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Copyright©2010,ElsevierInc.AllrightsReservedChapter1WhyParallelComputing?AnIntroductiontoParallelProgrammingPeterPachecoCopyright©2010,ElsevierIncCopyright©2010,ElsevierInc.AllrightsReservedRoadmapWhyweneedever-increasingperformance.Whywe’rebuildingparallelsystems.Whyweneedtowriteparallelprograms.Howdowewriteparallelprograms?Whatwe’llbedoing.Concurrent,parallel,distributed!#ChapterSubtitleCopyright©2010,ElsevierIncChangingtimesCopyright©2010,ElsevierInc.AllrightsReservedFrom1986–2002,microprocessorswerespeedinglikearocket,increasinginperformanceanaverageof50%peryear.
Sincethen,it’sdroppedtoabout20%increaseperyear.ChangingtimesCopyright©2010AnintelligentsolutionCopyright©2010,ElsevierInc.AllrightsReservedInsteadofdesigningandbuildingfastermicroprocessors,putmultipleprocessorsonasingleintegratedcircuit.
AnintelligentsolutionCopyrigNowit’suptotheprogrammersAddingmoreprocessorsdoesn’thelpmuchifprogrammersaren’tawareofthem……ordon’tknowhowtousethem.
Serialprogramsdon’tbenefitfromthisapproach(inmostcases).Copyright©2010,ElsevierInc.AllrightsReservedNowit’suptotheprogrammersWhyweneedever-increasingperformanceComputationalpowerisincreasing,butsoareourcomputationproblemsandneeds.Problemsweneverdreamedofhavebeensolvedbecauseofpastincreases,suchasdecodingthehumangenome.Morecomplexproblemsarestillwaitingtobesolved.Copyright©2010,ElsevierInc.AllrightsReservedWhyweneedever-increasingpeClimatemodelingCopyright©2010,ElsevierInc.AllrightsReservedClimatemodelingCopyright©20ProteinfoldingCopyright©2010,ElsevierInc.AllrightsReservedProteinfoldingCopyright©201DrugdiscoveryCopyright©2010,ElsevierInc.AllrightsReservedDrugdiscoveryCopyright©2010EnergyresearchCopyright©2010,ElsevierInc.AllrightsReservedEnergyresearchCopyright©201DataanalysisCopyright©2010,ElsevierInc.AllrightsReservedDataanalysisCopyright©2010,Whywe’rebuildingparallelsystemsUptonow,performanceincreaseshavebeenattributabletoincreasingdensityoftransistors.
Butthereare
inherent
problems.Copyright©2010,ElsevierInc.AllrightsReservedWhywe’rebuildingparallelsyAlittlephysicslessonSmallertransistors=fasterprocessors.Fasterprocessors=increasedpowerconsumption.Increasedpowerconsumption=increasedheat.Increasedheat=unreliableprocessors.Copyright©2010,ElsevierInc.AllrightsReservedAlittlephysicslessonSmallerSolutionMoveawayfromsingle-coresystemstomulticoreprocessors.“core”=centralprocessingunit(CPU)
Copyright©2010,ElsevierInc.AllrightsReservedIntroducingparallelism!!!SolutionMoveawayfromsingleWhyweneedtowriteparallelprogramsRunningmultipleinstancesofaserialprogramoftenisn’tveryuseful.Thinkofrunningmultipleinstancesofyourfavoritegame.Whatyoureallywantisfor
ittorunfaster.Copyright©2010,ElsevierInc.AllrightsReservedWhyweneedtowriteparallelApproachestotheserialproblemRewriteserialprogramssothatthey’reparallel.
Writetranslationprogramsthatautomaticallyconvertserialprogramsintoparallelprograms.Thisisverydifficulttodo.Successhasbeenlimited.Copyright©2010,ElsevierInc.AllrightsReservedApproachestotheserialproblMoreproblemsSomecodingconstructscanberecognizedbyanautomaticprogramgenerator,andconvertedtoaparallelconstruct.However,it’slikelythattheresultwillbeaveryinefficientprogram.Sometimesthebestparallelsolutionistostepbackanddeviseanentirelynewalgorithm.Copyright©2010,ElsevierInc.AllrightsReservedMoreproblemsSomecodingconstExampleComputenvaluesandaddthemtogether.Serialsolution:Copyright©2010,ElsevierInc.AllrightsReservedExampleComputenvaluesandadExample(cont.)Wehavepcores,pmuchsmallerthann.Eachcoreperformsapartialsumofapproximatelyn/pvalues.Copyright©2010,ElsevierInc.AllrightsReservedEachcoreusesit’sownprivatevariablesandexecutesthisblockofcode
independentlyoftheothercores.Example(cont.)WehavepcoresExample(cont.)Aftereachcorecompletesexecutionofthecode,isaprivatevariablemy_sumcontainsthesumofthevaluescomputedbyitscallstoCompute_next_value.Ex.,8cores,n=24,thenthecallstoCompute_next_valuereturn:Copyright©2010,ElsevierInc.AllrightsReserved1,4,3,9,2,8,5,1,1,5,2,7,2,5,0,4,1,8,6,5,1,2,3,9Example(cont.)AftereachcoreExample(cont.)Onceallthecoresaredonecomputingtheirprivatemy_sum,theyformaglobalsumbysendingresultstoadesignated“master”corewhichaddsthefinalresult.Copyright©2010,ElsevierInc.AllrightsReservedExample(cont.)OnceallthecoExample(cont.)Copyright©2010,ElsevierInc.AllrightsReservedExample(cont.)Copyright©201Example(cont.)Copyright©2010,ElsevierInc.AllrightsReservedCore01234567my_sum8197157131214Globalsum8+19+7+15+7+13+12+14=95Core01234567my_sum95197157131214Example(cont.)Copyright©201Copyright©2010,ElsevierInc.AllrightsReservedButwait!There’samuchbetterway
tocomputetheglobalsum.Copyright©2010,ElsevierIncBetterparallelalgorithmDon’tmakethemastercoredoallthework.Shareitamongtheothercores.Pairthecoressothatcore0addsitsresultwithcore1’sresult.Core2addsitsresultwithcore3’sresult,etc.Workwithoddandevennumberedpairsofcores.Copyright©2010,ElsevierInc.AllrightsReservedBetterparallelalgorithmDon’tBetterparallelalgorithm(cont.)Repeattheprocessnowwithonlytheevenlyrankedcores.Core0addsresultfromcore2.Core4addstheresultfromcore6,etc.Nowcoresdivisibleby4repeattheprocess,andsoforth,untilcore0hasthefinalresult.Copyright©2010,ElsevierInc.AllrightsReservedBetterparallelalgorithm(conMultiplecoresformingaglobalsumCopyright©2010,ElsevierInc.AllrightsReservedMultiplecoresformingaglobaAnalysisInthefirstexample,themastercoreperforms7receivesand7additions.Inthesecondexample,themastercoreperforms3receivesand3additions.Theimprovementismorethanafactorof2!Copyright©2010,ElsevierInc.AllrightsReservedAnalysisInthefirstexample,Analysis(cont.)Thedifferenceismoredramaticwithalargernumberofcores.Ifwehave1000cores:Thefirstexamplewouldrequirethemastertoperform999receivesand999additions.Thesecondexamplewouldonlyrequire10receivesand10additions.
That’sanimprovementofalmostafactorof100!Copyright©2010,ElsevierInc.AllrightsReservedAnalysis(cont.)ThedifferenceHowdowewriteparallelprograms?TaskparallelismPartitionvarioustaskscarriedoutsolvingtheproblemamongthecores.
DataparallelismPartitionthedatausedinsolvingtheproblemamongthecores.Eachcorecarriesoutsimilaroperationsonit’spartofthedata.Copyright©2010,ElsevierInc.AllrightsReservedHowdowewriteparallelprogrProfessorPCopyright©2010,ElsevierInc.AllrightsReserved15questions300examsProfessorPCopyright©2010,EProfessorP’sgradingassistantsCopyright©2010,ElsevierInc.AllrightsReservedTA#1TA#2TA#3ProfessorP’sgradingassistanDivisionofwork–
dataparallelismCopyright©2010,ElsevierInc.AllrightsReservedTA#1TA#2TA#3100exams100exams100examsDivisionofwork–
dataparalDivisionofwork–
taskparallelismCopyright©2010,ElsevierInc.AllrightsReservedTA#1TA#2TA#3Questions1-5Questions6-10Questions11-15Divisionofwork–
taskparalDivisionofwork–
dataparallelismCopyright©2010,ElsevierInc.AllrightsReservedDivisionofwork–
dataparalDivisionofwork–
taskparallelismCopyright©2010,ElsevierInc.AllrightsReservedTasksReceivingAdditionDivisionofwork–
taskparalCoordinationCoresusuallyneedtocoordinatetheirwork.Communication–oneormorecoressendtheircurrentpartialsumstoanothercore.Loadbalancing–sharetheworkevenlyamongthecoressothatoneisnotheavilyloaded.Synchronization–becauseeachcoreworksatitsownpace,makesurecoresdonotgettoofaraheadoftherest.Copyright©2010,ElsevierInc.AllrightsReservedCoordinationCoresusuallyneedWhatwe’llbedoingLearningtowriteprogramsthatareexplicitlyparallel.UsingtheClanguage.UsingthreedifferentextensionstoC.Message-PassingInterface(MPI)PosixThreads(Pthreads)OpenMPCopyright©2010,ElsevierInc.AllrightsReservedWhatwe’llbedoingLearningtoTypeofparallelsystemsShared-memoryThecorescanshareaccesstothecomputer’smemory.Coordinatethecoresbyhavingthemexamineandupdatesharedmemorylocations.Distributed-memoryEachcorehasitsown,privatememory.Thecoresmustcommunicateexplicitlybysendingmessagesacrossanetwork.Copyright©2010,ElsevierInc.AllrightsReservedTypeofparallelsystemsSharedTypeofparallelsystemsCopyright©2010,ElsevierInc.AllrightsReservedShared-memoryDistributed-memoryTypeofparallelsystemsCopyriTerminologyConcurrentcomputing–aprogramisoneinwhichmultipletaskscanbeinprogressatanyinstant.Parallelcomputing–aprogramisoneinwhichmultipletaskscooperatecloselytosolveaproblemDistributedcomputing–aprogrammayneedtocooperatewithotherprogramstosolveaproblem.Copyright©2010,ElsevierInc.AllrightsReservedTerminologyConcurrentcomputiConcludingRemarks(1)Thelawsofphysicshavebroughtustothedoorstepofmulticoretechnology.Serialprogramstypicallydon’tbenefitfrommultiplecores.Automaticparallelprogramgenerationfromserialprogramcodeisn’tthemostefficientapproachtogethighperformancefrommulticorecomputers.Copyright©2010,ElsevierInc.AllrightsReservedConcludingRemarks(1)ThelawsConcludingRemarks(2)Learningtowriteparallelprogramsinvolveslearninghowtocoordinatethecores.Parallelprogramsareusuallyverycomplexandtherefore,requiresoundprogramtechniquesanddevelopment.Copyright©2010,ElsevierInc.AllrightsReservedConcludingRemarks(2)LearningCopyright©2010,ElsevierInc.AllrightsReservedChapter1WhyParallelComputing?AnIntroductiontoParallelProgrammingPeterPachecoCopyright©2010,ElsevierIncCopyright©2010,ElsevierInc.AllrightsReservedRoadmapWhyweneedever-increasingperformance.Whywe’rebuildingparallelsystems.Whyweneedtowriteparallelprograms.Howdowewriteparallelprograms?Whatwe’llbedoing.Concurrent,parallel,distributed!#ChapterSubtitleCopyright©2010,ElsevierIncChangingtimesCopyright©2010,ElsevierInc.AllrightsReservedFrom1986–2002,microprocessorswerespeedinglikearocket,increasinginperformanceanaverageof50%peryear.
Sincethen,it’sdroppedtoabout20%increaseperyear.ChangingtimesCopyright©2010AnintelligentsolutionCopyright©2010,ElsevierInc.AllrightsReservedInsteadofdesigningandbuildingfastermicroprocessors,putmultipleprocessorsonasingleintegratedcircuit.
AnintelligentsolutionCopyrigNowit’suptotheprogrammersAddingmoreprocessorsdoesn’thelpmuchifprogrammersaren’tawareofthem……ordon’tknowhowtousethem.
Serialprogramsdon’tbenefitfromthisapproach(inmostcases).Copyright©2010,ElsevierInc.AllrightsReservedNowit’suptotheprogrammersWhyweneedever-increasingperformanceComputationalpowerisincreasing,butsoareourcomputationproblemsandneeds.Problemsweneverdreamedofhavebeensolvedbecauseofpastincreases,suchasdecodingthehumangenome.Morecomplexproblemsarestillwaitingtobesolved.Copyright©2010,ElsevierInc.AllrightsReservedWhyweneedever-increasingpeClimatemodelingCopyright©2010,ElsevierInc.AllrightsReservedClimatemodelingCopyright©20ProteinfoldingCopyright©2010,ElsevierInc.AllrightsReservedProteinfoldingCopyright©201DrugdiscoveryCopyright©2010,ElsevierInc.AllrightsReservedDrugdiscoveryCopyright©2010EnergyresearchCopyright©2010,ElsevierInc.AllrightsReservedEnergyresearchCopyright©201DataanalysisCopyright©2010,ElsevierInc.AllrightsReservedDataanalysisCopyright©2010,Whywe’rebuildingparallelsystemsUptonow,performanceincreaseshavebeenattributabletoincreasingdensityoftransistors.
Butthereare
inherent
problems.Copyright©2010,ElsevierInc.AllrightsReservedWhywe’rebuildingparallelsyAlittlephysicslessonSmallertransistors=fasterprocessors.Fasterprocessors=increasedpowerconsumption.Increasedpowerconsumption=increasedheat.Increasedheat=unreliableprocessors.Copyright©2010,ElsevierInc.AllrightsReservedAlittlephysicslessonSmallerSolutionMoveawayfromsingle-coresystemstomulticoreprocessors.“core”=centralprocessingunit(CPU)
Copyright©2010,ElsevierInc.AllrightsReservedIntroducingparallelism!!!SolutionMoveawayfromsingleWhyweneedtowriteparallelprogramsRunningmultipleinstancesofaserialprogramoftenisn’tveryuseful.Thinkofrunningmultipleinstancesofyourfavoritegame.Whatyoureallywantisfor
ittorunfaster.Copyright©2010,ElsevierInc.AllrightsReservedWhyweneedtowriteparallelApproachestotheserialproblemRewriteserialprogramssothatthey’reparallel.
Writetranslationprogramsthatautomaticallyconvertserialprogramsintoparallelprograms.Thisisverydifficulttodo.Successhasbeenlimited.Copyright©2010,ElsevierInc.AllrightsReservedApproachestotheserialproblMoreproblemsSomecodingconstructscanberecognizedbyanautomaticprogramgenerator,andconvertedtoaparallelconstruct.However,it’slikelythattheresultwillbeaveryinefficientprogram.Sometimesthebestparallelsolutionistostepbackanddeviseanentirelynewalgorithm.Copyright©2010,ElsevierInc.AllrightsReservedMoreproblemsSomecodingconstExampleComputenvaluesandaddthemtogether.Serialsolution:Copyright©2010,ElsevierInc.AllrightsReservedExampleComputenvaluesandadExample(cont.)Wehavepcores,pmuchsmallerthann.Eachcoreperformsapartialsumofapproximatelyn/pvalues.Copyright©2010,ElsevierInc.AllrightsReservedEachcoreusesit’sownprivatevariablesandexecutesthisblockofcode
independentlyoftheothercores.Example(cont.)WehavepcoresExample(cont.)Aftereachcorecompletesexecutionofthecode,isaprivatevariablemy_sumcontainsthesumofthevaluescomputedbyitscallstoCompute_next_value.Ex.,8cores,n=24,thenthecallstoCompute_next_valuereturn:Copyright©2010,ElsevierInc.AllrightsReserved1,4,3,9,2,8,5,1,1,5,2,7,2,5,0,4,1,8,6,5,1,2,3,9Example(cont.)AftereachcoreExample(cont.)Onceallthecoresaredonecomputingtheirprivatemy_sum,theyformaglobalsumbysendingresultstoadesignated“master”corewhichaddsthefinalresult.Copyright©2010,ElsevierInc.AllrightsReservedExample(cont.)OnceallthecoExample(cont.)Copyright©2010,ElsevierInc.AllrightsReservedExample(cont.)Copyright©201Example(cont.)Copyright©2010,ElsevierInc.AllrightsReservedCore01234567my_sum8197157131214Globalsum8+19+7+15+7+13+12+14=95Core01234567my_sum95197157131214Example(cont.)Copyright©201Copyright©2010,ElsevierInc.AllrightsReservedButwait!There’samuchbetterway
tocomputetheglobalsum.Copyright©2010,ElsevierIncBetterparallelalgorithmDon’tmakethemastercoredoallthework.Shareitamongtheothercores.Pairthecoressothatcore0addsitsresultwithcore1’sresult.Core2addsitsresultwithcore3’sresult,etc.Workwithoddandevennumberedpairsofcores.Copyright©2010,ElsevierInc.AllrightsReservedBetterparallelalgorithmDon’tBetterparallelalgorithm(cont.)Repeattheprocessnowwithonlytheevenlyrankedcores.Core0addsresultfromcore2.Core4addstheresultfromcore6,etc.Nowcoresdivisibleby4repeattheprocess,andsoforth,untilcore0hasthefinalresult.Copyright©2010,ElsevierInc.AllrightsReservedBetterparallelalgorithm(conMultiplecoresformingaglobalsumCopyright©2010,ElsevierInc.AllrightsReservedMultiplecoresformingaglobaAnalysisInthefirstexample,themastercoreperforms7receivesand7additions.Inthesecondexample,themastercoreperforms3receivesand3additions.Theimprovementismorethanafactorof2!Copyright©2010,ElsevierInc.AllrightsReservedAnalysisInthefirstexample,Analysis(cont.)Thedifferenceismoredramaticwithalargernumberofcores.Ifwehave1000cores:Thefirstexamplewouldrequirethemastertoperform999receivesand999additions.Thesecondexamplewouldonlyrequire10receivesand10additions.
That’sanimprovementofalmostafactorof100!Copyright©2010,ElsevierInc.AllrightsReservedAnalysis(cont.)ThedifferenceHowdowewriteparallelprograms?TaskparallelismPartitionvarioustaskscarriedoutsolvingtheproblemamongthecores.
DataparallelismPartitionthedatausedinsolvingtheproblemamongthecores.Eachcorecarriesoutsimilaroperationsonit’spartofthedata.Copyright©2010,ElsevierInc.AllrightsReservedHowdowewriteparallelprogrProfessorPCopyright©2010,ElsevierInc.AllrightsReserved15questions300examsProfessorPCopyright©2010,EProfessorP’sgradingassistantsCopyright©2010,ElsevierInc.AllrightsReservedTA#1TA#2TA#3ProfessorP’sgradingassistanDivisionofwork–
dataparallelismCopyright©2010,ElsevierInc.AllrightsReservedTA#1TA#2TA#3100exams100exams100examsDivisionofwork–
dataparalDivisionofwork–
taskparallelismCopyright©2010,ElsevierInc.AllrightsReservedTA#1TA#2TA#3Questions1-5Questions6-10Questions11-15Divisionofwork–
taskparalDivisionofwork–
dataparallelismCopyright©2010,ElsevierInc.AllrightsReservedDivisionofwork–
dataparalDivisionofwork–
taskparallelismCopyright©2010,ElsevierInc.AllrightsReservedTasksReceivingAdditionDivisionofwork–
taskparalCoordinationCoresusuallyneedtocoordinatetheirwork.Communication–oneormorecoressendtheircurrentpartialsumstoanothercore.Loadbalancing–sharetheworkevenlyamongthecoressothatoneisnotheavily
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