The importance of HPC management software for the enterprise deployment of simulation lifecycle management toolsA Platform Computing white paper

Author:Joseph Cieslak, P.E.Platform Computing jcieslak@platform.com

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Contents1.Introduction________________________________________________________ 2

2.OptimizinguseofdistributedheterogeneousITresources___________________ 4

3.Data-awareschedulingfordisperseddatasets ___________________________ 5

4.Integratingenterpriseenvironmentsusingmultipleworkloadmanagers_______ 6

5.TheintersectionofSLMandcloudcomputing ____________________________ 7

6.Conclusion________________________________________________________ 10

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1. IntroductionSimulationlifecyclemanagement(SLM)isbestdefinedasthecaptureand

managementofengineeringknowledgeacquiredfromcomputer-aided-engineering

orsimulationtoolsperformingproductdesignvalidations.SLMaddressestheneed

fordatamanagement,authentication,historicalreference,processautomation,

collaboration,andIPprotection–thisissimilartotheadvantagesproductlifecycle

management(PLM)hasprovidedfortheusersofcomputer-aided-designtoolsover

thepastdecade.

SLMbenefitsmembersoftheentireengineeringenterprise.Thisrangesfrom

simulationexpertswhowanttospendlesstimemanipulatingfilesandmoretime

focusingontruedesignoptimization,todesigners,managers,andmanufacturing

expertswhocannowbecomeinvolvedatthecriticalconceptualstageofproduct

designwheresimulationhasthegreatestimpact.

SLMprovidesbenefitstotheentireengineeringenterpriseincludingprocess

monitoring,errorhandlingandaconfigurablenotificationanddatamanagement

framework.ButtotakefulladvantageofSLM,severalITinfrastructurechallenges

needtobeaddressed.Thispaperexplainsthenecessityforintegrationsbetween

SLMproductsandworkloadmanagement(WLM)frameworkstomakethemrobust

enoughforenterprise-widedeployment.ItfocusesonmajorareaswherePlatform

Computing’stechnologycanaddimmediatevaluetoSLMfunctionality,including:

• Optimizingtheuseofdistributed,heterogeneousITresources

• Data-awareschedulingfordisperseddatasets

• Integratingenterpriseenvironmentsusingmultipleresourcemanagers

• IntersectionofSLMwithcloudcomputing

ThewhitepaperdrawsonPlatformComputing’sextensiveexperienceinhigh

performancecomputing(HPC)managementsolutionsthatdynamicallyconnect

distributedcomputingresourcesanddatatoworkloaddemandaccordingto

businesspolicies.Since1992,usersofsimulationapplicationsfromavarietyof

marketshavebenefitedbyleveragingintegrationswithPlatformLSF®becauseof

itsadvanceddistributedresourcemanagementfunctionalityforenterprise-wide

computing.PlatformComputingsoftwarehelpsmanagenearlyfivemillionCPUs

aroundtheworld,drivingfasterperformance,deliveringmoreflexiblesharing,and

ultimately,enablingthebestpossibleuseofvaluableITresources.

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2. Optimizing use of distributed heterogeneous IT resourcesLeadingmanufacturingorganizationsaroundtheworld

recognizethattheearlierengineeringsimulation

canbeintroducedintoaproduct’slifecycle,themore

effectiveitisinreducingmanufacturingcostand

acceleratingtimetomarket.Duetorecentadvances

incomputationalprocessingpower,simulationsthat

justafewyearsagowereperformedasdiscrete,

decoupledeventsarenowbeingreplacedbymulti-

disciplinarysimulationscapableofevaluatingseveral

performancevariablesatonetime.Multi-disciplinary

simulationsuseprocessmanagerstocouplevarious

applicationsusedtoevaluatestructural,fluidflow,

electromechanicsandimpactproperties,intoasingle,

virtualprototype.Thisapproachmoreaccurately

representsactualphysicalbehavior.

ManyorganizationshavesuccessfullyusedSLM

techniquesonindividualprojectsoratadepartment

level.However,extendingSLMconceptstoabroader

enterpriseuserbaseisamajorchallenge.IT

organizationsfacedwithcomplexenvironmentshave

typicallydesignedandmanagedtheirinfrastructure

asapplication-orline-of-business-basedsilos.

Historicallythesesilosweredeployedandoptimized

torunasingleprocessorsetofapplications.Athick-clientapplicationhandledalldataaccessand

businesslogic.Today’sSLMproductsuseweb-based

orservices-orientedarchitecturesthatallowfor

network-wideaccessanddatasharingamongusers.

Unfortunatelytheseproductsstillviewcomputing

assetsandthird-partyapplicationsoftwareas

dedicatedresourcesmadeavailablewithoutrules

forprioritization.

SLMtoolsusedinsegregatedworkgroupsaresimple

andmanageableinthiscontextbecausethereareonly

ahandfulofinfrastructurevariablestomanage–e.g.

users,workstations,computeservers,applications

licenses,anddataservers(Figure1).

However,tomakeSLMacomprehensivesolution

foranentireenterpriseseveralITinfrastructure

challengesneedtobeaddressed.Theyinclude:

• HowtointegrateSLM’sservice-orientedarchitecture

(SOA)applicationswithinexistingengineering

computeinfrastructure–SLMprocessmanagers

mayneedtocalloutseveralapplicationsforasingle

multi-disciplinarysimulationincluding:

o Parallelizedimpactandcomputationalfluid

dynamics(CFD)softwareoptimizedforefficiency

onLinuxclusters

o Highendvisualizationtoolsandproprietary

engineeringtoolsonWindows-basedservers

o Computer–aided-designsoftwareforgeometry

creationandspreadsheetsthatrunexclusively

onWindowsworkstations

• ProvidingSLMprocessmanagerswithaccess

togloballydispersedcomputeservers,application

softwareanddatasetsusingheterogeneous

hardwareandoperatingsystemswithoutdisrupting

locally-tunedresourceprioritization

• Securityandtrackingofsimulationprocesses

anddata

Simulation Process& Data Managers

Compute Resources(Heterogenous Enterprise)

File Servers(Applications and Archived Data)

Relational Database(SLM Meta Data)Workstations

(Thick client applications)

Remote Clients(Thin client access)

SOA BasedApplications

Figure1.SLMinfrastructurebuildingblocks

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• Applicationsoftwarelicenseprioritization

andmanagement

• Integrationwithworkstationsandcluster-based

serversthatusenewmulti-coreandGPUchipsets

• Integrationwithhighspeedinterconnectsfor

applicationsthatuseparallelprocessing

• Prioritizationofsimulationeventsbased

onprocessinterdependencies

• Jobmonitoringandadministrationtoassure

effectiveresourceutilization

Tomeetthesechallenges,simulationapplications

havebeenre-written,removingthebarrierscreatedby

theirpreviousclient-serverstructure.Nowoperating

withinaservice-orientedarchitecture(SOA),boththe

applicationanditsassociateddatacanbeaccessedby

userslocatedacrosstheentireengineeringenterprise.

ButjustasSOAreconstitutessimulationsoftware

asaservicetomakeSLMareality,thecomputing

resourcesusedforSLMneedtobevirtualizedas

wellinaservice-orientedinfrastructure(SOI)–this

allowsthesharingofinfrastructurebetweenmultiple

applicationsandusergroups.

PlatformISFprovidesaSOIthatmanagesresource

supplyacrosstheenterprise,decouplingitfrom

resourcedemand.ThisallowsSOA-basedSLM

softwaretosendrequeststhroughPlatformISF,

ensuringthatITresourcesaremadeavailablewhen

andwheretheyareneededtoprovideallconsumers

withappropriateservicelevels(Figure2).

PlatformISFhasbeendesignedtoprovidean

additionallayerofresourcemanagementthat

isoperatingsystemagnostic.Inthecaseofa

SLMprocessmanagerrequiringapplicationsina

predeterminedsequence,PlatformISFmarshals

therequiredresourcesastheyarecalledoutinthe

workflow.Duringthisprocess,PlatformISFallows

discreteinstancesofPlatformLSForotherthird-party

gridandclusterproductstoorchestratetheircurrent

jobs,tasksandsessionsasusual.

Figure2.PlatformISFcomponents

Batch

Process-Oriented

Task-OrientedInteractive API Driven

MPI CLI Parametric SOA VM

Portal-Based

Platform Symphony

ApplicationServices

Self-ServicePortal & APIs

Reporting& Accounting

Service Delivery

Platform LSF

Platform LSF PlatformSymphony Other

Workload Management Adapters

VM ManagerAdapters

Multi-bootAdapter

ExternalManagement Tools

ProvisioningTool Adapters

External CloudProvider

Application Cluster Adapters

Resource Integrations

AmazonWeb Services

Platform ISF

Allocation Engine

Reservation & On-Demand Scheduling

Resource-AwareAllocation Policies

Self-ServiceResource Planning

Calendar-DrivenAllocation

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PlatformISFistheculminationofalmosttwodecades

ofPlatform’sexperienceinmanagingenterprisewide

complexproductiondatacenterswhichneedto:

• DeliverITresourcesfasterwithminimumTCO

• Enablehigherutilizationofresources

• Achieveservicelevelsatlowestpossiblecost

• Reducedatacenteradministrationand

infrastructurecosts

• OptimizeSOAandcloudcomputinginfrastructure

PlatformISFisleveragedbyPlatformLSFand

PlatformSymphony,andisanessentialcomponent

ofSASGridManager,anOEMcomponentprovided

exclusivelybyPlatformComputing(Figure3).

3. Data-aware scheduling for dispersed data setsSLMdrivenapplicationsneedaccesstodatastored

oneitherlocalorremotestorageresourcesinorder

toplacethedataintoanareawhereitcanbeused

byoneorseveralCPUsintheenterpriseexecutinga

simulation.Iftheresourcemanagementsystemdoes

notexplicitlyaccountfortheamountofdataeach

jobneedstoaccess,somejobswilloccupytheCPU

resourcesformuchlongerthannecessary,spending

significantamountsoftimewaitingforfiletransfer.

SinceanHPCsystemcanhaveasmanyas100,000

multi-threadedprocessorsandcancostmanymillions

ofdollars,itisimperativetooperatethesesystems

efficiently.

InatypicalHPCsystem,whilesomejobsarewaiting

fordatatocomein,theCPUcanworkonotherjobs.

However,job-levelschedulersembeddedincurrent

SLMprocessmanagersusuallydonotprovidethislevel

ofoptimizationwhensharingCPUresourceswithother

consumers.Thisresultsinunacceptablethroughput.

Therefore,theadditionofanintelligentscheduling

algorithmiscriticalforthesuccessfulenterprise

deploymentofprocessmanagersorsimulation

lifecyclemanagementsystems.Commerciallyavailable

workloadmanagementsystemslikePlatformLSFsolvetheproblemofstagingmultiplejobsonevery

CPUatthecorelevel.

Inaddition,PlatformComputinghasdesigneda

newsetofdata-awareschedulingpoliciesthatcan

leverageexistingSLMmetadatatofurtheroptimize

theschedulingofjobswithdatasetdependencies.

TheSLMproductsusePlatformLSFandadata-aware

schedulerplug-intoreducejobwaittimes.Thedata-

awarescheduleroptimizesdatastagingversusjob

waittimeinadistributedenvironment.Basedonthe

estimateddatastagingtimeandjobwaittimeineach

location,itmakesintelligentdecisionstoeithermove

Shared resource pool

The HPC Data Center

Platform LSF Platfrom ISF HPC Third-party,in-house WLM

The Corporate Data Center

Enterprise Application Users HPC Application Users

ERP

Figure3.PlatformISFinaheterogeneousenterprise

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thedatatowherethejobisormovethejobtowhere

thedatais.Theschedulerincorporatesmetricssuch

asnetworkbandwidthandtransferlatencytoensure

accurateestimates.

WorkinginconcertwithPlatformLSF,thedata-aware

schedulercanautomatetheprocessofstaginginput

filesfromremotetolocalstorageresources.Itcanalso

increaseutilizationbyoversubscribingthecomputing

resource’sCPUsinordertooverlaydatastagingjobs

withcomputeintensivejobs.And,byintegratingthe

resourcemanagementsystemwiththeSLMmeta-

data,userscanfocusontheirwork,asopposed

toworryingabouttediousdatastaginganddata

managementissues(Figure4).

4. Integrating enterprise environments using multiple workload managers Inaperfectworld,acustomerwoulduseasingle,

resourcemanagementsystemwithauniversal

workloadmanagementschemaforallinfrastructure

assetsinaSLM-drivenenterprise.Butasdiscussed

above,engineeringinfrastructuresareamosaicof

heterogeneousresourcesprovisionedtoaccommodate

theneedsofindividualdepartments,ormaximize

performanceandutilizationforaspecificapplication.

EvenorganizationsstandardizedonaWLM,suchas

PlatformLSF,mayrunseveralindependentinstances

prioritizedforthepeakdemandonsiloedcompute

systems.Asaresult,SLMprocessmanagershavea

difficulttimeintegratingintoexistinginfrastructures.

PlatformISFemploysapracticalapproachdesigned

tosolvetheissuesofintegratingmultipledistributed

resourcemanagerinstances.Itallowsorganizationsto

plug-inprocessmanagerworkloads,whileproviding

individualworkgroupsanddepartmentswiththe

flexibilitytodeploytheWLMsolutionsbestsuited

totheirneeds.PlatformMetaScheduleralsoallows

worktobesubmittedtodisparateschedulerssuchas

SunGridEngine™,OpenPBS,Torque,AltairPBSPro™,

MicrosoftWindowsHPCServer2008,andIBMTivoli

WorkloadSchedulerLoadLeveler™.Thismeansthat

alljobs–includingthoserunningonworkstationsor

remoteclusters–canbecontrolledandmonitored

throughasinglemanagementinterface.From

theperspectiveofbothPlatformComputing’sjob

brokeringutilitiesandweb-basedtoolsinteractingwith

thePlatformISFAPI,jobsrunningonremoteclusters

appearsimilarinallrespects(Figure5).

Figure4.Data-awareschedulingarchitecture

Host 1 Host 3Host 2

D1 D3D2

SLM Platform LSF

Dataset Manager Platform LSF

SCRIPT Input DOE

DOE

Output

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PlatformISFleveragestheexistingfunctionality

inPlatformLSFcontrolsthathandleresources

processing,aswellasapplicationlicensesanddata

staging.ThisallowsPlatformISFtoprovideSLM

productsawaythatenablesuserstoeasilyunify

clusterenvironmentswithouthavingtomanagethe

complexitiesofinteractingwithmultipleworkload

managementsystemswithdifferentinterfacesor

schedulingmethodologies.

5. The intersection of SLM and cloud computingCloudcomputingisoneofthefastestgrowing

segmentsoftheinformationtechnology(IT)

industrybecause,comparedtotraditionalpackaged

applications,itoffersamorecost-effectivealternative

forenterprisestoachievetheirbusinessobjectives.

Thisisanewparadigminwhichsharingbenefits

bothendusersandIT.Bothprivateandpublicsector

organizationsarehighlyinterestedandmovingtoward

potentialadoption.Forexample,theUSGeneral

ServicesAdministration(GSA),whichisresponsible

for$70MillioningovernmentITspending,nowhasa

projectknownasthe“federalcloud.”1

Thetechnologyandbestpracticesdevelopedoverthe

lastdecadeindistributedcomputingarchitectures

suchasclustersandgridshavecontributeddirectly

tothecloudcomputingmodel.Althoughitleverages

recentlydevelopedtechnology,cloudcomputingis

abusiness,notatechnicaltrend,andbecauseofits

recentarrivalonthescene,itoftenmeansdifferent

thingstodifferentpeople.Buteventhoughthereare

manydifferentdefinitionsoftheterm“cloud,”theyall

havefourkeycharacteristicsincommon:

• Infrastructure sharing–Today’senterprisedata

centersarecharacterizedbyfluctuatingresource

demandsfromavarietyofusers.Cloudcomputing

enablesdynamicsharingoftheseresourcessothat

demandscanbemetcosteffectively.

• Scalability–Tohandleeverincreasingworkload

demandsandsupporttheentireenterprise,cloud

computingmusthavetheflexibilitytosignificantly

scaleITresources.Scalabilityandflexibilityallowthe

cloudprovidertofulfill–oratleastcomeclose–to

thepromiseofunlimitedITservicesondemand.

Figure5.PlatformISFwithmultipleworkloadmanagementsystems

Platform LSF

Application A Application B Application C

Sun Grid EngineHPC Server

2008, Scheduler

1Cohen,Reuven,“TheUSFederalGovernmentdefinesCloudComputing”,,May7,2009See:http://www.elasticvapor.com/2009/05/us-federal-government-defines-cloud.html

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• Self service–Cloudcomputingprovidescustomers

withaccesstoITresourcesthroughservice-based

offerings.ThedetailsofITresourcesandtheirsetup

aretransparenttotheusers.

• Pay-per-use–Becausecloudresourcescanbe

addedandremovedaccordingtoworkloaddemand,

userspayforonlywhattheyuseandarenotcharged

whentheirservicedemandsdecrease.

Cloudcomputingprovidesanidealmechanismfor

collaborationanddatasharingbeyondtheboundaries

ofanorganization–acoreconstructforSLM.In

thepast,engineeringinfrastructuressegregated

theircomputeassetsinworkgroupordepartmental

structureswithlittleresourcesharing.Today’sgrid-

enabledinfrastructuresdoprovideamechanismto

shareresourcesbetweenenterprisedepartments

tomaximizeresourceutilization.However,large

engineeringconsortiumsoftenincludemany

individualslocatedaroundtheglobe,aswellas

companiesandtheirsupplychainsthatareoutsidethe

organization’sinfrastructureboundaries(Figure6).

Cloudcomputing’spromiseistheabilitytoprovision

infrastructurequicklyandflexiblybasedonactual

demandandusage.Forexample,avirtualorganization

collaboratingandinteractingintermittentlyona

project-by-projectbasis,willfindthatcloudcomputing

isthemostefficientmechanismforsharingresources.

AlthoughinternalorexternalSLMconsumersdonot

havetoownormanagetheunderlyinginfrastructure,

theydohavecontroloveroperatingsystems,

computingcapacity,storage,deployedapplications,

andnetworkingcomponents.Andsinceuserscan

bebilledonapay-per-usemodel,engineering

organizationscanbenefitfromcostsavings,

performanceimprovements,andenhanced

operatingflexibility.

PlatformComputingisleadingthewayindelivering

cloudtechnologytohelpenterprisesacceleratedata

centerperformancetomatchthespeedofbusiness

demand.Onesuchearlycloudcomputingdeployment

istheSingaporeNationalGridServicedevelopedin

partnershipwithPlatformComputing,Alatum(the

cloudserviceproviderarmofSingaporeTelecom),

Figure6.TheevolutionofengineeringITinfrastructure

Hig

hLo

w

Time

2015Today

Clouds• Virtualization of services• Dynamic service provisioning• On demand, utility, self-service• SaaS, SOA

Grids• Cluster-to-cluster sharing management• Reliable file transfer & staging

Clusters• Workgroup clusters• Optimized for specific applications• Little sharing of compute resources between departments

Enterprise Grid

Distributed Clusters

Public & Private Cloud

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Hewlett-Packard,andothers.Thedeploymentis

alreadyhelpingenterprisesandconsumersbenefit

fromaffordable,secure,on-demand,pay-per-use

accesstohighperformancecomputing,software,and

datastorageservices.PlatformISFenablesdelivery

ofInfrastructure-as-a-Service(IaaS),creatinga

sharedcomputinginfrastructurefromphysicaland

virtualresourcestodeliverapplicationenvironments

accordingtoworkload-awareandresource-aware

policies(Figure7).

TheAlatumcloudallowsconsumerstonotonly

accessbi-directionallysynchronizeddata,buttorent

processing,storage,networks,andotherfundamental

computingresourcesandprovisionrequiredsoftware–

includingSLMapplicationsandoperatingsystems

ondemand2.

PlatformISFistheleadingend-to-endprivatecloud

managementsoftware.Itcreatesasharedcomputing

infrastructurefromphysicalandvirtualresources

todeliverapplicationenvironmentsaccordingto

workload-awareandresource-awarepolicies.The

softwareconsistsofthreelayers:

•Resource integration–Thisfoundationlayer

integratesdistributedandheterogeneousIT

resourcestoformasharedsystem.Allmajor

industrystandardhardware,operatingsystems

(includingLinuxandWindows),andVMhypervisors

(includingVMwareESX,Xen,CitrixXenServer,

MicrosoftHyper-VandRedHatKVM)aresupported.

Thislayercantransparentlyintegrateresources

fromexternalproviderswhilemaintainingitsprivate

cloudmanagementenvironment.

•Allocation engine–Onceapoolofsharedresources

isformed,asetofsite-specificpoliciesisconfigured

intheallocationenginelayertoensurethat

applicationsreceivetherequiredresources.The

policiesalsoensurethattheorganization’sresource

sharingprioritiesareapplied,andthatthequota

constraintsapplicabletobusinessgroupssharing

thecloudarereinforced.Thisprivatecloud“brain”is

criticalforITagility.

•Service delivery–ThistoplayerofPlatformISF

providesinterfacestousersandapplicationsas

wellassupportingthecloudservicemanagement

lifecycle.Aself-serviceportalenablesusersto

requestandobtainphysicalserversandVMsin

minutesinsteadofdaysorweeks.PlatformISFhasasetofAPIsthatcanbecalledbyapplications,

middlewareandworkloadmanagerstorequestand

returnresourceswithouthumanintervention3.

Figure7.Threelayersofinfrastructuredelivered

byPlatformISF

• VMware ESX• Microsoft Hyper-V• Citrix Xen• Red Hat KVM• Sun Solaris Containers• Xen open source

VM• BMC BladeLogic• HP Opsware• Tivoli Provisioning Manager• Symantec Altiris• IBM xCAT• Platform Cluster Manager• Scalent IM

Provisioning• Amazon EC2• IBM CoD• HP Enterprise Services

External Services

Test / Dev HPC J2EE

APPLICATION WORKLOADS

Others

ApplicationServices

Self-ServicePortal & APIs

Reporting& Accounting

Service Delivery

Reservation& On-Demand

Scheduling

Resource-AwareAllocationPolicies

Self-ServiceResourcePlanning

Allocation Engine

VM ManagerAdapters

ProvisioningTool Adapters

ExternalService

Adapters

Resource Integrations

Support for diverse workload

PLATFORM ISF

2AdditionalinformationaboutAlatumandotherPlatformISFusescasesisavailablein“EnterpriseCloudComputing:TransformingIT”,aPlatformwhitepaper(http://www.platform.com/resources/whitepapers),andintheSingaporeNationalGridcustomerSuccessStory(http://www.platform.com/resources/casestudies/Singapore-CS-web.pdf)

3TolearnmoreaboutPlatformISFandcloudcomputingpleasedownloadacopyof“EnterpriseCloudComputing:TransformingIT”,aPlatformComputingwhitepaper(http://www.platform.com/resources/whitepapers)

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6. ConclusionAstheindustrypioneerandlong-timeleaderin

HighPerformanceComputing(HPC)management

software,PlatformComputinghasyearsofexperience

indynamicallyconnectingdistributedcomputing

resourcesanddatatoworkloaddemandaccordingto

businesspoliciesforenterprise-widecomputing.The

companyrecognizestheneedtoworkcollaboratively

withSLMsolutionprovidersandofferthemintegration

pointstoPlatformComputing’sadvanceddistributed

resourcemanagementfunctionalityforcluster,grid,

andcloudcomputing.

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PlatformComputingistheleaderincluster,gridandcloudmanagementsoftware-servingmorethan2,000oftheworld’smostdemandingorganizationsforover17years.OurworkloadandresourcemanagementsolutionsdeliverITresponsivenessandlowercostsforenterpriseandHPCapplications.PlatformhasstrategicrelationshipswithCray,DellTM,HP,IBM®,Intel®,Microsoft®,RedHat®,andSAS®.Visitwww.platform.com.

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