예제 #1
0
def loaddata():
    print "loading the data..."
    Utilities.setSession("openuh")
    #Utilities.setSession("perfdmf")
    #trial = TrialMeanResult(Utilities.getTrial("fortran", "test", "O3-2048-real.8-bounds"))
    #trial = TrialMeanResult(Utilities.getTrial("fortran", "test", "O3-2048-real.8-options"))
    #trial = TrialMeanResult(Utilities.getTrial("msap_parametric.static", "size.400", "1.threads"))
    trial = TrialMeanResult(
        Utilities.getTrial("msap_parametric.optix.static", "size.400",
                           "16.threads"))
    return trial
예제 #2
0
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
예제 #3
0
###################################################################

print "--------------- JPython test script start ------------"
print "--- Looking for load imbalances --- "

# create a rulebase for processing
print "Loading Rules..."
ruleHarness = RuleHarness.useGlobalRules("openuh/OpenUHRules.drl")

# load the trial
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)
예제 #4
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 -------------"
예제 #5
0
from glue import ExtractNonCallpathEventOperation
from glue import DeriveMetricOperation
from glue import MergeTrialsOperation
from glue import DerivedMetrics
from glue import TopXEvents
from glue import MeanEventFact

###################################################################

print "---------------- JPython test script begin -----------"

# create a rulebase for processing
ruleHarness = RuleHarness.useGlobalRules("openuh/OpenUHRules.drl")

# load a trial
trial = TrialMeanResult(Utilities.getTrial("Fluid Dynamic", "rib 45", "1_8"))

# calculate the derived metric
totalStalls = "BACK_END_BUBBLE_ALL"
totalCycles = "CPU_CYCLES"
derivor = DeriveMetricOperation(trial, totalStalls, totalCycles,
                                DeriveMetricOperation.DIVIDE)
derived = derivor.processData().get(0)

for event in derived.getEvents():
    MeanEventFact.compareEventToMain(derived, mainEvent, derived, event)
print

# process the rules
RuleHarness.getInstance().processRules()
예제 #6
0
from glue import TrialMeanResult
from glue import TopXEvents
from glue import AbstractResult
from glue import DeriveMetricOperation
from glue import DerivedMetrics
from glue import MeanEventFact

###################################################################

print "---------------- JPython test script begin -----------"

# create a rulebase for processing
#ruleHarness = RuleHarness.useGlobalRules("openuh/OpenUHRules.drl")

# load a trial
Utilities.setSession("openuh")
trial = TrialMeanResult(Utilities.getTrial("Fluid Dynamic", "rib 45", "1_8"))

# calculate the derived metric
totalStalls = "BACK_END_BUBBLE_ALL"
totalCycles = "CPU_CYCLES"
newMetric = "(BACK_END_BUBBLE_ALL/CPU_CYCLES)"
derivor = DeriveMetricOperation(trial, totalStalls, totalCycles, DeriveMetricOperation.DIVIDE)
derived = derivor.processData().get(0)

# get the top 10 events
top10er = TopXEvents(derived, newMetric, AbstractResult.EXCLUSIVE, 10)
top10 = top10er.processData().get(0)

print "Top 10 events with high stall/cycle ratios:"
for event in top10er.getSortedEventNames():
예제 #7
0
###################################################################

print "--------------- JPython test script start ------------"
print "--- Calculating inefficiency --- "

# create a rulebase for processing
#print "Loading Rules..."
ruleHarness = RuleHarness.useGlobalRules("openuh/OpenUHRules.drl")

# load the trial
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("test")
#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 OpenMP", "rib 90",
                       "Original OpenMP 1_16"))

# extract the non-callpath events from the trial
print "extracting"
extractor = ExtractNonCallpathEventOperation(trial)
extracted = extractor.processData().get(0)

# get basic statistics
print "stats"
예제 #8
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 RemoteMemoryRatio
    global RatioMemoryAccesses
    global Total
    global TotalRatio

    print "--------------- JPython test script start ------------"
    print "--- Calculating Memory Stall Causes --- "

    # load the trial
    print "loading the data..."
    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 OpenMP", "rib 90",
                           "1_16"))
    first = processTrial(trial)
    trial = TrialResult(
        Utilities.getTrial("Fluid Dynamic - Optimized OpenMP", "rib 90",
                           "1_16"))
    second = processTrial(trial)

    differ = DifferenceOperation(first)
    differ.addInput(second)
    diff = differ.processData().get(0)

    # output the top 10
    top10er = TopXEvents(diff, diff.getTimeMetric(), AbstractResult.EXCLUSIVE,
                         10)
    top10 = top10er.processData().get(0)
    for event in top10.getEvents():
        print
        print event, "L1 hits: ", L1Hits, diff.getInclusive(0, event, L1Hits)
        print event, "L2 hits: ", L2Hits, diff.getInclusive(0, event, L2Hits)
        print event, "L3 hits: ", L3Hits, diff.getInclusive(0, event, L3Hits)
        print event, "TLB Penalty: ", TLBPenalty, diff.getInclusive(
            0, event, TLBPenalty)
        print event, "Local Memory Hits: ", LocalMemoryHits, diff.getInclusive(
            0, event, LocalMemoryHits)
        print event, "Remote Memory Hits: ", RemoteMemoryHits, diff.getInclusive(
            0, event, RemoteMemoryHits)
        print event, "Total: ", Total, diff.getInclusive(0, event, Total)
        print event, "Total Ratio: ", TotalRatio, diff.getInclusive(
            0, event, TotalRatio)
        print event, "local/remote ratio: ", RatioMemoryAccesses, diff.getInclusive(
            0, event, RatioMemoryAccesses)
        print

    print "---------------- JPython test script end -------------"
예제 #9
0
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 -------------"