc, "values per thread for this trial:"
#for event in top10er.getSortedEventNames():
#print event, derived.getExclusive(thread, event, PowerPerProc)
print
#print mainEvent, "INCLUSIVE: ", derived.getInclusive(thread, mainEvent, PowerPerProc)
print
# compute the energy consumed by each event
print "Computing joules consumed..."
derived, EnergyPerProc = getEnergy(derived, PowerPerProc)
Joules = EnergyPerProc
# iterate over events, output inefficiency derived metric
print
#print "Top 10 Average", EnergyPerProc, "values per thread for this trial:"
#for event in top10er.getSortedEventNames():
#print event, derived.getExclusive(thread, event, EnergyPerProc)
print
#print mainEvent, "INCLUSIVE: ", derived.getInclusive(thread, mainEvent, EnergyPerProc)
print
# compute the floating point operations per joule per event
print "Computing FP_OPS/joule..."
derived, FlopsPerJoule = getFlopsPerJoule(derived, EnergyPerProc)
PPJ = FlopsPerJoule
# iterate over events, output inefficiency derived metric
print
#print "Top 10 Average", FlopsPerJoule, "values per thread for this trial:"
#for event in top10er.getSortedEventNames():
#print event, derived.getExclusive(thread, event, FlopsPerJoule)
print
#print mainEvent, "INCLUSIVE: ", derived.getInclusive(thread, mainEvent, FlopsPerJoule)
print
# compute the floating point operations per joule per event
print "Computing Instructions Per Cycle..."
derived, IPC = getIPC(derived)
# iterate over events, output inefficiency derived metric
print
#print "Top 10 Average", IPC, "values per thread for this trial:"
#for event in top10er.getSortedEventNames():
#print event, derived.getExclusive(thread, event, IPC)
print
#print mainEvent, "INCLUSIVE: ", derived.getInclusive(thread, mainEvent, IPC)
print
# compute the floating point operations per joule per event
print "Computing Issued Per Cycle..."
derived, issuedPerCycle = getIssuedPerCycle(derived)
# iterate over events, output inefficiency derived metric
print
#print "Top 10 Average", issuedPerCycle, "values per thread for this trial:"
#for event in top10er.getSortedEventNames():
#print event, derived.getExclusive(thread, event, issuedPerCycle)
print
#print mainEvent, "INCLUSIVE: ", derived.getInclusive(thread, mainEvent, issuedPerCycle)
print
#print "Time to completion..."
print
#for event in top10er.getSortedEventNames():
#print event, derived.getExclusive(thread, event, derived.getTimeMetric())/1000000
print
#print mainEvent, "INCLUSIVE: ", derived.getInclusive(thread, mainEvent, derived.getTimeMetric())/1000000
# process the rules
#RuleHarness.getInstance().processRules()
print "---------------- JPython test script end -------------"
return derived
print "loading the data..."
# choose the right database configuration - a string which matches the end of the jdbc connection,
# such as "perfdmf" to match "jdbc:derby:/Users/khuck/src/tau2/apple/lib/perfdmf"
Utilities.setSession("openuh")
# load just the average values across all threads, input: app_name, exp_name, trial_name
#trial = TrialResult(Utilities.getTrial("Fluid Dynamic", "rib 45", "1_8"))
#trial = TrialResult(Utilities.getTrial("msap_parametric.optix.dynamic.4", "size.400", "16.threads"))
#trial = TrialResult(Utilities.getTrial("msap_parametric.optix.static_nowait", "size.400", "16.threads"))
trial = TrialResult(Utilities.getTrial("static", "size.400", "16.threads"))
#trial = TrialResult(Utilities.getTrial("msap_parametric.optix.dynamic.1", "size.400", "16.threads"))
#trial = TrialResult(Utilities.getCurrentTrial())
# extract the non-callpath events from the trial
extractor = ExtractNonCallpathEventOperation(trial)
extracted = extractor.processData().get(0)
# get basic statistics
statMaker = BasicStatisticsOperation(extracted, False)
stats = statMaker.processData()
stddev = stats.get(BasicStatisticsOperation.STDDEV)
means = stats.get(BasicStatisticsOperation.MEAN)
totals = stats.get(BasicStatisticsOperation.TOTAL)
mainEvent = means.getMainEvent()
print "Main Event: ", mainEvent
# get the ratio between stddev and total
ratioMaker = RatioOperation(stddev, means)
#ratioMaker = RatioOperation(stddev, means)
ratios = ratioMaker.processData().get(0)
def extractNonCallpath(input):
# extract the non-callpath events from the trial
extractor = ExtractNonCallpathEventOperation(input)
#extractor = ExtractCallpathEventOperation(input)
return extractor.processData().get(0)
def main():
global mainEvent
global True
global False
global L1Hits
global L2Hits
global L3Hits
global L1DataStalls
global InstMiss
global L2Refs
global L2DataRef
global L2Misses
global L3Misses
global TLBPenalty
global EarCache
global LocalMemoryHits
global RemoteMemoryHits
global RemoteMemoryAccesses
global RatioMemoryAccesses
global Total
global TotalRatio
print "--------------- JPython test script start ------------"
print "--- Calculating Memory Stall Causes --- "
# create a rulebase for processing
print "Loading Rules..."
ruleHarness = RuleHarness.useGlobalRules("openuh/OpenUHRules.drl")
# load the trial
print "loading the data..."
# check to see if the user has selected a trial
tmp = Utilities.getCurrentTrial()
if tmp != None:
trial = TrialResult(tmp)
print
else:
# remove these two lines to bypass this and use the default trial
print "No trial selected - script exiting"
return
# choose the right database configuration - a string which matches the end of the jdbc connection,
# such as "perfdmf" to match "jdbc:derby:/Users/khuck/src/tau2/apple/lib/perfdmf"
#Utilities.setSession("openuh")
# load just the average values across all threads, input: app_name, exp_name, trial_name
#trial = TrialResult(Utilities.getTrial("Fluid Dynamic - Unoptimized", "rib 45", "1_8"))
# extract the non-callpath events from the trial
print "extracting non-callpath..."
extractor = ExtractNonCallpathEventOperation(trial)
extracted = extractor.processData().get(0)
# get basic statistics
print "computing mean..."
statMaker = BasicStatisticsOperation(extracted, True)
stats = statMaker.processData()
means = stats.get(BasicStatisticsOperation.MEAN)
# get main event
mainEvent = means.getMainEvent()
print "Main Event: ", mainEvent
# calculate all derived metrics
print "Deriving memory stall metrics..."
derived, PowerPerProc = getMemoryModel(means)
# iterate over events, output inefficiency derived metric
for event in derived.getEvents():
MeanEventFact.compareEventToMain(derived, mainEvent, derived, event)
print
print
# output the top 10
top10er = TopXEvents(derived, derived.getTimeMetric(),
AbstractResult.EXCLUSIVE, 10)
top10 = top10er.processData().get(0)
for event in top10.getEvents():
print
if event == mainEvent:
print event, "L1 hits: ", L1Hits, derived.getInclusive(
0, event, L1Hits)
print event, "L2 hits: ", L2Hits, derived.getInclusive(
0, event, L2Hits)
print event, "L3 hits: ", L3Hits, derived.getInclusive(
0, event, L3Hits)
print event, "TLB Penalty: ", TLBPenalty, derived.getInclusive(
0, event, TLBPenalty)
print event, "Local Memory Hits: ", LocalMemoryHits, derived.getInclusive(
0, event, LocalMemoryHits)
print event, "Remote Memory Hits: ", RemoteMemoryHits, derived.getInclusive(
0, event, RemoteMemoryHits)
print event, "Total: ", Total, derived.getInclusive(
0, event, Total)
print event, "Total Ratio: ", TotalRatio, derived.getInclusive(
0, event, TotalRatio)
print event, "local/remote ratio: ", RatioMemoryAccesses, derived.getInclusive(
0, event, RatioMemoryAccesses)
else:
print event, "L1 hits: ", L1Hits, derived.getExclusive(
0, event, L1Hits)
print event, "L2 hits: ", L2Hits, derived.getExclusive(
0, event, L2Hits)
print event, "L3 hits: ", L3Hits, derived.getExclusive(
0, event, L3Hits)
print event, "TLB Penalty: ", TLBPenalty, derived.getExclusive(
0, event, TLBPenalty)
print event, "Local Memory Hits: ", LocalMemoryHits, derived.getExclusive(
0, event, LocalMemoryHits)
print event, "Remote Memory Hits: ", RemoteMemoryHits, derived.getExclusive(
0, event, RemoteMemoryHits)
print event, "Total: ", Total, derived.getExclusive(
0, event, Total)
print event, "Total Ratio: ", TotalRatio, derived.getExclusive(
0, event, TotalRatio)
print event, "local/remote ratio: ", RatioMemoryAccesses, derived.getExclusive(
0, event, RatioMemoryAccesses)
print
# process the rules
RuleHarness.getInstance().processRules()
print "---------------- JPython test script end -------------"
def main():
global mainEvent
global True
global False
print "--------------- JPython test script start ------------"
print "--- Calculating Power Models --- "
# create a rulebase for processing
#print "Loading Rules..."
#ruleHarness = RuleHarness.useGlobalRules("openuh/OpenUHRules.drl")
# load the trial
print "loading the data..."
# check to see if the user has selected a trial
tmp = Utilities.getCurrentTrial()
if tmp != None:
trial = TrialResult(tmp)
print
else:
# remove these two lines to bypass this and use the default trial
print "No trial selected - script exiting"
return
Utilities.setSession("openuh")
# load just the average values across all threads, input: app_name, exp_name, trial_name
#trial = TrialResult(Utilities.getTrial("msap_parametric.optix.static", "size.400", "16.threads"))
#trial = TrialResult(Utilities.getTrial("Fluid Dynamic - Unoptimized", "rib 45", "1_8"))
# extract the non-callpath events from the trial
print "extracting non-callpath..."
extractor = ExtractNonCallpathEventOperation(trial)
extracted = extractor.processData().get(0)
# print "extracting event..."
# extractor = ExtractEventOperation(trial, "MAIN__")
# extracted = extractor.processData().get(0)
# get basic statistics
print "computing mean..."
statMaker = BasicStatisticsOperation(extracted, True)
stats = statMaker.processData()
means = stats.get(BasicStatisticsOperation.MEAN)
# get main event
mainEvent = means.getMainEvent()
print "Main Event: ", mainEvent
# calculate all derived metrics
print "Deriving power metrics..."
derived, PowerPerProc = getPowerModel(means)
# get the top 10 "power dense" events
top10er = TopXEvents(derived, PowerPerProc, AbstractResult.EXCLUSIVE, 10)
top10 = top10er.processData().get(0)
# just one thread
thread = 0
# iterate over events, output inefficiency derived metric
print "Top 10 Average", PowerPerProc, "values per thread for this trial:"
for event in top10er.getSortedEventNames():
print event, top10.getExclusive(thread, event, PowerPerProc)
print
print mainEvent, "INCLUSIVE: ", derived.getInclusive(thread, mainEvent, PowerPerProc)
print
# compute the energy consumed by each event
print "Computing joules consumed..."
derived, EnergyPerProc = getEnergy(derived, PowerPerProc)
# get the top 10 "power dense" events
top10er = TopXEvents(derived, EnergyPerProc, AbstractResult.EXCLUSIVE, 10)
top10 = top10er.processData().get(0)
# iterate over events, output inefficiency derived metric
print "Top 10 Average", EnergyPerProc, "values per thread for this trial:"
for event in top10er.getSortedEventNames():
print event, top10.getExclusive(thread, event, EnergyPerProc)
#print event, top10.getExclusive(thread, event, "LINUX_TIMERS")
#print event, top10.getExclusive(thread, event, "(LINUX_TIMERS*1.0E-6)")
print
print mainEvent, "INCLUSIVE: ", derived.getInclusive(thread, mainEvent, EnergyPerProc)
#print mainEvent, derived.getExclusive(thread, event, "LINUX_TIMERS")
#print mainEvent, derived.getExclusive(thread, event, "(LINUX_TIMERS*1.0E-6)")
print
# compute the floating point operations per joule per event
print "Computing FP_OPS/joule..."
derived, FlopsPerJoule = getFlopsPerJoule(derived, EnergyPerProc)
# get the top 10 "power dense" events
top10er = TopXEvents(derived, FlopsPerJoule, AbstractResult.EXCLUSIVE, 10)
top10 = top10er.processData().get(0)
# iterate over events, output inefficiency derived metric
print "Top 10 Average", FlopsPerJoule, "values per thread for this trial:"
for event in top10er.getSortedEventNames():
print event, top10.getExclusive(thread, event, FlopsPerJoule)
print
print mainEvent, "INCLUSIVE: ", derived.getInclusive(thread, mainEvent, FlopsPerJoule)
print
# process the rules
#RuleHarness.getInstance().processRules()
print "---------------- JPython test script end -------------"