MultiplePlatforms:PortingAgent-BasedSimulationfromGridstoGraphicscardsD r. Ma r iamK i ran

Un iv ers i ty o f B radfordPresentedat:WorkshoponPortabilityAmongHPCArchitecturesforScientificApplicationsSuperComputing2015

AgendafortheTalkIntroduction

Settingthestage:Agent-basedmodelling

IntroducingFLAMEanditsportabilityfromHPCtoGPU

Portabilityproblems– rewritingmodelstomakesurethey‘run’

PossiblefuturedirectionsofusingClouds

Researchchallenges

Conclusions

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Computingworkingwithotherdisciplines

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Distributedandscalablecomputing

ScientificComputing

Complexsystemmodels(economic,biological,social

networks)Emergentbehaviourusingagent-basedmodelling

Agent-basedmodellingonHPCandGPU

(FLAME)www.flame.ac.uk

ModellingandSimulationon

Cloud

Agent-basedModellingEachindividual isapacketofprogrammingcodeallowedtosimulatetogether

Granularity

Interactions

Overcomemostassumptionsinthemodel

Examples innature– birdflockingbehaviour (boids),crowdbehaviour inhumans

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IntroducingFLAMEforbuildingagent-basedmodelsProducedattheUniversityofSheffield,UK.

Flexible Large-scaleAgent-basedModellingenvironment.

BasedonX-machinearchitecture foragents.

Beingusedinawidenumberofprojects(Modellingofcells, tissues,biologicalandeconomicscenariosornetworkingmodels)

Automaticallyproducesparallelisable codeformodels.

Easeofprogrammingfornon-computerexperts.

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FLAMEfilesThis file helps with parallelisation on HPC

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FLAMEadvantagesProducesautomaticallyparallelisable code.

Defaultitrunsinserial.

Butbyjustaddingaflag–p,whilecompiling, itproducesaparallelisable modelcode.

Communicationishandledusinganintelligentmessageboardlibrarywhichcanpooloutrelevantmessages,sort,randomise orfilterthemonanycriteria.

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Libmboard– FLAMEmessageboardlibrary

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SoftwareEngineeringperspective…FlamefollowsastrictX-machinearchitecture foritsagentsallowingittocontain◦ Memory◦ Functions◦ States◦ Messagesinandout

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Portingmodels:fromHPCtoGraphicsCards

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MultiplatformcapabilityYoucanwritemodelseasily

Softwareworksouthowtodistribute

Allyouhavetodoisrun

Needsomeknowledgeofthesystem

Preallocationandmemoryrequirements

Sometimesyouneedtorewritethecompletemodel

Howtotestthemodelrewrittenincorrect?

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FromFLAME

Softwaredoestherest

Samemodelsrunningon(a)differentdistributionsand(b)numberofnodes

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Changingplacementofprocessesonprocessors- samemodelChangingnumberofprocessors- samemodel

Note:FutureworkonCloudsmayintroduceamultitudeofmorefactors–Energy,Cost,OptimalVMplacement,networks,andmanymore

WhataretheperformancecharacteristicsMainperformancewasTime

Doweneedanymore?

-Modelchecking

-Costs

-Eco-efficiency

-Datapatterns– verifyingresults

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HPCversusGPUConsiderablechangesinthesoftwaretoensureitexecutesonGPU:

◦ WritingtheAgents– differentmodeldescriptions

◦ Pre-allocationofAgentmemory– GPUneedsalladvanceknowledge– nodynamicallocationofmemoryispossible

◦ Messagecommunication:needtobreakdownbigger functionsintosimpleronemessagefuntions

◦ SimplerversusComplex– Removedynamicarrays- memoryneedstobesimple

◦ LoopingthroughMessages– Looptraversalisdifferent,rewrite functions

◦ Agentbirthanddeath– Advancememoryallocation

◦ Realtimevisualization– HPCdoesnotallowthis

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LoopingthroughMessagesCodeforHPCneedstointroduceaflag‘finished’toleave thewhile loop.

Elsesimulationhangs!

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GPUimplementation:int MyFunction(xmahine_memory*agent,xmachine_message_list*list){

boolfinished=false;xmachine_message*message=get_first_message(list);while(message){

if(!finished){if(message->id==agent->id){

agent->state+=message->state;finished=true;

}}

message=get_next_message(message,list);}return0;

}

HPCimplementation:int MyFunction (xmahine_memory*agent,xmachine_message_list*list){

xmachine_message*message=get_first_message(list);while(message){

if(message->id==agent->id){agent->state+=message->state;return0;

}message=get_next_message(message,list);}return0;

}

Whataboutcloud?OPENLABS

GIV INGACCESSEVERYWHERE

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Computationally- whymovetowardsCloud?

Issues High performance computing Cloud computingKind of modelsand processing

Processing is limited is somearchitectures

Can introduce dynamicscalability for more complexprocessing.

Cost Access to expensive hardware tomodel and simulate systems.

Resources can be hired asneeded.

Failurerecovery

No fault recovery when disk spaceruns out.

Applications can burst to moreClouds if needed, automatically.

Dynamicchanges in themodel

No real time processing, jobs aresubmitted to a queue, whichmeans real time changes cannotbe incorporated in themodels.

Can execute jobs on the flywhich can read real time datafeeding to the models directly.(very useful for sensor relatedmodels)

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CloudComputationalchallengesrelevanttoABMMemory constraints savedasbigdatasetsService levelagreements

Optimise computationReducetime

ReducecostsEnergyefficientcode

Hideawayasmuchcomputation aspossible

- VMdoing processing- Databeingsaved indataservers

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Researchchallengesstillrelevant1.Languagetocommunicatemodelsbetweenmultiplegroups

2.Automaticallyparsethistooptimaldistributionforprocessing◦ RewritemodelsforGPU,HPC,Cloud?◦ Whataretheperformancemetricsneededbymodellers?

3.Justsavinginformationneeded,globalaverages,specificeventsforverification

‘Openlab’toexecuteandsharemodelsandresults?

Modeldescription

(1)

Particularmodellingtechnique(e.g.ABM)

Parsetoproduceautomatic

parallelisation(2)

Codeexecutes

Resultsaresaved,analysed,visualise(real-time,batch)(3)

Architecturedependency(HPC,GPU,Cloud)

whatisneeded?Globalparameters,

memoryconstraints,additionalprocessing?

Performancemetrics(whattoconsider?)

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ConclusionsSimulationsaregettinglargerandmorecomplex.

Realistic simulationsrequire largerpopulations,ormultiple typesofpopulation,asthevalidityofemergentcharacteristic dependentonboth:theaccuracyofthebehaviour modelledandpopulationsizes.Forecastbehaviours ofsystemsfasterthanthewall-clock time.

Run-timecostsarepresentlyinhibiting theeffectiveuseofABMasforecastingtool.

Agent-basedmodelshavesuccessfullybeenabletouncovernewaspectsofeconomicsystemssuchastheeffectofmigrationonEUlabormarketsoruncoveringsomeunderlying factsinbiological systemsandneedHPC,GPUsandnewertechnologies.

ManymodelswrittenforHPCandGPUshouldportraysimilarcharacteristics, hidingawaymuchofthesoftwarecomplexity fromthenoncomputingscientistsusingthetoolstowritetheirmodelswhichisachallenge initsownright.

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ThankyouandAnyquestions?

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