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Performance and Scalability of

Microsoft SQL Server on VMware vSphere 4

W H I T E P A P E R


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Tbl of Contnts

I n t o d u c t i o n 3

H i g h l i g h t s 3

Pfomnc Tst envionmnt 4

woklod Dscon 4

hd Confguon 5

Sv hd Dscon 5

Sog hd nd Confguon 5

Cln hd 5

Sof Confguon 6

Sof Vsons 6

Sog Lyou 6

Bncmk Modology 7

Sngl Vul Mcn Scl U tss 7

Mull Vul Mcn Scl Ou tss 7

exmns vS 4: Fus nd enncmns 7

Pfomnc rsults 8

Sngl Vul Mcn pfomnc rlv o Nv 8

Mull Vul Mcn pfomnc nd Sclbly 9

pfomnc imc of indvdul Fus 10

Vul Mcn Mono 10

Lg pgs 11

pfomnc imc of vS enncmns 11

Vul Mcn Mono 11

Sog Sck enncmns 11

Nok Ly 12

rsouc Mngmn 12

Conclusion 13

D i s c l i m s 1 3

acknoldgmnts 13

about th autho 13

rfncs 14


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VMware white paper

IntoductionVMware vSphere 4 contains numerous perormance related enhancements that make it easy to virtualize a resource heavy database

with minimal impact to per ormance. The improved resource management capabilities in vSphere acilitate more eectiveconsolidation o multiple SQL Server virtual machines (VMs) on a single host without compromising perormance or scalability.

Greater consolidation can signicantly reduce the cost o physical inrastructure and o licensing SQL Server, even in smaller-scale

environments.

This paper describes a detailed perormance analysis o Microsot SQL Server 2008 running on vSphere. The perormance test places a

signicant load on the CPU, memory, storage, and network subsystems. The results demonstrate efcient and highly scalable

perormance or an enterprise database workload running on a virtual platorm.

To demonstrate the perormance and scalability o the vSphere platorm, the test:

MeasuresperformanceofSQLServer2008inan8virtualCPU(vCPU),58GBvirtualmachineusingahighendOLTPworkloadderived

rom TPC-E1.

Scalestheworkload,database,andvirtualmachineresourcesfrom1vCPUto8vCPUs(scaleuptests).

Consolidatesmultiple2vCPUvirtualmachinesfrom1to8virtualmachines,effectivelyovercommittingthephysicalCPUs(scale out tests).

QuantifiestheperformancegainsfromsomeofthekeynewfeaturesinvSphere.

The ollowing metrics are used to quantiy perormance:

SinglevirtualmachineOLTPthroughputrelativetonative(physicalmachine)performanceinthesameconfiguration.

Aggregatethroughputinaconsolidationenvironment.

HighlightsThe results show vSphere can virtualize large SQL Server deployments with perormance comparable to that on a

physical environment. The experiments show that:

SQLServerrunningina2vCPUvirtualmachineperformedat92percentofaphysicalsystembootedwith2CPUs.

An8vCPUvirtualmachineachieved86percentofphysicalmachineperformance.

The statistics in Table 1 demonstrate the resource intensive nature o the workload.

Table 1. Comparison of workload profiles for physical machine and virtual machine in 8 CPU configuration

Mtic Physicl Mchin Vitul Mchin

tougu n nscons scond* 3557 3060

avg sons m of ll nscons** 234 ms 255 ms

Dsk i/O ougu (iOpS) 29 K 255 K

Dsk i/O lncs 9 ms 8 ms

Nok ck cv

Nok ck snd

10 K/sc

16 K/sc

85 K/sc

8 K/sc

Nok bndd cv

Nok bndd snd

118 Mb/sc

123 Mb/sc

10 Mb/sc

105 Mb/sc

1 See disclaimer on page 13.

*Workload consists o a mix o 10 transactions. Metric reported is the aggregate o all transactions.

**Averageoftheresponsetimesofall10transactionsintheworkload.


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In the consolidation experiments, the workload was run on multiple 2 vCPU SQL Server virtual machines:

AggregatethroughputisshowntoscalelinearlyuntilphysicalCPUsarefullyutilized.

WhenphysicalCPUsareovercommitted,vSphereevenlydistributesresourcestovirtualmachines,whichensurespredictableper-ormance under heavy load.

Pfomnc Tst envionmntIn this section, the workloads characteristics, hardware and sotware congurations, and the testing methodology are described.

The same components were used or both the physical machine and vir tual machine experiments.

Workload DescriptionTheworkloadusedintheseexperimentsismodeledontheTPC-Ebenchmark.ThisworkloadwillbereferredtoastheBrokerage

workload.TheBrokerageworkloadisanon-comparableimplementationoftheTPC-Ebusinessmodel2.

TheTPC-Ebenchmarkusesadatabasetomodelabrokeragefirmwithcustomerswhogeneratetransactionsrelatedtotrades,

account inquiries, and market research. The brokerage irm in turn interacts with inancial markets to execute orders on behal othe customers and updates relevant account inormation.

Thebenchmarkisscalable,meaningthatthenumberofcustomersdefinedforthebrokeragefirmcanbevariedto representthe

workloads o dierent-sized businesses. The benchmark deines the required mix o transactions the benchmark must maintain.

The TPC-E metric is given in transactions per second (tps). It speciically reers to the number o Trade-Result transactions the

server can sustain over a period o time.

TheBrokerageworkloadconsistsoftentransactionsthathaveadenedratioofexecution.Ofthesetransactiontypes,fourupdate

thedatabase,andtheothersareread-only.TheI/Oloadisquiteheavyandconsistsofsmallaccesssizes.ThediskI/Oaccessesconsist

o random reads and writes with a read- to-write ratio o 7:1.

The workload is sized by number o customers dened or the brokerage rm. To put the storage requirements in context, at the

185,000-customerscaleinthe8CPUexperiments,approximately1.5terabytesofstoragewereusedforthedatabase.

In terms o the impact on the system, this workload spends considerable execution time in the operating system kernel contextwhich incurs more virtualization overhead than user-mode code. This workload also was observed to have a large cache resident

workingsetandisverysensitivetothehardwaretranslationlookasidebuer(TLB).Ecientvirtualizationofkernellevelactivity

within the guest operating system code and intelligent scheduling decisions are critical to perormance with this workload.

2 See disclaimer on page 13.


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Hardware ConfigurationThe experiments were run in the VMware perormance laboratory. The test bed consisted o a ser ver running the database sotware

(in both native and virtual environments), a storage backend with sufcient spindles to support the storage bandwidth requirements,

and a client machine running the benchmark driver. Figure 1 is a schematic o the test bed conguration:

Figure 1. Test bed configuration

Server Hardware Description

Table 2. Server hardware

Dll po edg 2970

Dul Sock Qud-Co Sv

269Ghz aMD Oon pocsso 2384

64GB mmoy

Storage Hardware and Configuration

Table 3. Storage hardware

eMC CLarON CX3-40 y

180 15K rpM dsk dvs

LUN confguon fo 8 vCpU vul mcn : 32 d + 1 log LUN n bo Nv nd eSX

LUN confguon fo mull vul mcns : 4 d + 1 log LUN n c VM

Client Hardware

Thesingle-virtualmachinetestswererunwithasingleclient.Anadditionalclientwasusedforthemulti-virtualmachinetestsbecausea

single client benchmark driver could drive only our virtual machines. Table 4 gives the hardware conguration o the two client systems:

Table 4. Client hardware

Dll Po edg 1950 HP Polint DL580 G5

Sngl-sock, qud-co sv Dul-sock, qud-co sv

266Ghz inl Xon X5355 ocsso 29Ghz inl Xon X7350 ocsso

160GB mmoy 64GB mmoy

Software Configuration

2-socket/8 core

AMD server

1Gb direct-attach4-way and 8-way

Intel clients

4Gb/s Fibre

Channel switch

EMC CX3-40,

180 drives

Server Hardware Description


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Software Versions

The operating system sotware, Microsot SQL Server 2008, and benchmark driver programs were identical in both native and

virtual environments.

Table 5. Software Versions

Soft Vsion

VM eSX 40 rtM buld #164009

Ong sysm (gus nd nv) Mcosof wndos Sv 2008

ens (Buld 60001: Svc pck 1)

Dbs mngmn sof Mcosof SQL Sv 2008 ens

edon 100160022

Storage Layout

Measures were taken to ensure there were no hot spots in the storage layout and that the database was uniormly laid out over all

availablespindles.Multiple,ve-diskwide,RAID-0LUNswerecreatedontheEMCCLARiiONCX3-40.WithinWindows,theseLUNswere

convertedtodynamicdiskswithstripedvolumescreatedacrossthem.Eachofthesevolumeswasusedasadataleforthedatabase.

The same database was used or experiments comparing native and virtual environments to ensure that the conguration o the

storagesubsystemwasidenticalforbothexperiments.ThiswasachievedbyimportingthestorageLUNSasRawDiskMapping(RDM)

devicesinESX.AschematicofthestoragelayoutisinFigure 2.

Figure 2. Storage layout

Benchmark Methodology

Windows Server 2008

str

ipe

str

ipe Dynamic disk 1

Dynamic disk 2

VMware ESX

Dynamic disk 3

RDM1 RDM3RDM2

LUN1 LUN3LUN2

str

ipe

str

ipe


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Single Virtual Machine Scale Up Tests

The tests include native and virtual experiments at 1, 2, 4, and 8 CPUs. For the native experiments, the bcdedit Windows utility was

used to speciy the number o processors to be booted. The size o the database, the memory size, and SQL Server buer cache were

careully scaled to ensure the workload prole was unchanged, while getting the best perormance rom the system or each data

point.Allthescaleupexperimentsranat100percentCPUutilizationinnativeandvirtualcongurations.Forexample,at2vCPUs,in

the guest, the workload would saturate both virtual CPUs.Table6 describes the conguration used or each experiment.

Table 6. Brokerage workload configuration for scale up tests

Numb of CPUs Dtbs Scl(Number of Customers)

Numb of UsConnctions

Vitul Mchin/Ntiv Mmoy

SQL Sv BuffCch Siz

1 30,000 65 9GB 7GB

2 60,000 120 16GB 14GB

4 115,000 220 32GB 28GB

8 185,000 440 58GB 535GB

Multiple Virtual Machine Scale Out TestsThe experiment includes identical 2 vCPU virtual machines with the same load applied to each. In order to provide low disk latencies

forthehighvolumeofIOPSfromeachvirtualmachine,thedatadisksforindividualVMsareconguredonexclusivespindlesandtwo

virtual machines shared one log disk. Table 7 describes the conguration used or each vir tual machine in the multi-virtual machine

experiments.

Table 7. Brokerage workload configuration for each 2 vCPU vir tual machine

Dtbs Scl Number of UserConnections

Vitul Mchin Mmoy SQL Sv Buff Cch

20000 35 7GB 5GB

Experiments with vSphere 4: Features and Enhancements

The 4 vCPU conguration mentioned above in Table6wasusedtoobtaintheresultswithESXfeaturesandenhancements.


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Pfomnc rsultsThesectionsbelowdescribetheperformanceresultsofexperimentswiththeBrokerageworkloadonSQLServerinanativeand

virtual environment. Single and multiple virtual machine results are examined, and then results are detailed that show improvementsduetospecicESX4.0features.

Single Virtual Machine Performance Relative to NativeHow vSphere 4 perorms and scales relative to native are shown in Figure 3 below. The results are normalized to the throughput

observed in a 1 CPU native conguration:

Figure 3. Scale-up performance in vSphere 4 compared with native

Thegraphdemonstratesthe1and2vCPUvirtualmachinesperformingat92percentofnative.The4and8vCPUvirtualmachines

achieve88and86percentofthenon-virtualthroughput,respectively.At1,2,and4vCPUsonthe8CPUserver,ESXisabletoeectively

ooadcertaintaskssuchasI/Oprocessingtoidlecores.HavingidleprocessorsalsogivesESXresourcemanagementmoreexibilityin making virtual CPU scheduling decisions. However, even with 8 vCPUs on a ully committed system, vSphere still delivers excellent

perormance relative to the native system.

The scaling in the graph represents the throughput as all aspects o the system are scaled such as number o CPUs, size o the

benchmark database, and SQL Server buer cache memory.Table 8showsESXscalingcomparablytothenativecongurations

ability to scale perormance.

Table 8. Scale up performance

Compison Performance Gain

Nv 8 CpU vs 4 CpU 171

vS 8 vCpU vs 4 vCpU 167

0

1

4

5

6

3

2

1 2 4 8

Throughput

(Normalizedto1CPUNativeResult)

Number of Physical or Virtual CPUs

Native

ESX 4.0


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Multiple Virtual Machine Performance and ScalabilityThese experiments demonstrate that multiple heavy SQL Server vir tual machines can be consolidated to achieve scalable aggregate

throughput with minimal perormance impact to individual virtual machines. Figure 4 shows the total benchmark throughput as

eight2vCPUSQLServervirtualmachinesareaddedtotheBrokerageworkloadontothesingle8-wayhost:

Figure 4. Consolidation of multiple SQL Server virtual machines

Each2vCPUvirtualmachineconsumesabout15percentofthetotalphysicalCPUs,5GBofmemoryintheSQLServerbuercache,

andperformsabout3600I/Ospersecond(IOPS).

Asthegraphdemonstrates,thethroughputincreaseslinearlyasuptofourvirtualmachines(8vCPUs)areadded.AsthephysicalCPUs

wereovercommittedbyincreasingthenumberofvirtualmachinesfromfourtosix(afactorof1.5),theaggregatethroughputincreasesbya

actor o 1.4 .

AddingeightvirtualmachinestothissaturatesthephysicalCPUsonthishost.ESX4.0nowschedules16vCPUsontoeightphysicalCPUs,

yetthebenchmarkaggregatethroughputincreasesafurther5percentastheESXschedulerisabletodelivermorethroughputusing

thefewidlecyclesleftoverinthe6vCPUconguration.Figure5showstheabilityofESXtofairlydistributeresourcesinthe8vCPU

conguration:

Figure 5. Overcommit fairness for 8 virtual machines

0.0

1.0

1.5

0.5

4.0

4.5

5.0

5.5

6.0

3.0

3.5

2.0

0

20

80

100

120

60

40

2.5

1 2 4 6 8

Throughput

(Normalizedto1VMresult)

Physi

calCPUUtilization(%)

Number of 2 vCPU VMs

Linear Performance Improvement Until CPU SaturationCPU

Overcommitted

ESX 4.0

Physical CPU Utilization

CPU Overcommitted(# CPUs > # Physical CPUs)

PercentageofAggregateTh

roughput

forEachVM

Throughput Distribution for 8 x 2 vCPU VMs

75.0

87.5

100.0

62.5

50.0

37.5

0.0

12.5

25.0

VM 4

VM 3

VM 2

VM 1

VM 8

VM 7

VM 6

VM 5


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Table9 highlights the resource intensive nature o the eight virtual machines that were used or the scale out experiments:

Table 9. Aggregate system metrics for eight SQL Server virtual machines

agggt Thoughput inTnsctions p Scond

Host CPU Utilization Disk I/O Thoughput(IOPS)

Network Packet Rate Network Bandwidth

2760 100% 23K 8 K/s cv

75 K/s snd

9 Mb/sc cv

98 Mb/sc snd

Performance Impact of Individual FeaturesInthissection,wequantifytheperformancegainsfromkeyexistingESXfeaturessuchaschoiceinvirtualmachinemonitorandlarge

page support.

Virtual Machine Monitor

Modernx86processorsfromAMDandIntelhavehardwaresupportforCPUinstructionsetandmemorymanagementunit(MMU)

virtualization. More details on these technologies can be ound in [1],[2], and [3].ESX3.5andvSphereeectivelyleveragethese

eatures to reduce the virtualization overhead and increase perormance as compared to native or most workloads.Figure6 details

theimprovementsduetoAMDshardwareMMUassupportedbyVMware.ResultsareshownascomparedtoVMwaresall-software

approach,binarytranslation(BT),andamixedmodeofAMD-VandvSpheressoftwareMMU.

Figure 6. Benefits of hardware assistance for CPU and memory virtualization

Intheseexperiments,enablingAMD-Vresultsinan18percentimprovementinperformancecomparedwithBT.Mostofthe

overhead in binary translation o this workload comes rom the cost o emulating privileged, high resolution timer-related calls used

by SQL Server. RVI provides another 4 percent improvement in perormance. When running on processors that include support or

AMD-VRVI,ESXchoosesRVIasthedefaultmonitortypeforWindowsServer2008guests.

0.80

0.88

0.92

0.84

1.12

1.16

1.20

1.24

1.28

1.04

1.08

0.96

1.00

Binary Translation (BT) Hardware-Assisted CPU

Virtualization

Hardware-Assisted Memory

& CPU Virtualization

ThroughputNormalizedtoBT


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Abriefdescriptionoftheseenhancementsandfeaturesisgivenbelow:

PVSCSI: A New Paravirtualized SCSI Adapter and Driver

ThePVSCSIdriverisinstalledintheguestoperatingsystemaspartofVMwareToolsandsharesI/Orequestandcompletionqueueswiththehypervisor.ThetightercouplingenablesthehypervisortopollforI/Orequestsfromguestandcompleterequests

usinganadaptiveinterruptcoalescingmechanism.ThisbatchingofI/Orequestsandcompletionofinterruptssignificantly

improvestheCPUefficiencyforhandlinglargevolumesofI/Ospersecond(IOPs).

A6percentimprovementinthroughputwiththePVSCSIdriverandadapterisobservedovertheLSILogicparalleladapterandguestdriver.

I/O Concurrency Improvements

InpreviousreleasesofESX,I/OrequestsissuedbytheguestareroutedtotheVMkernelviathevirtualmachinemonitor(VMM).

OncetherequestsreachtheVMkernel,theyexecuteasynchronously.TheexecutionmodelinESX4.0allowstheVMMto

asynchronouslyhandletheI/OrequestsallowingvCPUsintheguesttoexecuteothertasksimmediatelyafterinitiatinganI/O

request.ThisimprovedI/Oconcurrencymodelisdesignedaroundtworingstructuresperadapterwhicharesharedbythe

VMM and the VMkernel.

Theworkloadbenefitedsignificantlyfromthisoptimizationandsawa9percentimprovementinthroughput. Virtual Interrupt Coalescing

InordertofurtherreducetheCPUcostofI/Oinhigh-IOPSworkloads,ESX4.0implementsvirtualinterruptcoalescingtoallow

forbatchingofI/Ocompletionstohappenattheguestlevel.Thisissimilartothephysicalinterruptcoalescingthatisprovidedin

many Fibre Channel host bus adapters.

Withthisoptimization,thediskI/OinterruptratewithinaWindowsServer2008guestwashalfofthatwithinthenativeoperating

system in the 8 vCPU coniguration.

Interrupt Delivery Optimizations

InESX3.5,virtualinterruptsforWindowsguestswerealwaysdeliveredtovCPU0.vSpherepostsinterruptstothevCPUthat

initiatedtheI/O,allowingforbetterscalabilityinsituationswherevCPU0couldbecomeabottleneck.

ESX4.0uniformlydistributesvirtualI/OinterruptstoallvCPUsintheguestfortheBrokerageworkload.

Network Layer

NetworktransmitcoalescingbetweentheclientandserverbenetedthisbenchmarkbytwopercentonvSphere.Transmitcoalescing

wasavailablefortheenhancedvmxnetnetworkingadaptersinceESX3.5anditwasfurtherenhancedinvSphere.Dynamictransmit

coalescing was also added to the E1000g adapter.

In these experiments, the parameter Net.vmxnetThroughputWeight,availablethroughtheAdvancedSoftwareSettingsconguration

tab in the VI Client, was changed rom the deault value 0 to 128, thus avoring transmit throughput over response time.

Settingthisparametercouldincreasenetworktransmitlatenciesandmustbetestedforitsimpactbeforebeingset.Noincreasein

transactionresponsetimeswereobservedfortheBrokerageworkloadduetothissetting.

Resource Management

vSphere includes several enhancements to the CPU scheduler that help signicantly in the single virtual machine as well as multiple

virtual machine perormance and scalability o this workload.

Further Relaxed Co-scheduling & Removal of Cell

Relaxedco-schedulingofvCPUsisallowedinESX3.5buthasbeenfurtherimprovedinESX4.0.InpreviousversionsofESX,the

scheduler would acquire a lock on a group o physical CPUs within which vCPUs o a virtual machine were to be scheduled.

InESX4.0thishasbeenreplacedwithfiner-grainedlocking,reducingschedulingoverheadsincaseswherefrequentscheduling

decisionsareneeded.Boththeseenhancementsgreatlyhelpthescalabilityofmulti-vCPUvirtualmachines.


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Enhanced Topology / Load Aware Scheduling

AgoalofthevSphereCPUresourcescheduleristomakeCPUmigrationdecisionsinordertomaintainprocessorcacheaffinity

while maximizing last level cache capacity.

Cache miss rates can be minimized by always scheduling a vCPU on the same core. However, this can result in delays in scheduling

certaintasksaswellaslowerCPUutilization.Bymakingintelligentmigrationdecisions,theschedulerinESX4.0strikesagood

balance between high CPU utilization and low cache miss rates.

The scheduler also takes into account the processor cache architecture. This is especially important in light o the dierences

between the various processor architectures in the market. Migration algorithms have also been enhanced to take into account

the load on the vCPUs and physical CPUs.

ConclusionTheexperimentsinthispaperdemonstratethatvSphereisoptimizedout-of-the-boxtohandletheCPU,memory,andI/O

requirements o most common SQL Server database congurations. The paper also clearly quantied the perormance gains rom

the improvements in vSphere. These improvements can result in better perormance, higher consolidation ratios, and lower total cost

or each workload.

The results show that perormance is not a barrier or conguring large multi-CPU SQL Server instances in virtual machines or

consolidating multiple virtual machines on a single host to achieve impressive aggregate throughput. The small dierence observed

in perormance between the equivalent deployments on physical and virtual machineswithout employing sophisticated tuning

at the vSphere layerindicate that the benets o virtualization are easily available to most SQL Server installations.

DisclimsAlldataisbasedonin-labresultswiththeRTMreleaseofvSphere4.Ourworkloadwasafair-useimplementationoftheTPC-E

businessmodel;theseresultsarenotTPC-EcompliantandarenotcomparabletoocialTPC-Eresults.TPCBenchmarkandTPC-Eare

trademarks o the Transaction Processing Perormance Council.

The throughput here is not meant to indicate the absolute perormance o Microsot SQL Server 2008, nor to compare its perormance

toanotherDBMS.SQLServerwasusedtoplaceaDBMSworkloadonESX,andobserveandoptimizetheperformanceofESX.

Thegoaloftheexperimentwastoshowtherelative-to-nativeperformanceofESX,anditsabilitytohandleaheavydatabaseworkload. It was not meant to measure the absolute perormance o the hardware and sotware components used in the study.

The throughput o the workload used does not constitute a TPC benchmark result.

acknoldgmntsTheauthorwouldliketothankAravindPavuluri,RezaTaheri,PritiMishra,ChethanKumar,JeBuell,NikhilBhatia,SeongbeomKim,

FeiGuo,WillMonin,ScottDrummonds,KaushikBanerjee,andKrishnaRajafortheirdetailedreviewsandcontributionstosectionsof

this paper.

about th authoPriya Sethuraman is a Senior Perormance Engineer in VMwares Core Perormance Group where she ocuses on optimizing the

perormance o applications in a virtualized environment. She is passionate about perormance and the opportunity to make

softwarerunecientlyonalargesystem.ShepresentedherworkonEnterpriseApplicationPerformanceandScalabilityonESXatVMworldEurope2009.

PriyareceivedherMSinComputerSciencefromUniversityofIllinoisUrbana-Champaign.PriortojoiningVMware,shehadextensive

experienceindatabaseperformanceonUNIXplatforms.


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rfncs[1]AMDVirtualization(AMD-V)Technology.http://www.amd.com/us-en/0,,3715_15781_15785,00.html.RetrievedApril14,2009.

[2]PerformanceEvaluationofAMDRVIhardwareAssist.http://www.vmware.com/pdf/RVI_performance.pdf.

[3]PerformanceEvaluationofIntelEPTHardwareAssist.http://www.vmware.com/pdf/Perf_ESX_Intel-EPT-eval.pdf.

[4]LargePagePerformance.Technicalreport,VMware,2008.http://www.vmware.com/resources/techresources/1039.

[5]ImprovingPerformancewithInterruptCoalescingforVirtualMachineDiskI/OinVMwareESXServer.IrfanAhmad,AjayGulati,and

AliMashtizadeh,SecondInternationalWorkshoponVirtualizationPerformance:Analysis,Characterization,andTools(VPACT09),held

withIEEEInternationalSymposiumonPerformanceAnalysisofSystemsandSoftware(ISPASS),2009.


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